From c3c7e042bbc74e3aa23e4c54d1acb92679a463f6 Mon Sep 17 00:00:00 2001 From: Crussade Date: Tue, 2 Dec 2025 09:31:52 +0100 Subject: [PATCH] training fix. add global settings --- TRANSFER_LEARNING_FEATURE.md | 434 +- add-project.html | 414 +- backend/.gitignore | 80 +- backend/0815/27/exp_infer.py | 28 - backend/1/6/exp.py | 48 + backend/1/6/exp_infer.py | 48 + backend/CONVERSION_SUMMARY.md | 148 - backend/QUICKSTART.md | 226 +- backend/README.md | 214 +- backend/app.py | 91 +- backend/asdf/5/exp_infer.py | 25 - backend/backend/1/1/exp_infer.py | 84 + .../annotations/coco_project_1_test.json | 3634 + .../annotations/coco_project_1_train.json | 57310 ++++++++++++++++ .../annotations/coco_project_1_valid.json | 6874 ++ backend/backend/1/custom_exp_1/exp.py | 84 + backend/check_db.py | 28 +- backend/data/README.md | 280 +- backend/data/__init__.py | 2 +- backend/data/test_base_configs.py | 158 +- backend/data/yolox_l.py | 30 +- backend/data/yolox_m.py | 28 +- backend/data/yolox_s.py | 34 +- backend/data/yolox_x.py | 28 +- backend/database/__init__.py | 8 +- backend/database/database.js | 20 +- backend/database/database.py | 18 +- .../migration_add_image_dimensions.sql | 12 - backend/models/Annotation.js | 80 +- backend/models/Annotation.py | 46 +- backend/models/AnnotationProjectMapping.py | 21 + backend/models/ClassMapping.py | 25 + backend/models/Images.js | 70 +- backend/models/Images.py | 38 +- backend/models/LabelStudioProject.js | 48 +- backend/models/LabelStudioProject.py | 26 +- backend/models/ProjectClass.py | 23 + backend/models/Settings.py | 21 + backend/models/TrainingProject.js | 76 +- backend/models/TrainingProject.py | 64 +- backend/models/TrainingProjectDetails.js | 66 +- backend/models/TrainingProjectDetails.py | 54 +- backend/models/TrainingSize.py | 25 + backend/models/__init__.py | 42 +- backend/models/index.js | 60 +- backend/models/training.js | 280 +- backend/models/training.py | 201 +- backend/requirements.txt | 16 +- backend/routes/__init__.py | 2 +- backend/routes/api.js | 992 +- backend/routes/api.py | 1398 +- backend/server.js | 68 +- backend/services/__init__.py | 2 +- backend/services/fetch-labelstudio.js | 184 +- backend/services/fetch_labelstudio.py | 178 +- backend/services/generate-json-yolox.js | 350 +- backend/services/generate-yolox-exp.js | 268 +- backend/services/generate_json_yolox.py | 467 +- backend/services/generate_yolox_exp.py | 557 +- backend/services/push-yolox-exp.js | 94 +- backend/services/push_yolox_exp.py | 205 +- backend/services/seed-label-studio.js | 240 +- backend/services/seed_label_studio.py | 298 +- backend/services/settings_service.py | 71 + backend/start.py | 28 +- backend/test/7/exp.py | 47 + documentation/Projektdoku.pdf | Bin 0 -> 1631626 bytes documentation/Projektdokumentation.md | 764 + edit-training.html | 1221 +- globals.css | 40 +- index.html | 259 +- js/add-class.js | 308 +- js/add-image.js | 76 +- js/dashboard-label-studio.js | 274 +- js/dashboard.js | 342 +- js/settings.js | 224 + js/setup-training-project.js | 430 +- js/start-training.js | 544 +- js/storage.js | 20 +- overview-training.html | 577 +- project-details.html | 297 +- settings.html | 236 + setup-training-project.html | 283 +- style.css | 1442 +- styleguide.css | 32 +- text.css | 78 +- 86 files changed, 77512 insertions(+), 7054 deletions(-) delete mode 100644 backend/0815/27/exp_infer.py create mode 100644 backend/1/6/exp.py create mode 100644 backend/1/6/exp_infer.py delete mode 100644 backend/CONVERSION_SUMMARY.md delete mode 100644 backend/asdf/5/exp_infer.py create mode 100644 backend/backend/1/1/exp_infer.py create mode 100644 backend/backend/1/custom_exp_1/annotations/coco_project_1_test.json create mode 100644 backend/backend/1/custom_exp_1/annotations/coco_project_1_train.json create mode 100644 backend/backend/1/custom_exp_1/annotations/coco_project_1_valid.json create mode 100644 backend/backend/1/custom_exp_1/exp.py delete mode 100644 backend/database/migration_add_image_dimensions.sql create mode 100644 backend/models/AnnotationProjectMapping.py create mode 100644 backend/models/ClassMapping.py create mode 100644 backend/models/ProjectClass.py create mode 100644 backend/models/Settings.py create mode 100644 backend/models/TrainingSize.py create mode 100644 backend/services/settings_service.py create mode 100644 backend/test/7/exp.py create mode 100644 documentation/Projektdoku.pdf create mode 100644 documentation/Projektdokumentation.md create mode 100644 js/settings.js create mode 100644 settings.html diff --git a/TRANSFER_LEARNING_FEATURE.md b/TRANSFER_LEARNING_FEATURE.md index 8f4bc49..7a19036 100644 --- a/TRANSFER_LEARNING_FEATURE.md +++ b/TRANSFER_LEARNING_FEATURE.md @@ -1,217 +1,217 @@ -# Transfer Learning Base Configuration Feature - -## Overview -This feature implements automatic loading of base configurations when "Train on COCO" transfer learning is selected. Base parameters are loaded from `backend/data/` based on the selected YOLOX model, and these protected fields are displayed as greyed out and non-editable in the frontend. - -## Components Modified/Created - -### Backend - -#### 1. Base Configuration Files (`backend/data/`) -- **`yolox_s.py`** - Base config for YOLOX-Small (depth=0.33, width=0.50) -- **`yolox_m.py`** - Base config for YOLOX-Medium (depth=0.67, width=0.75) -- **`yolox_l.py`** - Base config for YOLOX-Large (depth=1.0, width=1.0) -- **`yolox_x.py`** - Base config for YOLOX-XLarge (depth=1.33, width=1.25) - -Each file contains a `BaseExp` class with protected parameters: -- Model architecture (depth, width, activation) -- Training hyperparameters (max_epoch, warmup_epochs, scheduler, etc.) -- Optimizer settings (momentum, weight_decay) -- Augmentation probabilities (mosaic_prob, mixup_prob, etc.) -- Input/output sizes - -#### 2. Services (`backend/services/generate_yolox_exp.py`) -**New functions:** -- `load_base_config(selected_model)` - Dynamically loads base config using importlib -- Modified `generate_yolox_inference_exp()` to support `use_base_config` parameter -- Base config merging logic: base β†’ user overrides β†’ defaults - -**Behavior:** -- `transfer_learning='coco'` β†’ loads base config + applies user overrides -- `transfer_learning='sketch'` β†’ uses only user-defined values -- Protected parameters from base config are preserved unless explicitly overridden - -#### 3. API Routes (`backend/routes/api.py`) -**New endpoint:** -```python -@api_bp.route('/base-config/', methods=['GET']) -def get_base_config(model_name): -``` -Returns the base configuration JSON for a specific YOLOX model. - -### Frontend - -#### 1. HTML (`edit-training.html`) -**Added:** -- Info banner to indicate when base config is active -- CSS styles for disabled input fields (grey background, not-allowed cursor) -- Visual feedback showing which model's base config is loaded - -**Banner HTML:** -```html - -``` - -**CSS for disabled fields:** -```css -.setting-row input[type="number"]:disabled, -.setting-row input[type="text"]:disabled, -.setting-row input[type="checkbox"]:disabled { - background: #d3d3d3 !important; - color: #666 !important; - cursor: not-allowed !important; - border: 1px solid #999 !important; -} -``` - -#### 2. JavaScript (`js/start-training.js`) -**New functionality:** - -1. **Base Config Loading:** - ```javascript - function loadBaseConfig(modelName) - ``` - Fetches base config from `/api/base-config/` - -2. **Apply Base Config:** - ```javascript - function applyBaseConfig(config, isCocoMode) - ``` - - Applies config values to form fields - - Disables and greys out protected fields - - Shows/hides info banner - - Adds tooltips to disabled fields - -3. **Update Transfer Learning Mode:** - ```javascript - function updateTransferLearningMode() - ``` - - Monitors changes to "Transfer Learning" dropdown - - Monitors changes to "Select Model" dropdown - - Loads appropriate base config when COCO mode is selected - - Clears base config when sketch mode is selected - -4. **Form Submission Enhancement:** - - Temporarily enables disabled fields before submission - - Ensures protected parameters are included in form data - - Re-disables fields after collection - -**Protected Fields List:** -```javascript -const protectedFields = [ - 'depth', 'width', 'act', 'max_epoch', 'warmup_epochs', 'warmup_lr', - 'scheduler', 'no_aug_epochs', 'min_lr_ratio', 'ema', 'weight_decay', - 'momentum', 'input_size', 'mosaic_scale', 'test_size', 'enable_mixup', - 'mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob', 'degrees', - 'translate', 'shear', 'mixup_scale', 'print_interval', 'eval_interval' -]; -``` - -## User Flow - -### 1. Normal Custom Training (Train from sketch) -- User selects model: e.g., "YOLOX-s" -- User selects "Train from sketch" -- All fields are editable (white background) -- User can customize all parameters -- Submission uses user-defined values only - -### 2. COCO Transfer Learning (Train on COCO) -- User selects model: e.g., "YOLOX-s" -- User selects "Train on coco" -- **Automatic actions:** - 1. Frontend calls `/api/base-config/YOLOX-s` - 2. Base config is loaded and applied - 3. Protected fields become greyed out and disabled - 4. Green info banner appears: "πŸ”’ Base Configuration Active" - 5. Tooltip on hover: "Protected by base config for YOLOX-s. Switch to 'Train from sketch' to customize." -- User can still edit non-protected fields -- On submit: both base config values AND user overrides are sent to backend -- Backend generates exp.py with merged settings - -### 3. Switching Models -- User changes from "YOLOX-s" to "YOLOX-l" (while in COCO mode) -- Frontend automatically: - 1. Fetches new base config for YOLOX-l - 2. Updates field values (depth=1.0, width=1.0, etc.) - 3. Updates banner text to show "YOLOX-l" -- Protected parameters update to match new model's architecture - -## Testing - -### Manual Test Steps: - -1. **Test Base Config Loading:** - ```bash - cd backend/data - python test_base_configs.py - ``` - Should display all parameters for yolox-s, yolox-m, yolox-l, yolox-x - -2. **Test API Endpoint:** - ```bash - # Start Flask server - cd backend - python app.py - - # In another terminal: - curl http://localhost:3000/api/base-config/YOLOX-s - ``` - Should return JSON with depth, width, activation, etc. - -3. **Test Frontend:** - - Open `edit-training.html?id=` in browser - - Select "YOLOX-s" model - - Select "Train on coco" β†’ fields should grey out - - Select "Train from sketch" β†’ fields should become editable - - Switch to "YOLOX-l" (in COCO mode) β†’ values should update - - Open browser console and check for: `Applied base config. Protected fields: depth, width, ...` - -4. **Test Form Submission:** - - With COCO mode active (fields greyed out) - - Click "Save Parameters" - - Check browser Network tab β†’ POST to `/api/yolox-settings` - - Verify payload includes protected parameters (depth, width, etc.) - - Check Flask logs for successful save - -### Expected Behaviors: - -βœ… **COCO mode + YOLOX-s:** -- depth: 0.33 (greyed out) -- width: 0.50 (greyed out) -- activation: silu (greyed out) -- Info banner visible - -βœ… **COCO mode + YOLOX-l:** -- depth: 1.0 (greyed out) -- width: 1.0 (greyed out) -- activation: silu (greyed out) - -βœ… **Sketch mode:** -- All fields white/editable -- No info banner -- User can set any values - -## Documentation - -- **`backend/data/README.md`** - Complete guide on base config system -- **`backend/data/test_base_configs.py`** - Test script for base configs - -## Benefits - -1. **Proven defaults:** Users start with battle-tested COCO pretraining settings -2. **Prevents mistakes:** Can't accidentally break model architecture by changing depth/width -3. **Easy customization:** Can still override specific parameters if needed -4. **Visual feedback:** Clear indication of which fields are protected -5. **Model-specific:** Each model (s/m/l/x) has appropriate architecture defaults -6. **Flexible:** Can easily add new models by creating new base config files - -## Future Enhancements - -- Add "Override" button next to protected fields to unlock individual parameters -- Show diff comparison between base config and user overrides -- Add validation warnings if user tries values far from base config ranges -- Export final merged config as preview before training +# Transfer Learning Base Configuration Feature + +## Overview +This feature implements automatic loading of base configurations when "Train on COCO" transfer learning is selected. Base parameters are loaded from `backend/data/` based on the selected YOLOX model, and these protected fields are displayed as greyed out and non-editable in the frontend. + +## Components Modified/Created + +### Backend + +#### 1. Base Configuration Files (`backend/data/`) +- **`yolox_s.py`** - Base config for YOLOX-Small (depth=0.33, width=0.50) +- **`yolox_m.py`** - Base config for YOLOX-Medium (depth=0.67, width=0.75) +- **`yolox_l.py`** - Base config for YOLOX-Large (depth=1.0, width=1.0) +- **`yolox_x.py`** - Base config for YOLOX-XLarge (depth=1.33, width=1.25) + +Each file contains a `BaseExp` class with protected parameters: +- Model architecture (depth, width, activation) +- Training hyperparameters (max_epoch, warmup_epochs, scheduler, etc.) +- Optimizer settings (momentum, weight_decay) +- Augmentation probabilities (mosaic_prob, mixup_prob, etc.) +- Input/output sizes + +#### 2. Services (`backend/services/generate_yolox_exp.py`) +**New functions:** +- `load_base_config(selected_model)` - Dynamically loads base config using importlib +- Modified `generate_yolox_inference_exp()` to support `use_base_config` parameter +- Base config merging logic: base β†’ user overrides β†’ defaults + +**Behavior:** +- `transfer_learning='coco'` β†’ loads base config + applies user overrides +- `transfer_learning='sketch'` β†’ uses only user-defined values +- Protected parameters from base config are preserved unless explicitly overridden + +#### 3. API Routes (`backend/routes/api.py`) +**New endpoint:** +```python +@api_bp.route('/base-config/', methods=['GET']) +def get_base_config(model_name): +``` +Returns the base configuration JSON for a specific YOLOX model. + +### Frontend + +#### 1. HTML (`edit-training.html`) +**Added:** +- Info banner to indicate when base config is active +- CSS styles for disabled input fields (grey background, not-allowed cursor) +- Visual feedback showing which model's base config is loaded + +**Banner HTML:** +```html + +``` + +**CSS for disabled fields:** +```css +.setting-row input[type="number"]:disabled, +.setting-row input[type="text"]:disabled, +.setting-row input[type="checkbox"]:disabled { + background: #d3d3d3 !important; + color: #666 !important; + cursor: not-allowed !important; + border: 1px solid #999 !important; +} +``` + +#### 2. JavaScript (`js/start-training.js`) +**New functionality:** + +1. **Base Config Loading:** + ```javascript + function loadBaseConfig(modelName) + ``` + Fetches base config from `/api/base-config/` + +2. **Apply Base Config:** + ```javascript + function applyBaseConfig(config, isCocoMode) + ``` + - Applies config values to form fields + - Disables and greys out protected fields + - Shows/hides info banner + - Adds tooltips to disabled fields + +3. **Update Transfer Learning Mode:** + ```javascript + function updateTransferLearningMode() + ``` + - Monitors changes to "Transfer Learning" dropdown + - Monitors changes to "Select Model" dropdown + - Loads appropriate base config when COCO mode is selected + - Clears base config when sketch mode is selected + +4. **Form Submission Enhancement:** + - Temporarily enables disabled fields before submission + - Ensures protected parameters are included in form data + - Re-disables fields after collection + +**Protected Fields List:** +```javascript +const protectedFields = [ + 'depth', 'width', 'act', 'max_epoch', 'warmup_epochs', 'warmup_lr', + 'scheduler', 'no_aug_epochs', 'min_lr_ratio', 'ema', 'weight_decay', + 'momentum', 'input_size', 'mosaic_scale', 'test_size', 'enable_mixup', + 'mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob', 'degrees', + 'translate', 'shear', 'mixup_scale', 'print_interval', 'eval_interval' +]; +``` + +## User Flow + +### 1. Normal Custom Training (Train from sketch) +- User selects model: e.g., "YOLOX-s" +- User selects "Train from sketch" +- All fields are editable (white background) +- User can customize all parameters +- Submission uses user-defined values only + +### 2. COCO Transfer Learning (Train on COCO) +- User selects model: e.g., "YOLOX-s" +- User selects "Train on coco" +- **Automatic actions:** + 1. Frontend calls `/api/base-config/YOLOX-s` + 2. Base config is loaded and applied + 3. Protected fields become greyed out and disabled + 4. Green info banner appears: "πŸ”’ Base Configuration Active" + 5. Tooltip on hover: "Protected by base config for YOLOX-s. Switch to 'Train from sketch' to customize." +- User can still edit non-protected fields +- On submit: both base config values AND user overrides are sent to backend +- Backend generates exp.py with merged settings + +### 3. Switching Models +- User changes from "YOLOX-s" to "YOLOX-l" (while in COCO mode) +- Frontend automatically: + 1. Fetches new base config for YOLOX-l + 2. Updates field values (depth=1.0, width=1.0, etc.) + 3. Updates banner text to show "YOLOX-l" +- Protected parameters update to match new model's architecture + +## Testing + +### Manual Test Steps: + +1. **Test Base Config Loading:** + ```bash + cd backend/data + python test_base_configs.py + ``` + Should display all parameters for yolox-s, yolox-m, yolox-l, yolox-x + +2. **Test API Endpoint:** + ```bash + # Start Flask server + cd backend + python app.py + + # In another terminal: + curl http://localhost:3000/api/base-config/YOLOX-s + ``` + Should return JSON with depth, width, activation, etc. + +3. **Test Frontend:** + - Open `edit-training.html?id=` in browser + - Select "YOLOX-s" model + - Select "Train on coco" β†’ fields should grey out + - Select "Train from sketch" β†’ fields should become editable + - Switch to "YOLOX-l" (in COCO mode) β†’ values should update + - Open browser console and check for: `Applied base config. Protected fields: depth, width, ...` + +4. **Test Form Submission:** + - With COCO mode active (fields greyed out) + - Click "Save Parameters" + - Check browser Network tab β†’ POST to `/api/yolox-settings` + - Verify payload includes protected parameters (depth, width, etc.) + - Check Flask logs for successful save + +### Expected Behaviors: + +βœ… **COCO mode + YOLOX-s:** +- depth: 0.33 (greyed out) +- width: 0.50 (greyed out) +- activation: silu (greyed out) +- Info banner visible + +βœ… **COCO mode + YOLOX-l:** +- depth: 1.0 (greyed out) +- width: 1.0 (greyed out) +- activation: silu (greyed out) + +βœ… **Sketch mode:** +- All fields white/editable +- No info banner +- User can set any values + +## Documentation + +- **`backend/data/README.md`** - Complete guide on base config system +- **`backend/data/test_base_configs.py`** - Test script for base configs + +## Benefits + +1. **Proven defaults:** Users start with battle-tested COCO pretraining settings +2. **Prevents mistakes:** Can't accidentally break model architecture by changing depth/width +3. **Easy customization:** Can still override specific parameters if needed +4. **Visual feedback:** Clear indication of which fields are protected +5. **Model-specific:** Each model (s/m/l/x) has appropriate architecture defaults +6. **Flexible:** Can easily add new models by creating new base config files + +## Future Enhancements + +- Add "Override" button next to protected fields to unlock individual parameters +- Show diff comparison between base config and user overrides +- Add validation warnings if user tries values far from base config ranges +- Export final merged config as preview before training diff --git a/add-project.html b/add-project.html index a9b6a35..cd4baa4 100644 --- a/add-project.html +++ b/add-project.html @@ -1,175 +1,241 @@ - - - - - - - - - - - - - -
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+
+ + + + + + + + + + + + + + + + \ No newline at end of file diff --git a/backend/.gitignore b/backend/.gitignore index 01d2e7e..eac320e 100644 --- a/backend/.gitignore +++ b/backend/.gitignore @@ -1,40 +1,40 @@ -# Python -__pycache__/ -*.py[cod] -*$py.class -*.so -.Python -venv/ -env/ -ENV/ -*.egg-info/ -dist/ -build/ - -# Flask -instance/ -.webassets-cache - -# Database -*.db -*.sqlite - -# Environment -.env -.flaskenv - -# IDE -.vscode/ -.idea/ -*.swp -*.swo - -# OS -.DS_Store -Thumbs.db - -# Logs -*.log - -# Uploads -uploads/*.pth +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +venv/ +env/ +ENV/ +*.egg-info/ +dist/ +build/ + +# Flask +instance/ +.webassets-cache + +# Database +*.db +*.sqlite + +# Environment +.env +.flaskenv + +# IDE +.vscode/ +.idea/ +*.swp +*.swo + +# OS +.DS_Store +Thumbs.db + +# Logs +*.log + +# Uploads +uploads/*.pth diff --git a/backend/0815/27/exp_infer.py b/backend/0815/27/exp_infer.py deleted file mode 100644 index 26bd2d1..0000000 --- a/backend/0815/27/exp_infer.py +++ /dev/null @@ -1,28 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Copyright (c) Megvii, Inc. and its affiliates. - -import os - -from yolox.exp import Exp as MyExp - - -class Exp(MyExp): - def __init__(self): - super(Exp, self).__init__() - self.data_dir = "/home/kitraining/To_Annotate/" - self.train_ann = "coco_project_27_train.json" - self.val_ann = "coco_project_27_valid.json" - self.test_ann = "coco_project_27_test.json" - self.num_classes = 80 - self.pretrained_ckpt = r'/home/kitraining/Yolox/YOLOX-main/pretrained/YOLOX-s.pth' - - - self.depth = 1.0 - self.width = 1.0 - self.input_size = (640.0, 640.0) - self.mosaic_scale = (0.1, 2.0) - self.random_size = (10, 20) - self.test_size = (640.0, 640.0) - self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] - self.enable_mixup = False diff --git a/backend/1/6/exp.py b/backend/1/6/exp.py new file mode 100644 index 0000000..07b7223 --- /dev/null +++ b/backend/1/6/exp.py @@ -0,0 +1,48 @@ +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "/home/kitraining/To_Annotate/" + self.train_ann = "coco_project_2_train.json" + self.val_ann = "coco_project_2_valid.json" + self.test_ann = "coco_project_2_test.json" + self.num_classes = 2 + self.pretrained_ckpt = r'/home/kitraining/Yolox/YOLOX-main/pretrained/YOLOX-s.pth' + self.activation = "silu" + self.depth = 0.33 + self.scheduler = "yoloxwarmcos" + self.width = 0.5 + self.input_size = (640.0, 640.0) + self.mosaic_scale = (0.1, 2.0) + self.test_size = (640.0, 640.0) + self.enable_mixup = True + self.max_epoch = 300 + self.warmup_epochs = 5 + self.warmup_lr = 0.0 + self.no_aug_epochs = 15 + self.min_lr_ratio = 0.05 + self.ema = True + self.weight_decay = 0.0005 + self.momentum = 0.9 + self.print_interval = 10 + self.eval_interval = 10 + self.test_conf = 0.01 + self.nms_thre = 0.65 + self.mosaic_prob = 1.0 + self.mixup_prob = 1.0 + self.hsv_prob = 1.0 + self.flip_prob = 0.5 + self.degrees = 10.0 + self.translate = 0.1 + self.shear = 2.0 + self.mixup_scale = (0.5, 1.5) + self.random_size = (10, 20) + self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] diff --git a/backend/1/6/exp_infer.py b/backend/1/6/exp_infer.py new file mode 100644 index 0000000..96a02d7 --- /dev/null +++ b/backend/1/6/exp_infer.py @@ -0,0 +1,48 @@ +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "/home/kitraining/To_Annotate/" + self.train_ann = "coco_project_6_train.json" + self.val_ann = "coco_project_6_valid.json" + self.test_ann = "coco_project_6_test.json" + self.num_classes = 2 + self.pretrained_ckpt = r'/home/kitraining/Yolox/YOLOX-main/pretrained/YOLOX-s.pth' + self.depth = 0.33 + self.width = 0.5 + self.input_size = (640.0, 640.0) + self.mosaic_scale = (0.1, 2.0) + self.test_size = (640.0, 640.0) + self.enable_mixup = True + self.max_epoch = 300 + self.warmup_epochs = 5 + self.warmup_lr = 0.0 + self.scheduler = "yoloxwarmcos" + self.no_aug_epochs = 15 + self.min_lr_ratio = 0.05 + self.ema = True + self.weight_decay = 0.0005 + self.momentum = 0.9 + self.print_interval = 10 + self.eval_interval = 10 + self.test_conf = 0.01 + self.nms_thre = 0.65 + self.mosaic_prob = 1.0 + self.mixup_prob = 1.0 + self.hsv_prob = 1.0 + self.flip_prob = 0.5 + self.degrees = 10.0 + self.translate = 0.1 + self.shear = 2.0 + self.mixup_scale = (0.5, 1.5) + self.activation = "silu" + self.random_size = (10, 20) + self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] diff --git a/backend/CONVERSION_SUMMARY.md b/backend/CONVERSION_SUMMARY.md deleted file mode 100644 index ed977a0..0000000 --- a/backend/CONVERSION_SUMMARY.md +++ /dev/null @@ -1,148 +0,0 @@ -# Backend Conversion Summary - -## βœ… Conversion Complete - -Your Node.js backend has been successfully converted to Python using Flask and SQLAlchemy. - -## πŸ“ New Python Files Created - -### Core Application -- **app.py** - Main Flask application (replaces server.js) -- **start.py** - Startup script for easy launching -- **requirements.txt** - Python dependencies (replaces package.json) - -### Database Layer -- **database/database.py** - SQLAlchemy database configuration (replaces database.js) - -### Models (Sequelize β†’ SQLAlchemy) -- **models/TrainingProject.py** -- **models/TrainingProjectDetails.py** -- **models/training.py** -- **models/LabelStudioProject.py** -- **models/Images.py** -- **models/Annotation.py** -- **models/__init__.py** - -### API Routes -- **routes/api.py** - All API endpoints converted to Flask blueprints (replaces api.js) -- **routes/__init__.py** - -### Services -- **services/fetch_labelstudio.py** - Label Studio API integration -- **services/seed_label_studio.py** - Database seeding logic -- **services/generate_json_yolox.py** - COCO JSON generation -- **services/generate_yolox_exp.py** - YOLOX experiment file generation -- **services/push_yolox_exp.py** - Save training settings to DB -- **services/__init__.py** - -### Documentation -- **README.md** - Comprehensive documentation -- **QUICKSTART.md** - Quick setup guide -- **.gitignore** - Python-specific ignore patterns - -## πŸ”„ Key Changes - -### Technology Stack -| Component | Node.js | Python | -|-----------|---------|--------| -| Framework | Express.js | Flask | -| ORM | Sequelize | SQLAlchemy | -| HTTP Client | node-fetch | requests | -| Package Manager | npm | pip | -| Runtime | Node.js | Python 3.8+ | - -### API Compatibility -βœ… All endpoints preserved with same URLs -βœ… Request/response formats maintained -βœ… Same database schema -βœ… Same business logic - -### Converted Features -- βœ… Training project management -- βœ… Label Studio integration -- βœ… YOLOX configuration and training -- βœ… File upload handling -- βœ… Image and annotation management -- βœ… COCO JSON generation -- βœ… Training logs - -## πŸš€ Getting Started - -1. **Install dependencies:** - ```bash - cd backend - python -m venv venv - .\venv\Scripts\Activate.ps1 # Windows - pip install -r requirements.txt - ``` - -2. **Run the server:** - ```bash - python start.py - ``` - -3. **Server runs at:** `http://0.0.0.0:3000` - -## πŸ“¦ Dependencies Installed - -- Flask 3.0.0 - Web framework -- Flask-CORS 4.0.0 - Cross-origin resource sharing -- Flask-SQLAlchemy 3.1.1 - ORM integration -- SQLAlchemy 2.0.23 - Database ORM -- PyMySQL 1.1.0 - MySQL driver -- requests 2.31.0 - HTTP client -- Pillow 10.1.0 - Image processing - -## ⚠️ Important Notes - -1. **Virtual Environment**: Always activate the virtual environment before running -2. **Database**: MySQL must be running with the `myapp` database created -3. **Credentials**: Update database credentials in `app.py` if needed -4. **Python Version**: Requires Python 3.8 or higher - -## πŸ§ͺ Testing - -Test the conversion: -```bash -# Get all training projects -curl http://localhost:3000/api/training-projects - -# Get Label Studio projects -curl http://localhost:3000/api/label-studio-projects -``` - -## πŸ“ Original Files - -Your original Node.js files remain untouched: -- server.js -- package.json -- routes/api.js -- models/*.js (JavaScript) -- services/*.js (JavaScript) - -You can keep them as backup or remove them once you verify the Python version works correctly. - -## πŸ” What to Verify - -1. βœ… Database connection works -2. βœ… All API endpoints respond correctly -3. βœ… File uploads work -4. βœ… Label Studio integration works -5. βœ… YOLOX training can be triggered -6. βœ… COCO JSON generation works - -## πŸ› Troubleshooting - -See **QUICKSTART.md** for common issues and solutions. - -## πŸ“š Further Documentation - -- **README.md** - Complete project documentation -- **QUICKSTART.md** - Setup guide -- **API Documentation** - All endpoints documented in README.md - ---- - -**Conversion completed successfully!** πŸŽ‰ - -Your backend is now running on Python with Flask and SQLAlchemy. diff --git a/backend/QUICKSTART.md b/backend/QUICKSTART.md index 42707e2..ca97b89 100644 --- a/backend/QUICKSTART.md +++ b/backend/QUICKSTART.md @@ -1,113 +1,113 @@ -# Quick Start Guide - Python Backend - -## Step-by-Step Setup - -### 1. Install Python -Make sure you have Python 3.8 or higher installed: -```bash -python --version -``` - -### 2. Create Virtual Environment -```bash -cd backend -python -m venv venv -``` - -### 3. Activate Virtual Environment - -**Windows:** -```powershell -.\venv\Scripts\Activate.ps1 -``` - -**Linux/Mac:** -```bash -source venv/bin/activate -``` - -### 4. Install Dependencies -```bash -pip install -r requirements.txt -``` - -### 5. Verify Database Connection -Make sure MySQL is running and the database `myapp` exists: -```sql -CREATE DATABASE IF NOT EXISTS myapp; -``` - -### 6. Run the Server -```bash -python start.py -``` - -Or: -```bash -python app.py -``` - -The server should now be running at `http://0.0.0.0:3000` - -## Testing the API - -Test if the server is working: -```bash -curl http://localhost:3000/api/training-projects -``` - -## Common Issues - -### ModuleNotFoundError -If you get import errors, make sure you've activated the virtual environment and installed all dependencies. - -### Database Connection Error -Check that: -- MySQL is running -- Database credentials in `app.py` are correct -- Database `myapp` exists - -### Port Already in Use -If port 3000 is already in use, modify the port in `app.py`: -```python -app.run(host='0.0.0.0', port=3001, debug=True) -``` - -## What Changed from Node.js - -1. **Server Framework**: Express.js β†’ Flask -2. **ORM**: Sequelize β†’ SQLAlchemy -3. **HTTP Client**: node-fetch β†’ requests -4. **Package Manager**: npm β†’ pip -5. **Dependencies**: package.json β†’ requirements.txt -6. **Startup**: `node server.js` β†’ `python app.py` - -## Next Steps - -1. Test all API endpoints -2. Update frontend to point to the new Python backend (if needed) -3. Migrate any remaining Node.js-specific logic -4. Test file uploads and downloads -5. Test YOLOX training functionality - -## File Structure Comparison - -**Before (Node.js):** -``` -backend/ -β”œβ”€β”€ server.js -β”œβ”€β”€ package.json -β”œβ”€β”€ routes/api.js -β”œβ”€β”€ models/*.js -└── services/*.js -``` - -**After (Python):** -``` -backend/ -β”œβ”€β”€ app.py -β”œβ”€β”€ requirements.txt -β”œβ”€β”€ routes/api.py -β”œβ”€β”€ models/*.py -└── services/*.py -``` +# Quick Start Guide - Python Backend + +## Step-by-Step Setup + +### 1. Install Python +Make sure you have Python 3.8 or higher installed: +```bash +python --version +``` + +### 2. Create Virtual Environment +```bash +cd backend +python -m venv venv +``` + +### 3. Activate Virtual Environment + +**Windows:** +```powershell +.\venv\Scripts\Activate.ps1 +``` + +**Linux/Mac:** +```bash +source venv/bin/activate +``` + +### 4. Install Dependencies +```bash +pip install -r requirements.txt +``` + +### 5. Verify Database Connection +Make sure MySQL is running and the database `myapp` exists: +```sql +CREATE DATABASE IF NOT EXISTS myapp; +``` + +### 6. Run the Server +```bash +python start.py +``` + +Or: +```bash +python app.py +``` + +The server should now be running at `http://0.0.0.0:3000` + +## Testing the API + +Test if the server is working: +```bash +curl http://localhost:3000/api/training-projects +``` + +## Common Issues + +### ModuleNotFoundError +If you get import errors, make sure you've activated the virtual environment and installed all dependencies. + +### Database Connection Error +Check that: +- MySQL is running +- Database credentials in `app.py` are correct +- Database `myapp` exists + +### Port Already in Use +If port 3000 is already in use, modify the port in `app.py`: +```python +app.run(host='0.0.0.0', port=3001, debug=True) +``` + +## What Changed from Node.js + +1. **Server Framework**: Express.js β†’ Flask +2. **ORM**: Sequelize β†’ SQLAlchemy +3. **HTTP Client**: node-fetch β†’ requests +4. **Package Manager**: npm β†’ pip +5. **Dependencies**: package.json β†’ requirements.txt +6. **Startup**: `node server.js` β†’ `python app.py` + +## Next Steps + +1. Test all API endpoints +2. Update frontend to point to the new Python backend (if needed) +3. Migrate any remaining Node.js-specific logic +4. Test file uploads and downloads +5. Test YOLOX training functionality + +## File Structure Comparison + +**Before (Node.js):** +``` +backend/ +β”œβ”€β”€ server.js +β”œβ”€β”€ package.json +β”œβ”€β”€ routes/api.js +β”œβ”€β”€ models/*.js +└── services/*.js +``` + +**After (Python):** +``` +backend/ +β”œβ”€β”€ app.py +β”œβ”€β”€ requirements.txt +β”œβ”€β”€ routes/api.py +β”œβ”€β”€ models/*.py +└── services/*.py +``` diff --git a/backend/README.md b/backend/README.md index f5d7fb1..e8a097b 100644 --- a/backend/README.md +++ b/backend/README.md @@ -1,107 +1,107 @@ -# Python Backend for COCO Tool - -This is the converted Python backend using Flask and SQLAlchemy. - -## Setup - -1. Create a virtual environment (recommended): -```bash -python -m venv venv -``` - -2. Activate the virtual environment: - - Windows: `venv\Scripts\activate` - - Linux/Mac: `source venv/bin/activate` - -3. Install dependencies: -```bash -pip install -r requirements.txt -``` - -## Running the Server - -### Option 1: Using start.py -```bash -python start.py -``` - -### Option 2: Using Flask directly -```bash -python app.py -``` - -### Option 3: Using Flask CLI -```bash -flask --app app run --host=0.0.0.0 --port=3000 -``` - -The server will start on `http://0.0.0.0:3000` - -## Database Configuration - -The database configuration is in `database/database.py`. Default settings: -- Host: localhost -- Database: myapp -- User: root -- Password: root - -Modify `app.py` to change these settings. - -## Project Structure - -``` -backend/ -β”œβ”€β”€ app.py # Main Flask application -β”œβ”€β”€ start.py # Startup script -β”œβ”€β”€ requirements.txt # Python dependencies -β”œβ”€β”€ database/ -β”‚ └── database.py # Database configuration -β”œβ”€β”€ models/ # SQLAlchemy models -β”‚ β”œβ”€β”€ __init__.py -β”‚ β”œβ”€β”€ Annotation.py -β”‚ β”œβ”€β”€ Images.py -β”‚ β”œβ”€β”€ LabelStudioProject.py -β”‚ β”œβ”€β”€ training.py -β”‚ β”œβ”€β”€ TrainingProject.py -β”‚ └── TrainingProjectDetails.py -β”œβ”€β”€ routes/ -β”‚ └── api.py # API endpoints -└── services/ # Business logic - β”œβ”€β”€ fetch_labelstudio.py - β”œβ”€β”€ generate_json_yolox.py - β”œβ”€β”€ generate_yolox_exp.py - β”œβ”€β”€ push_yolox_exp.py - └── seed_label_studio.py -``` - -## API Endpoints - -All endpoints are prefixed with `/api`: - -- `GET /api/seed` - Seed database from Label Studio -- `POST /api/generate-yolox-json` - Generate YOLOX training files -- `POST /api/start-yolox-training` - Start YOLOX training -- `GET /api/training-log` - Get training logs -- `GET/POST /api/training-projects` - Manage training projects -- `GET /api/label-studio-projects` - Get Label Studio projects -- `GET/POST/PUT /api/training-project-details` - Manage project details -- `POST /api/yolox-settings` - Save YOLOX settings -- `GET/DELETE /api/trainings` - Manage trainings -- `DELETE /api/training-projects/:id` - Delete training project - -## Migration Notes - -This is a direct conversion from Node.js/Express to Python/Flask: -- Express β†’ Flask -- Sequelize ORM β†’ SQLAlchemy ORM -- node-fetch β†’ requests library -- Async routes maintained where needed -- All file paths and logic preserved from original - -## Differences from Node.js Version - -1. Python uses async/await differently - some routes may need adjustments -2. File handling uses Python's built-in open() instead of fs module -3. Subprocess calls use Python's subprocess module -4. JSON handling uses Python's json module -5. Path operations use os.path instead of Node's path module +# Python Backend for COCO Tool + +This is the converted Python backend using Flask and SQLAlchemy. + +## Setup + +1. Create a virtual environment (recommended): +```bash +python -m venv venv +``` + +2. Activate the virtual environment: + - Windows: `venv\Scripts\activate` + - Linux/Mac: `source venv/bin/activate` + +3. Install dependencies: +```bash +pip install -r requirements.txt +``` + +## Running the Server + +### Option 1: Using start.py +```bash +python start.py +``` + +### Option 2: Using Flask directly +```bash +python app.py +``` + +### Option 3: Using Flask CLI +```bash +flask --app app run --host=0.0.0.0 --port=3000 +``` + +The server will start on `http://0.0.0.0:3000` + +## Database Configuration + +The database configuration is in `database/database.py`. Default settings: +- Host: localhost +- Database: myapp +- User: root +- Password: root + +Modify `app.py` to change these settings. + +## Project Structure + +``` +backend/ +β”œβ”€β”€ app.py # Main Flask application +β”œβ”€β”€ start.py # Startup script +β”œβ”€β”€ requirements.txt # Python dependencies +β”œβ”€β”€ database/ +β”‚ └── database.py # Database configuration +β”œβ”€β”€ models/ # SQLAlchemy models +β”‚ β”œβ”€β”€ __init__.py +β”‚ β”œβ”€β”€ Annotation.py +β”‚ β”œβ”€β”€ Images.py +β”‚ β”œβ”€β”€ LabelStudioProject.py +β”‚ β”œβ”€β”€ training.py +β”‚ β”œβ”€β”€ TrainingProject.py +β”‚ └── TrainingProjectDetails.py +β”œβ”€β”€ routes/ +β”‚ └── api.py # API endpoints +└── services/ # Business logic + β”œβ”€β”€ fetch_labelstudio.py + β”œβ”€β”€ generate_json_yolox.py + β”œβ”€β”€ generate_yolox_exp.py + β”œβ”€β”€ push_yolox_exp.py + └── seed_label_studio.py +``` + +## API Endpoints + +All endpoints are prefixed with `/api`: + +- `GET /api/seed` - Seed database from Label Studio +- `POST /api/generate-yolox-json` - Generate YOLOX training files +- `POST /api/start-yolox-training` - Start YOLOX training +- `GET /api/training-log` - Get training logs +- `GET/POST /api/training-projects` - Manage training projects +- `GET /api/label-studio-projects` - Get Label Studio projects +- `GET/POST/PUT /api/training-project-details` - Manage project details +- `POST /api/yolox-settings` - Save YOLOX settings +- `GET/DELETE /api/trainings` - Manage trainings +- `DELETE /api/training-projects/:id` - Delete training project + +## Migration Notes + +This is a direct conversion from Node.js/Express to Python/Flask: +- Express β†’ Flask +- Sequelize ORM β†’ SQLAlchemy ORM +- node-fetch β†’ requests library +- Async routes maintained where needed +- All file paths and logic preserved from original + +## Differences from Node.js Version + +1. Python uses async/await differently - some routes may need adjustments +2. File handling uses Python's built-in open() instead of fs module +3. Subprocess calls use Python's subprocess module +4. JSON handling uses Python's json module +5. Path operations use os.path instead of Node's path module diff --git a/backend/app.py b/backend/app.py index fcd1cdc..727aa4e 100644 --- a/backend/app.py +++ b/backend/app.py @@ -1,43 +1,48 @@ -from flask import Flask, send_from_directory -from flask_cors import CORS -import os -from database.database import db, init_db - -app = Flask(__name__, static_folder='..', static_url_path='') -CORS(app) - -# Configure database -app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql+pymysql://root:root@localhost/myapp' -app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False - -# Initialize database -db.init_app(app) - -# Import and register blueprints -from routes.api import api_bp -app.register_blueprint(api_bp, url_prefix='/api') - -# Serve static files (HTML, CSS, JS) -@app.route('/') -def index(): - return send_from_directory('..', 'index.html') - -@app.route('/') -def serve_static(path): - return send_from_directory('..', path) - -# Initialize DB and start server -if __name__ == '__main__': - with app.app_context(): - try: - # Test database connection - db.engine.connect() - print('DB connection established.') - - # Create tables if they don't exist - db.create_all() - - # Start server - app.run(host='0.0.0.0', port=3000, debug=True) - except Exception as err: - print(f'Failed to start: {err}') +from flask import Flask, send_from_directory +from flask_cors import CORS +import os +from database.database import db, init_db + +app = Flask(__name__, static_folder='..', static_url_path='') +CORS(app) + +# Configure database +app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql+pymysql://root:root@localhost/myapp2' +app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False + +# Initialize database +db.init_app(app) + +# Import and register blueprints +from routes.api import api_bp +app.register_blueprint(api_bp, url_prefix='/api') + +# Serve static files (HTML, CSS, JS) +@app.route('/') +def index(): + return send_from_directory('..', 'index.html') + +@app.route('/') +def serve_static(path): + return send_from_directory('..', path) + +# Initialize DB and start server +if __name__ == '__main__': + with app.app_context(): + try: + # Test database connection + db.engine.connect() + print('DB connection established.') + + # Create tables if they don't exist + db.create_all() + + # Initialize default settings + from services.settings_service import initialize_default_settings + initialize_default_settings() + print('Settings initialized.') + + # Start server + app.run(host='0.0.0.0', port=4000, debug=True) + except Exception as err: + print(f'Failed to start: {err}') diff --git a/backend/asdf/5/exp_infer.py b/backend/asdf/5/exp_infer.py deleted file mode 100644 index de775e4..0000000 --- a/backend/asdf/5/exp_infer.py +++ /dev/null @@ -1,25 +0,0 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Copyright (c) Megvii, Inc. and its affiliates. - -import os - -from yolox.exp import Exp as MyExp - - -class Exp(MyExp): - def __init__(self): - super(Exp, self).__init__() - self.data_dir = "/home/kitraining/To_Annotate/" - self.train_ann = "coco_project_5_train.json" - self.val_ann = "coco_project_5_valid.json" - self.test_ann = "coco_project_5_test.json" - self.num_classes = 4 - self.depth = 1.0 - self.width = 1.0 - self.input_size = (640, 640) - self.mosaic_scale = (0.1, 2) - self.random_size = (10, 20) - self.test_size = (640, 640) - self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] - self.enable_mixup = False diff --git a/backend/backend/1/1/exp_infer.py b/backend/backend/1/1/exp_infer.py new file mode 100644 index 0000000..63b48ce --- /dev/null +++ b/backend/backend/1/1/exp_infer.py @@ -0,0 +1,84 @@ +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "/home/kitraining/To_Annotate" # Where images are located + self.annotations_dir = "./backend/1/custom_exp_1" # Where annotation JSONs are located + self.train_ann = "coco_project_1_train.json" + self.val_ann = "coco_project_1_valid.json" + self.test_ann = "coco_project_1_test.json" + self.num_classes = 2 + # Disable train2017 subdirectory - our images are directly in data_dir + self.name = "" + # Set data workers for training + self.data_num_workers = 8 + self.depth = 1.0 + self.width = 1.0 + self.input_size = (640.0, 640.0) + self.mosaic_scale = (0.1, 2.0) + self.test_size = (640.0, 640.0) + self.enable_mixup = True + self.max_epoch = 300 + self.warmup_epochs = 5 + self.warmup_lr = 0.0 + self.scheduler = "yoloxwarmcos" + self.no_aug_epochs = 15 + self.min_lr_ratio = 0.05 + self.ema = True + self.weight_decay = 0.0005 + self.momentum = 0.9 + self.print_interval = 10 + self.eval_interval = 10 + self.test_conf = 0.01 + self.nms_thre = 0.65 + self.mosaic_prob = 1.0 + self.mixup_prob = 1.0 + self.hsv_prob = 1.0 + self.flip_prob = 0.5 + self.degrees = 10.0 + self.translate = 0.1 + self.shear = 2.0 + self.mixup_scale = (0.5, 1.5) + self.activation = "silu" + self.random_size = (10, 20) + + def get_dataset(self, cache=False, cache_type="ram"): + """Override to use name parameter for images directory""" + from yolox.data import COCODataset + + # COCODataset constructs image paths as: os.path.join(data_dir, name, file_name) + # YOLOX adds "annotations/" to data_dir automatically, so we pass annotations_dir directly + # Use empty string for name since we have absolute paths in JSON + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.train_ann, + name="", + img_size=self.input_size, + preproc=self.preproc if hasattr(self, 'preproc') else None, + cache=cache, + cache_type=cache_type, + ) + + def get_eval_dataset(self, **kwargs): + """Override eval dataset using name parameter""" + from yolox.data import COCODataset + + testdev = kwargs.get("testdev", False) + legacy = kwargs.get("legacy", False) + + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.val_ann if not testdev else self.test_ann, + name="", + img_size=self.test_size, + preproc=None, # No preprocessing for evaluation + ) + self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] diff --git a/backend/backend/1/custom_exp_1/annotations/coco_project_1_test.json b/backend/backend/1/custom_exp_1/annotations/coco_project_1_test.json new file mode 100644 index 0000000..9637898 --- /dev/null +++ b/backend/backend/1/custom_exp_1/annotations/coco_project_1_test.json @@ -0,0 +1,3634 @@ +{ + "images": [ + { + "id": 794, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_4\\videorecorded7\\videorecorded7_0028.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 193, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_4\\videorecorded2\\videorecorded2_0030.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 693, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_1\\videorecorded6\\videorecorded6_0018.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 826, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_4\\videorecorded7\\videorecorded7_0060.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 178, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_4\\videorecorded2\\videorecorded2_0025.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 340, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_1\\videorecorded4\\videorecorded4_0011.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 109, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_4\\videorecorded1\\videorecorded1_0053.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 279, + "file_name": "\\home\\kitraining\\To_Annotate/Baby\\RUN_3\\videorecorded3\\videorecorded3_0023.jpg", + "width": 1280.0, + "height": 720.0 + }, + { + "id": 613, + "file_name": 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/dev/null +++ b/backend/backend/1/custom_exp_1/exp.py @@ -0,0 +1,84 @@ +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "/home/kitraining/To_Annotate" # Where images are located + self.annotations_dir = "./backend/1/custom_exp_1" # Where annotation JSONs are located + self.train_ann = "coco_project_1_train.json" + self.val_ann = "coco_project_1_valid.json" + self.test_ann = "coco_project_1_test.json" + self.num_classes = 2 + # Disable train2017 subdirectory - our images are directly in data_dir + self.name = "" + # Set data workers for training + self.data_num_workers = 8 + self.depth = 1.0 + self.width = 1.0 + self.input_size = (640.0, 640.0) + self.mosaic_scale = (0.1, 2.0) + self.test_size = (640.0, 640.0) + self.enable_mixup = True + self.max_epoch = 300 + self.warmup_epochs = 5 + self.warmup_lr = 0.0 + self.scheduler = "yoloxwarmcos" + self.no_aug_epochs = 15 + self.min_lr_ratio = 0.05 + self.ema = True + self.weight_decay = 0.0005 + self.momentum = 0.9 + self.print_interval = 10 + self.eval_interval = 10 + self.test_conf = 0.01 + self.nms_thre = 0.65 + self.mosaic_prob = 1.0 + self.mixup_prob = 1.0 + self.hsv_prob = 1.0 + self.flip_prob = 0.5 + self.degrees = 10.0 + self.translate = 0.1 + self.shear = 2.0 + self.mixup_scale = (0.5, 1.5) + self.activation = "silu" + self.random_size = (10, 20) + + def get_dataset(self, cache=False, cache_type="ram"): + """Override to use name parameter for images directory""" + from yolox.data import COCODataset + + # COCODataset constructs image paths as: os.path.join(data_dir, name, file_name) + # YOLOX adds "annotations/" to data_dir automatically, so we pass annotations_dir directly + # Use empty string for name since we have absolute paths in JSON + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.train_ann, + name="", + img_size=self.input_size, + preproc=self.preproc if hasattr(self, 'preproc') else None, + cache=cache, + cache_type=cache_type, + ) + + def get_eval_dataset(self, **kwargs): + """Override eval dataset using name parameter""" + from yolox.data import COCODataset + + testdev = kwargs.get("testdev", False) + legacy = kwargs.get("legacy", False) + + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.val_ann if not testdev else self.test_ann, + name="", + img_size=self.test_size, + preproc=None, # No preprocessing for evaluation + ) + self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] diff --git a/backend/check_db.py b/backend/check_db.py index 26060c4..aae97a1 100644 --- a/backend/check_db.py +++ b/backend/check_db.py @@ -1,14 +1,14 @@ -import pymysql - -conn = pymysql.connect(host='localhost', user='root', password='root', database='myapp') -cursor = conn.cursor() -cursor.execute('DESCRIBE image') -rows = cursor.fetchall() - -print("Current 'image' table structure:") -print("-" * 60) -for row in rows: - print(f"Field: {row[0]:<15} Type: {row[1]:<15} Null: {row[2]}") -print("-" * 60) - -conn.close() +import pymysql + +conn = pymysql.connect(host='localhost', user='root', password='root', database='myapp2') +cursor = conn.cursor() +cursor.execute('DESCRIBE image') +rows = cursor.fetchall() + +print("Current 'image' table structure:") +print("-" * 60) +for row in rows: + print(f"Field: {row[0]:<15} Type: {row[1]:<15} Null: {row[2]}") +print("-" * 60) + +conn.close() diff --git a/backend/data/README.md b/backend/data/README.md index 613cd66..fa4e58e 100644 --- a/backend/data/README.md +++ b/backend/data/README.md @@ -1,140 +1,140 @@ -# YOLOX Base Configuration System - -## Overview - -This directory contains base experiment configurations for YOLOX models. These configurations define "protected" parameters that are preserved during transfer learning from COCO-pretrained models. - -## How It Works - -### Transfer Learning Flow - -1. **COCO Transfer Learning** (`transfer_learning = 'coco'`): - - Loads base configuration from `data/yolox_*.py` based on `selected_model` - - Base parameters are **protected** and used as defaults - - User settings from the form only override what's explicitly set - - Result: Best of both worlds - proven COCO settings + your customizations - -2. **Sketch/Custom Training** (`transfer_learning = 'sketch'`): - - No base configuration loaded - - Uses only user-defined parameters from the training form - - Full control over all settings - -### Base Configuration Files - -- `yolox_s.py` - YOLOX-Small (depth=0.33, width=0.50) -- `yolox_m.py` - YOLOX-Medium (depth=0.67, width=0.75) -- `yolox_l.py` - YOLOX-Large (depth=1.0, width=1.0) -- `yolox_x.py` - YOLOX-XLarge (depth=1.33, width=1.25) - -### Protected Parameters - -These parameters are defined in base configs and **preserved** unless explicitly overridden: - -**Model Architecture:** -- `depth` - Model depth multiplier -- `width` - Model width multiplier -- `activation` - Activation function (silu) - -**Training Hyperparameters:** -- `basic_lr_per_img` - Learning rate per image -- `scheduler` - LR scheduler (yoloxwarmcos) -- `warmup_epochs` - Warmup epochs -- `max_epoch` - Maximum training epochs -- `no_aug_epochs` - No augmentation epochs -- `min_lr_ratio` - Minimum LR ratio - -**Optimizer:** -- `momentum` - SGD momentum -- `weight_decay` - Weight decay - -**Augmentation:** -- `mosaic_prob` - Mosaic probability -- `mixup_prob` - Mixup probability -- `hsv_prob` - HSV augmentation probability -- `flip_prob` - Flip probability -- `degrees` - Rotation degrees -- `translate` - Translation -- `shear` - Shear -- `mosaic_scale` - Mosaic scale range -- `mixup_scale` - Mixup scale range -- `enable_mixup` - Enable mixup - -**Input/Output:** -- `input_size` - Training input size -- `test_size` - Testing size -- `random_size` - Random size range - -**Evaluation:** -- `eval_interval` - Evaluation interval -- `print_interval` - Print interval - -## Customizing Base Configurations - -### Adding a New Model - -Create a new file `data/yolox_MODELNAME.py`: - -```python -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Base configuration for YOLOX-MODELNAME - -class BaseExp: - """Base experiment configuration for YOLOX-MODELNAME""" - - # Define protected parameters - depth = 1.0 - width = 1.0 - # ... other parameters -``` - -### Modifying Parameters - -Edit the corresponding `yolox_*.py` file and update the `BaseExp` class attributes. - -**Example:** To change YOLOX-S max epochs: -```python -# In data/yolox_s.py -class BaseExp: - max_epoch = 500 # Changed from 300 - # ... other parameters -``` - -## Parameter Priority - -The merge logic follows this priority (highest to lowest): - -1. **User form values** (if explicitly set, not None) -2. **Base config values** (if transfer_learning='coco') -3. **Default fallbacks** (hardcoded minimums) - -## Example - -### COCO Transfer Learning -``` -User sets in form: max_epoch=100, depth=0.5 -Base config (yolox_s.py) has: depth=0.33, width=0.50, max_epoch=300 - -Result: depth=0.5 (user override), width=0.50 (base), max_epoch=100 (user override) -``` - -### Sketch Training -``` -User sets in form: max_epoch=100, depth=0.5 -No base config loaded - -Result: depth=0.5 (user), max_epoch=100 (user), width=1.0 (default fallback) -``` - -## Debugging - -To see which base config was loaded, check Flask logs: -``` -Loaded base config for yolox-s: ['depth', 'width', 'activation', ...] -``` - -If base config fails to load: -``` -Warning: Could not load base config for yolox-s: [error message] -Falling back to custom settings only -``` +# YOLOX Base Configuration System + +## Overview + +This directory contains base experiment configurations for YOLOX models. These configurations define "protected" parameters that are preserved during transfer learning from COCO-pretrained models. + +## How It Works + +### Transfer Learning Flow + +1. **COCO Transfer Learning** (`transfer_learning = 'coco'`): + - Loads base configuration from `data/yolox_*.py` based on `selected_model` + - Base parameters are **protected** and used as defaults + - User settings from the form only override what's explicitly set + - Result: Best of both worlds - proven COCO settings + your customizations + +2. **Sketch/Custom Training** (`transfer_learning = 'sketch'`): + - No base configuration loaded + - Uses only user-defined parameters from the training form + - Full control over all settings + +### Base Configuration Files + +- `yolox_s.py` - YOLOX-Small (depth=0.33, width=0.50) +- `yolox_m.py` - YOLOX-Medium (depth=0.67, width=0.75) +- `yolox_l.py` - YOLOX-Large (depth=1.0, width=1.0) +- `yolox_x.py` - YOLOX-XLarge (depth=1.33, width=1.25) + +### Protected Parameters + +These parameters are defined in base configs and **preserved** unless explicitly overridden: + +**Model Architecture:** +- `depth` - Model depth multiplier +- `width` - Model width multiplier +- `activation` - Activation function (silu) + +**Training Hyperparameters:** +- `basic_lr_per_img` - Learning rate per image +- `scheduler` - LR scheduler (yoloxwarmcos) +- `warmup_epochs` - Warmup epochs +- `max_epoch` - Maximum training epochs +- `no_aug_epochs` - No augmentation epochs +- `min_lr_ratio` - Minimum LR ratio + +**Optimizer:** +- `momentum` - SGD momentum +- `weight_decay` - Weight decay + +**Augmentation:** +- `mosaic_prob` - Mosaic probability +- `mixup_prob` - Mixup probability +- `hsv_prob` - HSV augmentation probability +- `flip_prob` - Flip probability +- `degrees` - Rotation degrees +- `translate` - Translation +- `shear` - Shear +- `mosaic_scale` - Mosaic scale range +- `mixup_scale` - Mixup scale range +- `enable_mixup` - Enable mixup + +**Input/Output:** +- `input_size` - Training input size +- `test_size` - Testing size +- `random_size` - Random size range + +**Evaluation:** +- `eval_interval` - Evaluation interval +- `print_interval` - Print interval + +## Customizing Base Configurations + +### Adding a New Model + +Create a new file `data/yolox_MODELNAME.py`: + +```python +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Base configuration for YOLOX-MODELNAME + +class BaseExp: + """Base experiment configuration for YOLOX-MODELNAME""" + + # Define protected parameters + depth = 1.0 + width = 1.0 + # ... other parameters +``` + +### Modifying Parameters + +Edit the corresponding `yolox_*.py` file and update the `BaseExp` class attributes. + +**Example:** To change YOLOX-S max epochs: +```python +# In data/yolox_s.py +class BaseExp: + max_epoch = 500 # Changed from 300 + # ... other parameters +``` + +## Parameter Priority + +The merge logic follows this priority (highest to lowest): + +1. **User form values** (if explicitly set, not None) +2. **Base config values** (if transfer_learning='coco') +3. **Default fallbacks** (hardcoded minimums) + +## Example + +### COCO Transfer Learning +``` +User sets in form: max_epoch=100, depth=0.5 +Base config (yolox_s.py) has: depth=0.33, width=0.50, max_epoch=300 + +Result: depth=0.5 (user override), width=0.50 (base), max_epoch=100 (user override) +``` + +### Sketch Training +``` +User sets in form: max_epoch=100, depth=0.5 +No base config loaded + +Result: depth=0.5 (user), max_epoch=100 (user), width=1.0 (default fallback) +``` + +## Debugging + +To see which base config was loaded, check Flask logs: +``` +Loaded base config for yolox-s: ['depth', 'width', 'activation', ...] +``` + +If base config fails to load: +``` +Warning: Could not load base config for yolox-s: [error message] +Falling back to custom settings only +``` diff --git a/backend/data/__init__.py b/backend/data/__init__.py index f8167a6..83db142 100644 --- a/backend/data/__init__.py +++ b/backend/data/__init__.py @@ -1 +1 @@ -# Base experiment configurations for YOLOX models +# Base experiment configurations for YOLOX models diff --git a/backend/data/test_base_configs.py b/backend/data/test_base_configs.py index 624313c..9ce9bf5 100644 --- a/backend/data/test_base_configs.py +++ b/backend/data/test_base_configs.py @@ -1,79 +1,79 @@ -#!/usr/bin/env python3 -""" -Test script to demonstrate base configuration loading for YOLOX models -""" - -import sys -import os -sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) - -from services.generate_yolox_exp import load_base_config - -def test_base_configs(): - """Test loading all base configurations""" - models = ['yolox-s', 'yolox-m', 'yolox-l', 'yolox-x'] - - print("=" * 80) - print("YOLOX Base Configuration Test") - print("=" * 80) - - for model in models: - print(f"\n{'='*80}") - print(f"Model: {model.upper()}") - print(f"{'='*80}") - - try: - config = load_base_config(model) - - # Group parameters by category - arch_params = ['depth', 'width', 'activation'] - training_params = ['max_epoch', 'warmup_epochs', 'basic_lr_per_img', 'scheduler', - 'no_aug_epochs', 'min_lr_ratio'] - optimizer_params = ['momentum', 'weight_decay'] - augmentation_params = ['mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob', - 'degrees', 'translate', 'shear', 'mosaic_scale', - 'mixup_scale', 'enable_mixup'] - input_params = ['input_size', 'test_size', 'random_size'] - eval_params = ['eval_interval', 'print_interval'] - - print("\n[Architecture]") - for param in arch_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print("\n[Training Hyperparameters]") - for param in training_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print("\n[Optimizer]") - for param in optimizer_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print("\n[Data Augmentation]") - for param in augmentation_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print("\n[Input/Output]") - for param in input_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print("\n[Evaluation]") - for param in eval_params: - if param in config: - print(f" {param:25s} = {config[param]}") - - print(f"\nβœ“ Successfully loaded {len(config)} parameters") - - except Exception as e: - print(f"βœ— Error loading config: {e}") - - print("\n" + "="*80) - print("Test Complete") - print("="*80) - -if __name__ == '__main__': - test_base_configs() +#!/usr/bin/env python3 +""" +Test script to demonstrate base configuration loading for YOLOX models +""" + +import sys +import os +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) + +from services.generate_yolox_exp import load_base_config + +def test_base_configs(): + """Test loading all base configurations""" + models = ['yolox-s', 'yolox-m', 'yolox-l', 'yolox-x'] + + print("=" * 80) + print("YOLOX Base Configuration Test") + print("=" * 80) + + for model in models: + print(f"\n{'='*80}") + print(f"Model: {model.upper()}") + print(f"{'='*80}") + + try: + config = load_base_config(model) + + # Group parameters by category + arch_params = ['depth', 'width', 'activation'] + training_params = ['max_epoch', 'warmup_epochs', 'basic_lr_per_img', 'scheduler', + 'no_aug_epochs', 'min_lr_ratio'] + optimizer_params = ['momentum', 'weight_decay'] + augmentation_params = ['mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob', + 'degrees', 'translate', 'shear', 'mosaic_scale', + 'mixup_scale', 'enable_mixup'] + input_params = ['input_size', 'test_size', 'random_size'] + eval_params = ['eval_interval', 'print_interval'] + + print("\n[Architecture]") + for param in arch_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print("\n[Training Hyperparameters]") + for param in training_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print("\n[Optimizer]") + for param in optimizer_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print("\n[Data Augmentation]") + for param in augmentation_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print("\n[Input/Output]") + for param in input_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print("\n[Evaluation]") + for param in eval_params: + if param in config: + print(f" {param:25s} = {config[param]}") + + print(f"\nβœ“ Successfully loaded {len(config)} parameters") + + except Exception as e: + print(f"βœ— Error loading config: {e}") + + print("\n" + "="*80) + print("Test Complete") + print("="*80) + +if __name__ == '__main__': + test_base_configs() diff --git a/backend/data/yolox_l.py b/backend/data/yolox_l.py index 16f53ea..0b6e99b 100644 --- a/backend/data/yolox_l.py +++ b/backend/data/yolox_l.py @@ -1,15 +1,15 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Base configuration for YOLOX-L model -# These parameters are preserved during transfer learning from COCO - -class BaseExp: - """Base experiment configuration for YOLOX-L""" - - # Model architecture (protected - always use these for yolox-l) - depth = 1.0 - width = 1.0 - - scheduler = "yoloxwarmcos" - - activation = "silu" +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Base configuration for YOLOX-L model +# These parameters are preserved during transfer learning from COCO + +class BaseExp: + """Base experiment configuration for YOLOX-L""" + + # Model architecture (protected - always use these for yolox-l) + depth = 1.0 + width = 1.0 + + scheduler = "yoloxwarmcos" + + activation = "silu" diff --git a/backend/data/yolox_m.py b/backend/data/yolox_m.py index 27f15a3..b39fe13 100644 --- a/backend/data/yolox_m.py +++ b/backend/data/yolox_m.py @@ -1,15 +1,15 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Base configuration for YOLOX-M model -# These parameters are preserved during transfer learning from COCO - -class BaseExp: - """Base experiment configuration for YOLOX-M""" - - # Model architecture (protected - always use these for yolox-m) - depth = 0.67 - width = 0.75 - - scheduler = "yoloxwarmcos" - +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Base configuration for YOLOX-M model +# These parameters are preserved during transfer learning from COCO + +class BaseExp: + """Base experiment configuration for YOLOX-M""" + + # Model architecture (protected - always use these for yolox-m) + depth = 0.67 + width = 0.75 + + scheduler = "yoloxwarmcos" + activation = "silu" \ No newline at end of file diff --git a/backend/data/yolox_s.py b/backend/data/yolox_s.py index d6ba3b9..642ee55 100644 --- a/backend/data/yolox_s.py +++ b/backend/data/yolox_s.py @@ -1,17 +1,17 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Base configuration for YOLOX-S model -# These parameters are preserved during transfer learning from COCO - -class BaseExp: - """Base experiment configuration for YOLOX-S""" - - # Model architecture (protected - always use these for yolox-s) - depth = 0.33 - width = 0.50 - - scheduler = "yoloxwarmcos" - - activation = "silu" - - +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Base configuration for YOLOX-S model +# These parameters are preserved during transfer learning from COCO + +class BaseExp: + """Base experiment configuration for YOLOX-S""" + + # Model architecture (protected - always use these for yolox-s) + depth = 0.33 + width = 0.50 + + scheduler = "yoloxwarmcos" + + activation = "silu" + + diff --git a/backend/data/yolox_x.py b/backend/data/yolox_x.py index 55dafa1..f9f8d7d 100644 --- a/backend/data/yolox_x.py +++ b/backend/data/yolox_x.py @@ -1,15 +1,15 @@ -#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Base configuration for YOLOX-X model -# These parameters are preserved during transfer learning from COCO - -class BaseExp: - """Base experiment configuration for YOLOX-X""" - - # Model architecture (protected - always use these for yolox-x) - depth = 1.33 - width = 1.25 - - scheduler = "yoloxwarmcos" - +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Base configuration for YOLOX-X model +# These parameters are preserved during transfer learning from COCO + +class BaseExp: + """Base experiment configuration for YOLOX-X""" + + # Model architecture (protected - always use these for yolox-x) + depth = 1.33 + width = 1.25 + + scheduler = "yoloxwarmcos" + activation = "silu" \ No newline at end of file diff --git a/backend/database/__init__.py b/backend/database/__init__.py index 5a2305d..d46a06b 100644 --- a/backend/database/__init__.py +++ b/backend/database/__init__.py @@ -1,4 +1,4 @@ -# Database module -from database.database import db - -__all__ = ['db'] +# Database module +from database.database import db + +__all__ = ['db'] diff --git a/backend/database/database.js b/backend/database/database.js index d47cf4d..12b0555 100644 --- a/backend/database/database.js +++ b/backend/database/database.js @@ -1,10 +1,10 @@ -// database.js -const { Sequelize } = require('sequelize'); - -const sequelize = new Sequelize('myapp', 'root', 'root', { - host: 'localhost', - dialect: 'mysql', - logging: false, -}); - -module.exports = sequelize; +// database.js +const { Sequelize } = require('sequelize'); + +const sequelize = new Sequelize('myapp', 'root', 'root', { + host: 'localhost', + dialect: 'mysql', + logging: false, +}); + +module.exports = sequelize; diff --git a/backend/database/database.py b/backend/database/database.py index 5debe6e..c601440 100644 --- a/backend/database/database.py +++ b/backend/database/database.py @@ -1,9 +1,9 @@ -from flask_sqlalchemy import SQLAlchemy - -db = SQLAlchemy() - -def init_db(app): - """Initialize database with app context""" - db.init_app(app) - with app.app_context(): - db.create_all() +from flask_sqlalchemy import SQLAlchemy + +db = SQLAlchemy() + +def init_db(app): + """Initialize database with app context""" + db.init_app(app) + with app.app_context(): + db.create_all() diff --git a/backend/database/migration_add_image_dimensions.sql b/backend/database/migration_add_image_dimensions.sql deleted file mode 100644 index 02adc8a..0000000 --- a/backend/database/migration_add_image_dimensions.sql +++ /dev/null @@ -1,12 +0,0 @@ --- Migration: Add width and height columns to image table --- Date: 2025-11-27 - -USE myapp; - --- Add width and height columns to image table -ALTER TABLE `image` -ADD COLUMN `width` FLOAT NULL AFTER `image_path`, -ADD COLUMN `height` FLOAT NULL AFTER `width`; - --- Verify the changes -DESCRIBE `image`; diff --git a/backend/models/Annotation.js b/backend/models/Annotation.js index fe092cd..e41e008 100644 --- a/backend/models/Annotation.js +++ b/backend/models/Annotation.js @@ -1,40 +1,40 @@ -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - - -const Annotation = sequelize.define('Annotation', { - annotation_id: { - type: DataTypes.INTEGER, - primaryKey: true, - autoIncrement: true, - }, - image_id: { - type: DataTypes.INTEGER, - allowNull: false, - }, - x: { - type: DataTypes.FLOAT, - allowNull: false, - }, - y: { - type: DataTypes.FLOAT, - allowNull: false, - }, - height: { - type: DataTypes.FLOAT, - allowNull: false, - }, - width: { - type: DataTypes.FLOAT, - allowNull: false, - }, - Label: { - type: DataTypes.STRING, - allowNull: false, - }, -}, { - tableName: 'annotation', - timestamps: false, -}); - -module.exports = Annotation; +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + + +const Annotation = sequelize.define('Annotation', { + annotation_id: { + type: DataTypes.INTEGER, + primaryKey: true, + autoIncrement: true, + }, + image_id: { + type: DataTypes.INTEGER, + allowNull: false, + }, + x: { + type: DataTypes.FLOAT, + allowNull: false, + }, + y: { + type: DataTypes.FLOAT, + allowNull: false, + }, + height: { + type: DataTypes.FLOAT, + allowNull: false, + }, + width: { + type: DataTypes.FLOAT, + allowNull: false, + }, + Label: { + type: DataTypes.STRING, + allowNull: false, + }, +}, { + tableName: 'annotation', + timestamps: false, +}); + +module.exports = Annotation; diff --git a/backend/models/Annotation.py b/backend/models/Annotation.py index 9b30150..2c80105 100644 --- a/backend/models/Annotation.py +++ b/backend/models/Annotation.py @@ -1,23 +1,23 @@ -from database.database import db - -class Annotation(db.Model): - __tablename__ = 'annotation' - - annotation_id = db.Column(db.Integer, primary_key=True, autoincrement=True) - image_id = db.Column(db.Integer, nullable=False) - x = db.Column(db.Float, nullable=False) - y = db.Column(db.Float, nullable=False) - height = db.Column(db.Float, nullable=False) - width = db.Column(db.Float, nullable=False) - Label = db.Column(db.String(255), nullable=False) - - def to_dict(self): - return { - 'annotation_id': self.annotation_id, - 'image_id': self.image_id, - 'x': self.x, - 'y': self.y, - 'height': self.height, - 'width': self.width, - 'Label': self.Label - } +from database.database import db + +class Annotation(db.Model): + __tablename__ = 'annotation' + + annotation_id = db.Column(db.Integer, primary_key=True, autoincrement=True) + image_id = db.Column(db.Integer, db.ForeignKey('image.image_id', ondelete='CASCADE'), nullable=False) + x = db.Column(db.Float, nullable=False) + y = db.Column(db.Float, nullable=False) + height = db.Column(db.Float, nullable=False) + width = db.Column(db.Float, nullable=False) + Label = db.Column(db.String(255), nullable=False) + + def to_dict(self): + return { + 'annotation_id': self.annotation_id, + 'image_id': self.image_id, + 'x': self.x, + 'y': self.y, + 'height': self.height, + 'width': self.width, + 'Label': self.Label + } diff --git a/backend/models/AnnotationProjectMapping.py b/backend/models/AnnotationProjectMapping.py new file mode 100644 index 0000000..70b287f --- /dev/null +++ b/backend/models/AnnotationProjectMapping.py @@ -0,0 +1,21 @@ +from database.database import db + +class AnnotationProjectMapping(db.Model): + """Mapping between training project details and label studio projects (3NF)""" + __tablename__ = 'annotation_project_mapping' + + id = db.Column(db.Integer, primary_key=True, autoincrement=True) + project_details_id = db.Column(db.Integer, db.ForeignKey('training_project_details.id', ondelete='CASCADE'), nullable=False) + label_studio_project_id = db.Column(db.Integer, db.ForeignKey('label_studio_project.project_id', ondelete='CASCADE'), nullable=False) + + # Unique constraint: each label studio project can only be mapped once per training project details + __table_args__ = ( + db.UniqueConstraint('project_details_id', 'label_studio_project_id', name='uq_annotation_mapping'), + ) + + def to_dict(self): + return { + 'id': self.id, + 'project_details_id': self.project_details_id, + 'label_studio_project_id': self.label_studio_project_id + } diff --git a/backend/models/ClassMapping.py b/backend/models/ClassMapping.py new file mode 100644 index 0000000..d6c96c4 --- /dev/null +++ b/backend/models/ClassMapping.py @@ -0,0 +1,25 @@ +from database.database import db + +class ClassMapping(db.Model): + """Class name mappings for training project details (3NF)""" + __tablename__ = 'class_mapping' + + id = db.Column(db.Integer, primary_key=True, autoincrement=True) + project_details_id = db.Column(db.Integer, db.ForeignKey('training_project_details.id', ondelete='CASCADE'), nullable=False) + label_studio_project_id = db.Column(db.Integer, db.ForeignKey('label_studio_project.project_id', ondelete='CASCADE'), nullable=False) + source_class = db.Column(db.String(255), nullable=False) + target_class = db.Column(db.String(255), nullable=False) + + # Unique constraint: each source class can only be mapped once per project details AND label studio project + __table_args__ = ( + db.UniqueConstraint('project_details_id', 'label_studio_project_id', 'source_class', name='uq_class_mapping'), + ) + + def to_dict(self): + return { + 'id': self.id, + 'project_details_id': self.project_details_id, + 'label_studio_project_id': self.label_studio_project_id, + 'source_class': self.source_class, + 'target_class': self.target_class + } diff --git a/backend/models/Images.js b/backend/models/Images.js index fc6d382..41a240b 100644 --- a/backend/models/Images.js +++ b/backend/models/Images.js @@ -1,35 +1,35 @@ - -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - -const Image = sequelize.define('Image', { - image_id: { - type: DataTypes.INTEGER, - primaryKey: true, - autoIncrement: true, - }, - image_path: { - type: DataTypes.STRING, - allowNull: false, - }, - project_id: { - type: DataTypes.INTEGER, - allowNull: false, - }, - width: { - type: DataTypes.FLOAT, - allowNull: true, - }, - height: { - type: DataTypes.FLOAT, - allowNull: true, - }, - -}, { - tableName: 'image', - timestamps: false, -}); - -module.exports = Image; - - + +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + +const Image = sequelize.define('Image', { + image_id: { + type: DataTypes.INTEGER, + primaryKey: true, + autoIncrement: true, + }, + image_path: { + type: DataTypes.STRING, + allowNull: false, + }, + project_id: { + type: DataTypes.INTEGER, + allowNull: false, + }, + width: { + type: DataTypes.FLOAT, + allowNull: true, + }, + height: { + type: DataTypes.FLOAT, + allowNull: true, + }, + +}, { + tableName: 'image', + timestamps: false, +}); + +module.exports = Image; + + diff --git a/backend/models/Images.py b/backend/models/Images.py index 3c5848a..ee67ece 100644 --- a/backend/models/Images.py +++ b/backend/models/Images.py @@ -1,19 +1,19 @@ -from database.database import db - -class Image(db.Model): - __tablename__ = 'image' - - image_id = db.Column(db.Integer, primary_key=True, autoincrement=True) - image_path = db.Column(db.String(500), nullable=False) - project_id = db.Column(db.Integer, nullable=False) - width = db.Column(db.Float) - height = db.Column(db.Float) - - def to_dict(self): - return { - 'image_id': self.image_id, - 'image_path': self.image_path, - 'project_id': self.project_id, - 'width': self.width, - 'height': self.height - } +from database.database import db + +class Image(db.Model): + __tablename__ = 'image' + + image_id = db.Column(db.Integer, primary_key=True, autoincrement=True) + image_path = db.Column(db.String(500), nullable=False) + project_id = db.Column(db.Integer, db.ForeignKey('label_studio_project.project_id', ondelete='CASCADE'), nullable=False) + width = db.Column(db.Integer) + height = db.Column(db.Integer) + + def to_dict(self): + return { + 'image_id': self.image_id, + 'image_path': self.image_path, + 'project_id': self.project_id, + 'width': self.width, + 'height': self.height + } diff --git a/backend/models/LabelStudioProject.js b/backend/models/LabelStudioProject.js index 2763883..b86ff81 100644 --- a/backend/models/LabelStudioProject.js +++ b/backend/models/LabelStudioProject.js @@ -1,24 +1,24 @@ - -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - -const Label_studio_project = sequelize.define('LabelStudioProject', { - project_id: { - type: DataTypes.INTEGER, - primaryKey: true, - unique: true, - allowNull: false, - }, - title:{ - type: DataTypes.STRING, - allowNull: false, - } - -}, { - tableName: 'label_studio_project', - timestamps: false, -}); - -module.exports = Label_studio_project; - - + +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + +const Label_studio_project = sequelize.define('LabelStudioProject', { + project_id: { + type: DataTypes.INTEGER, + primaryKey: true, + unique: true, + allowNull: false, + }, + title:{ + type: DataTypes.STRING, + allowNull: false, + } + +}, { + tableName: 'label_studio_project', + timestamps: false, +}); + +module.exports = Label_studio_project; + + diff --git a/backend/models/LabelStudioProject.py b/backend/models/LabelStudioProject.py index a0c5953..6bdf1a3 100644 --- a/backend/models/LabelStudioProject.py +++ b/backend/models/LabelStudioProject.py @@ -1,13 +1,13 @@ -from database.database import db - -class LabelStudioProject(db.Model): - __tablename__ = 'label_studio_project' - - project_id = db.Column(db.Integer, primary_key=True, unique=True) - title = db.Column(db.String(255), nullable=False) - - def to_dict(self): - return { - 'project_id': self.project_id, - 'title': self.title - } +from database.database import db + +class LabelStudioProject(db.Model): + __tablename__ = 'label_studio_project' + + project_id = db.Column(db.Integer, primary_key=True, unique=True) + title = db.Column(db.String(255), nullable=False) + + def to_dict(self): + return { + 'project_id': self.project_id, + 'title': self.title + } diff --git a/backend/models/ProjectClass.py b/backend/models/ProjectClass.py new file mode 100644 index 0000000..7919f72 --- /dev/null +++ b/backend/models/ProjectClass.py @@ -0,0 +1,23 @@ +from database.database import db + +class ProjectClass(db.Model): + """Class definitions for training projects (3NF)""" + __tablename__ = 'project_class' + + id = db.Column(db.Integer, primary_key=True, autoincrement=True) + project_id = db.Column(db.Integer, db.ForeignKey('training_project.project_id', ondelete='CASCADE'), nullable=False) + class_name = db.Column(db.String(255), nullable=False) + display_order = db.Column(db.Integer, default=0) + + # Unique constraint: one class name per project + __table_args__ = ( + db.UniqueConstraint('project_id', 'class_name', name='uq_project_class'), + ) + + def to_dict(self): + return { + 'id': self.id, + 'project_id': self.project_id, + 'class_name': self.class_name, + 'display_order': self.display_order + } diff --git a/backend/models/Settings.py b/backend/models/Settings.py new file mode 100644 index 0000000..7c2c6ba --- /dev/null +++ b/backend/models/Settings.py @@ -0,0 +1,21 @@ +from database.database import db + +class Settings(db.Model): + __tablename__ = 'settings' + + id = db.Column(db.Integer, primary_key=True) + key = db.Column(db.String(255), unique=True, nullable=False) + value = db.Column(db.Text, nullable=True) + description = db.Column(db.String(500), nullable=True) + created_at = db.Column(db.DateTime, server_default=db.func.now()) + updated_at = db.Column(db.DateTime, server_default=db.func.now(), onupdate=db.func.now()) + + def to_dict(self): + return { + 'id': self.id, + 'key': self.key, + 'value': self.value, + 'description': self.description, + 'created_at': self.created_at.isoformat() if self.created_at else None, + 'updated_at': self.updated_at.isoformat() if self.updated_at else None + } diff --git a/backend/models/TrainingProject.js b/backend/models/TrainingProject.js index 3a8420c..2161929 100644 --- a/backend/models/TrainingProject.js +++ b/backend/models/TrainingProject.js @@ -1,38 +1,38 @@ -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - -const Training_Project = sequelize.define('LabelStudioProject', { - project_id: { - type: DataTypes.INTEGER, - primaryKey: true, - unique: true, - allowNull: false, - autoIncrement: true, - }, - title:{ - type: DataTypes.STRING, - allowNull: false, - }, - description: { - type: DataTypes.STRING, - }, - classes: { - type: DataTypes.JSON, - allowNull: false, - }, - project_image: { - type: DataTypes.BLOB, - }, - project_image_type: { - type: DataTypes.STRING, - allowNull: true, - } - -}, { - tableName: 'training_project', - timestamps: false, -}); - -module.exports = Training_Project; - - +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + +const Training_Project = sequelize.define('LabelStudioProject', { + project_id: { + type: DataTypes.INTEGER, + primaryKey: true, + unique: true, + allowNull: false, + autoIncrement: true, + }, + title:{ + type: DataTypes.STRING, + allowNull: false, + }, + description: { + type: DataTypes.STRING, + }, + classes: { + type: DataTypes.JSON, + allowNull: false, + }, + project_image: { + type: DataTypes.BLOB, + }, + project_image_type: { + type: DataTypes.STRING, + allowNull: true, + } + +}, { + tableName: 'training_project', + timestamps: false, +}); + +module.exports = Training_Project; + + diff --git a/backend/models/TrainingProject.py b/backend/models/TrainingProject.py index 96b89d8..6d52b84 100644 --- a/backend/models/TrainingProject.py +++ b/backend/models/TrainingProject.py @@ -1,28 +1,36 @@ -from database.database import db - -class TrainingProject(db.Model): - __tablename__ = 'training_project' - - project_id = db.Column(db.Integer, primary_key=True, unique=True, autoincrement=True) - title = db.Column(db.String(255), nullable=False) - description = db.Column(db.String(500)) - classes = db.Column(db.JSON, nullable=False) - project_image = db.Column(db.LargeBinary) - project_image_type = db.Column(db.String(100)) - - def to_dict(self): - result = { - 'project_id': self.project_id, - 'title': self.title, - 'description': self.description, - 'classes': self.classes, - 'project_image_type': self.project_image_type - } - if self.project_image: - import base64 - base64_data = base64.b64encode(self.project_image).decode('utf-8') - mime_type = self.project_image_type or 'image/png' - result['project_image'] = f'data:{mime_type};base64,{base64_data}' - else: - result['project_image'] = None - return result +from database.database import db + +class TrainingProject(db.Model): + __tablename__ = 'training_project' + + project_id = db.Column(db.Integer, primary_key=True, unique=True, autoincrement=True) + title = db.Column(db.String(255), nullable=False) + description = db.Column(db.String(500)) + project_image = db.Column(db.LargeBinary) + project_image_type = db.Column(db.String(100)) + + # Relationship to classes (3NF) + classes_relation = db.relationship('ProjectClass', backref='project', lazy=True, cascade='all, delete-orphan') + + def to_dict(self, include_classes=True): + result = { + 'project_id': self.project_id, + 'title': self.title, + 'description': self.description, + 'project_image_type': self.project_image_type + } + + # Include classes as array for backwards compatibility + if include_classes: + from models.ProjectClass import ProjectClass + classes = ProjectClass.query.filter_by(project_id=self.project_id).order_by(ProjectClass.display_order).all() + result['classes'] = [c.class_name for c in classes] + + if self.project_image: + import base64 + base64_data = base64.b64encode(self.project_image).decode('utf-8') + mime_type = self.project_image_type or 'image/png' + result['project_image'] = f'data:{mime_type};base64,{base64_data}' + else: + result['project_image'] = None + return result diff --git a/backend/models/TrainingProjectDetails.js b/backend/models/TrainingProjectDetails.js index 779b076..872cf11 100644 --- a/backend/models/TrainingProjectDetails.js +++ b/backend/models/TrainingProjectDetails.js @@ -1,33 +1,33 @@ -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - -const TrainingProjectDetails = sequelize.define('TrainingProjectDetails', { - id: { - type: DataTypes.INTEGER, - primaryKey: true, - autoIncrement: true, - unique: true, - }, - project_id: { - type: DataTypes.INTEGER, - allowNull: false, - unique: true, - }, - annotation_projects: { - type: DataTypes.JSON, - allowNull: false, - }, - class_map: { - type: DataTypes.JSON, - allowNull: true, - }, - description: { - type: DataTypes.JSON, - allowNull: true, - } -}, { - tableName: 'training_project_details', - timestamps: false, -}); - -module.exports = TrainingProjectDetails; +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + +const TrainingProjectDetails = sequelize.define('TrainingProjectDetails', { + id: { + type: DataTypes.INTEGER, + primaryKey: true, + autoIncrement: true, + unique: true, + }, + project_id: { + type: DataTypes.INTEGER, + allowNull: false, + unique: true, + }, + annotation_projects: { + type: DataTypes.JSON, + allowNull: false, + }, + class_map: { + type: DataTypes.JSON, + allowNull: true, + }, + description: { + type: DataTypes.JSON, + allowNull: true, + } +}, { + tableName: 'training_project_details', + timestamps: false, +}); + +module.exports = TrainingProjectDetails; diff --git a/backend/models/TrainingProjectDetails.py b/backend/models/TrainingProjectDetails.py index 9f1ccbf..47eaa8f 100644 --- a/backend/models/TrainingProjectDetails.py +++ b/backend/models/TrainingProjectDetails.py @@ -1,19 +1,35 @@ -from database.database import db - -class TrainingProjectDetails(db.Model): - __tablename__ = 'training_project_details' - - id = db.Column(db.Integer, primary_key=True, unique=True, autoincrement=True) - project_id = db.Column(db.Integer, nullable=False, unique=True) - annotation_projects = db.Column(db.JSON, nullable=False) - class_map = db.Column(db.JSON) - description = db.Column(db.JSON) - - def to_dict(self): - return { - 'id': self.id, - 'project_id': self.project_id, - 'annotation_projects': self.annotation_projects, - 'class_map': self.class_map, - 'description': self.description - } +from database.database import db + +class TrainingProjectDetails(db.Model): + __tablename__ = 'training_project_details' + + id = db.Column(db.Integer, primary_key=True, unique=True, autoincrement=True) + project_id = db.Column(db.Integer, db.ForeignKey('training_project.project_id', ondelete='CASCADE'), nullable=False, unique=True) + description_text = db.Column(db.Text) # Renamed from 'description' JSON to plain text + + # Relationships (3NF) + annotation_mappings = db.relationship('AnnotationProjectMapping', backref='project_details', lazy=True, cascade='all, delete-orphan') + class_mappings = db.relationship('ClassMapping', backref='project_details', lazy=True, cascade='all, delete-orphan') + + def to_dict(self, include_mappings=True): + result = { + 'id': self.id, + 'project_id': self.project_id, + 'description': self.description_text + } + + # Include mappings for backwards compatibility + if include_mappings: + from models.AnnotationProjectMapping import AnnotationProjectMapping + from models.ClassMapping import ClassMapping + + # Get annotation projects as array + mappings = AnnotationProjectMapping.query.filter_by(project_details_id=self.id).all() + result['annotation_projects'] = [m.label_studio_project_id for m in mappings] + + # Get class map as dictionary (grouped by label_studio_project_id for backwards compatibility) + # Return format: {source: target} (flattened across all projects) + class_maps = ClassMapping.query.filter_by(project_details_id=self.id).all() + result['class_map'] = {cm.source_class: cm.target_class for cm in class_maps} + + return result diff --git a/backend/models/TrainingSize.py b/backend/models/TrainingSize.py new file mode 100644 index 0000000..9201127 --- /dev/null +++ b/backend/models/TrainingSize.py @@ -0,0 +1,25 @@ +from database.database import db + +class TrainingSize(db.Model): + """Size configurations for training (3NF - replaces JSON arrays)""" + __tablename__ = 'training_size' + + id = db.Column(db.Integer, primary_key=True, autoincrement=True) + training_id = db.Column(db.Integer, db.ForeignKey('training.id', ondelete='CASCADE'), nullable=False) + size_type = db.Column(db.String(50), nullable=False) # 'input_size', 'test_size', 'mosaic_scale', 'mixup_scale' + value_order = db.Column(db.Integer, nullable=False, default=0) # Order in array (0=first, 1=second) + value = db.Column(db.Float, nullable=False) + + # Composite key ensures proper ordering + __table_args__ = ( + db.UniqueConstraint('training_id', 'size_type', 'value_order', name='uq_training_size'), + ) + + def to_dict(self): + return { + 'id': self.id, + 'training_id': self.training_id, + 'size_type': self.size_type, + 'value_order': self.value_order, + 'value': self.value + } diff --git a/backend/models/__init__.py b/backend/models/__init__.py index ccf4d18..caf5d59 100644 --- a/backend/models/__init__.py +++ b/backend/models/__init__.py @@ -1,16 +1,26 @@ -# Import all models to ensure they are registered with SQLAlchemy -from models.TrainingProject import TrainingProject -from models.TrainingProjectDetails import TrainingProjectDetails -from models.training import Training -from models.LabelStudioProject import LabelStudioProject -from models.Images import Image -from models.Annotation import Annotation - -__all__ = [ - 'TrainingProject', - 'TrainingProjectDetails', - 'Training', - 'LabelStudioProject', - 'Image', - 'Annotation' -] +# Import all models to ensure they are registered with SQLAlchemy +from models.TrainingProject import TrainingProject +from models.TrainingProjectDetails import TrainingProjectDetails +from models.training import Training +from models.LabelStudioProject import LabelStudioProject +from models.Images import Image +from models.Annotation import Annotation +from models.Settings import Settings +from models.ProjectClass import ProjectClass +from models.AnnotationProjectMapping import AnnotationProjectMapping +from models.ClassMapping import ClassMapping +from models.TrainingSize import TrainingSize + +__all__ = [ + 'TrainingProject', + 'TrainingProjectDetails', + 'Training', + 'LabelStudioProject', + 'Image', + 'Annotation', + 'Settings', + 'ProjectClass', + 'AnnotationProjectMapping', + 'ClassMapping', + 'TrainingSize' +] diff --git a/backend/models/index.js b/backend/models/index.js index 78d2e54..8273bec 100644 --- a/backend/models/index.js +++ b/backend/models/index.js @@ -1,30 +1,30 @@ -const LabelStudioProject = require('./LabelStudioProject.js'); -const Annotation = require('./Annotation.js'); -const Image = require('./Images.js'); -const sequelize = require('../database/database.js'); -const TrainingProjectDetails = require('./TrainingProjectDetails.js'); -const TrainingProject = require('./TrainingProject.js'); -const Training = require('./training.js'); - - - -const Project = LabelStudioProject; -const Img = Image; -const Ann = Annotation; - -// Associations -Project.hasMany(Img, { foreignKey: 'project_id' }); -Img.belongsTo(Project, { foreignKey: 'project_id' }); - -Img.hasMany(Ann, { foreignKey: 'image_id' }); -Ann.belongsTo(Img, { foreignKey: 'image_id' }); - -// TrainingProjectDetails <-> TrainingProject -TrainingProjectDetails.belongsTo(TrainingProject, { foreignKey: 'project_id' }); -TrainingProject.hasOne(TrainingProjectDetails, { foreignKey: 'project_id' }); - -// Training <-> TrainingProjectDetails -Training.belongsTo(TrainingProjectDetails, { foreignKey: 'project_details_id' }); -TrainingProjectDetails.hasMany(Training, { foreignKey: 'project_details_id' }); - -module.exports = { Project, Img, Ann, TrainingProjectDetails, TrainingProject, Training }; +const LabelStudioProject = require('./LabelStudioProject.js'); +const Annotation = require('./Annotation.js'); +const Image = require('./Images.js'); +const sequelize = require('../database/database.js'); +const TrainingProjectDetails = require('./TrainingProjectDetails.js'); +const TrainingProject = require('./TrainingProject.js'); +const Training = require('./training.js'); + + + +const Project = LabelStudioProject; +const Img = Image; +const Ann = Annotation; + +// Associations +Project.hasMany(Img, { foreignKey: 'project_id' }); +Img.belongsTo(Project, { foreignKey: 'project_id' }); + +Img.hasMany(Ann, { foreignKey: 'image_id' }); +Ann.belongsTo(Img, { foreignKey: 'image_id' }); + +// TrainingProjectDetails <-> TrainingProject +TrainingProjectDetails.belongsTo(TrainingProject, { foreignKey: 'project_id' }); +TrainingProject.hasOne(TrainingProjectDetails, { foreignKey: 'project_id' }); + +// Training <-> TrainingProjectDetails +Training.belongsTo(TrainingProjectDetails, { foreignKey: 'project_details_id' }); +TrainingProjectDetails.hasMany(Training, { foreignKey: 'project_details_id' }); + +module.exports = { Project, Img, Ann, TrainingProjectDetails, TrainingProject, Training }; diff --git a/backend/models/training.js b/backend/models/training.js index 9e3679f..7315917 100644 --- a/backend/models/training.js +++ b/backend/models/training.js @@ -1,140 +1,140 @@ -const { DataTypes } = require('sequelize'); -const sequelize = require('../database/database.js'); - -const Training = sequelize.define('training', { - id: { - type: DataTypes.INTEGER, - autoIncrement: true, - unique: true, - primaryKey: true - }, - exp_name: { - type: DataTypes.STRING(255) - }, - max_epoch: { - type: DataTypes.INTEGER - }, - depth: { - type: DataTypes.FLOAT - }, - width: { - type: DataTypes.FLOAT - }, - activation: { - type: DataTypes.STRING(255) - }, - warmup_epochs: { - type: DataTypes.INTEGER - }, - warmup_lr: { - type: DataTypes.FLOAT - }, - basic_lr_per_img: { - type: DataTypes.FLOAT - }, - scheduler: { - type: DataTypes.STRING(255) - }, - no_aug_epochs: { - type: DataTypes.INTEGER - }, - min_lr_ratio: { - type: DataTypes.FLOAT - }, - ema: { - type: DataTypes.BOOLEAN - }, - weight_decay: { - type: DataTypes.FLOAT - }, - momentum: { - type: DataTypes.FLOAT - }, - input_size: { - type: DataTypes.JSON - }, - print_interval: { - type: DataTypes.INTEGER - }, - eval_interval: { - type: DataTypes.INTEGER - }, - save_history_ckpt: { - type: DataTypes.BOOLEAN - }, - test_size: { - type: DataTypes.JSON - }, - test_conf: { - type: DataTypes.FLOAT - }, - nms_thre: { - type: DataTypes.FLOAT - }, - multiscale_range: { - type: DataTypes.INTEGER - }, - enable_mixup: { - type: DataTypes.BOOLEAN - }, - mosaic_prob: { - type: DataTypes.FLOAT - }, - mixup_prob: { - type: DataTypes.FLOAT - }, - hsv_prob: { - type: DataTypes.FLOAT - }, - flip_prob: { - type: DataTypes.FLOAT - }, - degrees: { - type: DataTypes.FLOAT - }, - mosaic_scale: { - type: DataTypes.JSON - }, - mixup_scale: { - type: DataTypes.JSON - }, - translate: { - type: DataTypes.FLOAT - }, - shear: { - type: DataTypes.FLOAT - }, - training_name: { - type: DataTypes.STRING(255) - }, - project_details_id: { - type: DataTypes.INTEGER, - allowNull: false - }, - seed: { - type: DataTypes.INTEGER - }, - train: { - type: DataTypes.INTEGER - }, - valid: { - type: DataTypes.INTEGER - }, - test: { - type: DataTypes.INTEGER - }, - selected_model: { - type: DataTypes.STRING(255) - }, - transfer_learning: { - type: DataTypes.STRING(255) - }, - model_upload: { - type: DataTypes.BLOB - } -}, { - tableName: 'training', - timestamps: false -}); - -module.exports = Training; +const { DataTypes } = require('sequelize'); +const sequelize = require('../database/database.js'); + +const Training = sequelize.define('training', { + id: { + type: DataTypes.INTEGER, + autoIncrement: true, + unique: true, + primaryKey: true + }, + exp_name: { + type: DataTypes.STRING(255) + }, + max_epoch: { + type: DataTypes.INTEGER + }, + depth: { + type: DataTypes.FLOAT + }, + width: { + type: DataTypes.FLOAT + }, + activation: { + type: DataTypes.STRING(255) + }, + warmup_epochs: { + type: DataTypes.INTEGER + }, + warmup_lr: { + type: DataTypes.FLOAT + }, + basic_lr_per_img: { + type: DataTypes.FLOAT + }, + scheduler: { + type: DataTypes.STRING(255) + }, + no_aug_epochs: { + type: DataTypes.INTEGER + }, + min_lr_ratio: { + type: DataTypes.FLOAT + }, + ema: { + type: DataTypes.BOOLEAN + }, + weight_decay: { + type: DataTypes.FLOAT + }, + momentum: { + type: DataTypes.FLOAT + }, + input_size: { + type: DataTypes.JSON + }, + print_interval: { + type: DataTypes.INTEGER + }, + eval_interval: { + type: DataTypes.INTEGER + }, + save_history_ckpt: { + type: DataTypes.BOOLEAN + }, + test_size: { + type: DataTypes.JSON + }, + test_conf: { + type: DataTypes.FLOAT + }, + nms_thre: { + type: DataTypes.FLOAT + }, + multiscale_range: { + type: DataTypes.INTEGER + }, + enable_mixup: { + type: DataTypes.BOOLEAN + }, + mosaic_prob: { + type: DataTypes.FLOAT + }, + mixup_prob: { + type: DataTypes.FLOAT + }, + hsv_prob: { + type: DataTypes.FLOAT + }, + flip_prob: { + type: DataTypes.FLOAT + }, + degrees: { + type: DataTypes.FLOAT + }, + mosaic_scale: { + type: DataTypes.JSON + }, + mixup_scale: { + type: DataTypes.JSON + }, + translate: { + type: DataTypes.FLOAT + }, + shear: { + type: DataTypes.FLOAT + }, + training_name: { + type: DataTypes.STRING(255) + }, + project_details_id: { + type: DataTypes.INTEGER, + allowNull: false + }, + seed: { + type: DataTypes.INTEGER + }, + train: { + type: DataTypes.INTEGER + }, + valid: { + type: DataTypes.INTEGER + }, + test: { + type: DataTypes.INTEGER + }, + selected_model: { + type: DataTypes.STRING(255) + }, + transfer_learning: { + type: DataTypes.STRING(255) + }, + model_upload: { + type: DataTypes.BLOB + } +}, { + tableName: 'training', + timestamps: false +}); + +module.exports = Training; diff --git a/backend/models/training.py b/backend/models/training.py index 2f66ead..9d9e8c7 100644 --- a/backend/models/training.py +++ b/backend/models/training.py @@ -1,92 +1,109 @@ -from database.database import db - -class Training(db.Model): - __tablename__ = 'training' - - id = db.Column(db.Integer, primary_key=True, autoincrement=True, unique=True) - exp_name = db.Column(db.String(255)) - max_epoch = db.Column(db.Integer) - depth = db.Column(db.Float) - width = db.Column(db.Float) - activation = db.Column(db.String(255)) - warmup_epochs = db.Column(db.Integer) - warmup_lr = db.Column(db.Float) - basic_lr_per_img = db.Column(db.Float) - scheduler = db.Column(db.String(255)) - no_aug_epochs = db.Column(db.Integer) - min_lr_ratio = db.Column(db.Float) - ema = db.Column(db.Boolean) - weight_decay = db.Column(db.Float) - momentum = db.Column(db.Float) - input_size = db.Column(db.JSON) - print_interval = db.Column(db.Integer) - eval_interval = db.Column(db.Integer) - save_history_ckpt = db.Column(db.Boolean) - test_size = db.Column(db.JSON) - test_conf = db.Column(db.Float) - nms_thre = db.Column(db.Float) - multiscale_range = db.Column(db.Integer) - enable_mixup = db.Column(db.Boolean) - mosaic_prob = db.Column(db.Float) - mixup_prob = db.Column(db.Float) - hsv_prob = db.Column(db.Float) - flip_prob = db.Column(db.Float) - degrees = db.Column(db.Float) - mosaic_scale = db.Column(db.JSON) - mixup_scale = db.Column(db.JSON) - translate = db.Column(db.Float) - shear = db.Column(db.Float) - training_name = db.Column(db.String(255)) - project_details_id = db.Column(db.Integer, nullable=False) - seed = db.Column(db.Integer) - train = db.Column(db.Integer) - valid = db.Column(db.Integer) - test = db.Column(db.Integer) - selected_model = db.Column(db.String(255)) - transfer_learning = db.Column(db.String(255)) - model_upload = db.Column(db.LargeBinary) - - def to_dict(self): - return { - 'id': self.id, - 'exp_name': self.exp_name, - 'max_epoch': self.max_epoch, - 'depth': self.depth, - 'width': self.width, - 'activation': self.activation, - 'warmup_epochs': self.warmup_epochs, - 'warmup_lr': self.warmup_lr, - 'basic_lr_per_img': self.basic_lr_per_img, - 'scheduler': self.scheduler, - 'no_aug_epochs': self.no_aug_epochs, - 'min_lr_ratio': self.min_lr_ratio, - 'ema': self.ema, - 'weight_decay': self.weight_decay, - 'momentum': self.momentum, - 'input_size': self.input_size, - 'print_interval': self.print_interval, - 'eval_interval': self.eval_interval, - 'save_history_ckpt': self.save_history_ckpt, - 'test_size': self.test_size, - 'test_conf': self.test_conf, - 'nms_thre': self.nms_thre, - 'multiscale_range': self.multiscale_range, - 'enable_mixup': self.enable_mixup, - 'mosaic_prob': self.mosaic_prob, - 'mixup_prob': self.mixup_prob, - 'hsv_prob': self.hsv_prob, - 'flip_prob': self.flip_prob, - 'degrees': self.degrees, - 'mosaic_scale': self.mosaic_scale, - 'mixup_scale': self.mixup_scale, - 'translate': self.translate, - 'shear': self.shear, - 'training_name': self.training_name, - 'project_details_id': self.project_details_id, - 'seed': self.seed, - 'train': self.train, - 'valid': self.valid, - 'test': self.test, - 'selected_model': self.selected_model, - 'transfer_learning': self.transfer_learning - } +from database.database import db + +class Training(db.Model): + __tablename__ = 'training' + + id = db.Column(db.Integer, primary_key=True, autoincrement=True, unique=True) + exp_name = db.Column(db.String(255)) + max_epoch = db.Column(db.Integer) + depth = db.Column(db.Float) + width = db.Column(db.Float) + activation = db.Column(db.String(255)) + warmup_epochs = db.Column(db.Integer) + warmup_lr = db.Column(db.Float) + basic_lr_per_img = db.Column(db.Float) + scheduler = db.Column(db.String(255)) + no_aug_epochs = db.Column(db.Integer) + min_lr_ratio = db.Column(db.Float) + ema = db.Column(db.Boolean) + weight_decay = db.Column(db.Float) + momentum = db.Column(db.Float) + # input_size moved to TrainingSize table + print_interval = db.Column(db.Integer) + eval_interval = db.Column(db.Integer) + save_history_ckpt = db.Column(db.Boolean) + # test_size moved to TrainingSize table + test_conf = db.Column(db.Float) + nms_thre = db.Column(db.Float) + multiscale_range = db.Column(db.Integer) + enable_mixup = db.Column(db.Boolean) + mosaic_prob = db.Column(db.Float) + mixup_prob = db.Column(db.Float) + hsv_prob = db.Column(db.Float) + flip_prob = db.Column(db.Float) + degrees = db.Column(db.Float) + # mosaic_scale moved to TrainingSize table + # mixup_scale moved to TrainingSize table + translate = db.Column(db.Float) + shear = db.Column(db.Float) + training_name = db.Column(db.String(255)) + project_details_id = db.Column(db.Integer, db.ForeignKey('training_project_details.id', ondelete='CASCADE'), nullable=False) + seed = db.Column(db.Integer) + train = db.Column(db.Integer) + valid = db.Column(db.Integer) + test = db.Column(db.Integer) + selected_model = db.Column(db.String(255)) + transfer_learning = db.Column(db.String(255)) + model_upload = db.Column(db.LargeBinary) + + # Relationship to size configurations (3NF) + size_configs = db.relationship('TrainingSize', backref='training', lazy=True, cascade='all, delete-orphan') + + def to_dict(self, include_sizes=True): + result = { + 'id': self.id, + 'exp_name': self.exp_name, + 'max_epoch': self.max_epoch, + 'depth': self.depth, + 'width': self.width, + 'activation': self.activation, + 'warmup_epochs': self.warmup_epochs, + 'warmup_lr': self.warmup_lr, + 'basic_lr_per_img': self.basic_lr_per_img, + 'scheduler': self.scheduler, + 'no_aug_epochs': self.no_aug_epochs, + 'min_lr_ratio': self.min_lr_ratio, + 'ema': self.ema, + 'weight_decay': self.weight_decay, + 'momentum': self.momentum, + 'print_interval': self.print_interval, + 'eval_interval': self.eval_interval, + 'save_history_ckpt': self.save_history_ckpt, + 'test_conf': self.test_conf, + 'nms_thre': self.nms_thre, + 'multiscale_range': self.multiscale_range, + 'enable_mixup': self.enable_mixup, + 'mosaic_prob': self.mosaic_prob, + 'mixup_prob': self.mixup_prob, + 'hsv_prob': self.hsv_prob, + 'flip_prob': self.flip_prob, + 'degrees': self.degrees, + 'translate': self.translate, + 'shear': self.shear, + 'training_name': self.training_name, + 'project_details_id': self.project_details_id, + 'seed': self.seed, + 'train': self.train, + 'valid': self.valid, + 'test': self.test, + 'selected_model': self.selected_model, + 'transfer_learning': self.transfer_learning + } + + # Include size arrays for backwards compatibility + if include_sizes: + from models.TrainingSize import TrainingSize + + def get_size_array(size_type): + sizes = TrainingSize.query.filter_by( + training_id=self.id, + size_type=size_type + ).order_by(TrainingSize.value_order).all() + return [s.value for s in sizes] if sizes else None + + result['input_size'] = get_size_array('input_size') + result['test_size'] = get_size_array('test_size') + result['mosaic_scale'] = get_size_array('mosaic_scale') + result['mixup_scale'] = get_size_array('mixup_scale') + + return result diff --git a/backend/requirements.txt b/backend/requirements.txt index 7bf80ec..35b495b 100644 --- a/backend/requirements.txt +++ b/backend/requirements.txt @@ -1,8 +1,8 @@ -Flask==3.0.0 -Flask-CORS==4.0.0 -Flask-SQLAlchemy==3.1.1 -SQLAlchemy==2.0.23 -PyMySQL==1.1.0 -python-dotenv==1.0.0 -requests==2.31.0 -Pillow==10.1.0 +Flask==3.0.0 +Flask-CORS==4.0.0 +Flask-SQLAlchemy==3.1.1 +SQLAlchemy==2.0.23 +PyMySQL==1.1.0 +python-dotenv==1.0.0 +requests==2.31.0 +Pillow==10.1.0 diff --git a/backend/routes/__init__.py b/backend/routes/__init__.py index 1102393..b71815a 100644 --- a/backend/routes/__init__.py +++ b/backend/routes/__init__.py @@ -1 +1 @@ -# Routes module +# Routes module diff --git a/backend/routes/api.js b/backend/routes/api.js index 917279d..cd593fc 100644 --- a/backend/routes/api.js +++ b/backend/routes/api.js @@ -1,496 +1,496 @@ -const express = require('express'); -const multer = require('multer'); -const upload = multer(); -const TrainingProject = require('../models/TrainingProject.js'); -const LabelStudioProject = require('../models/LabelStudioProject.js') -const { seedLabelStudio, updateStatus } = require('../services/seed-label-studio.js'); -const fs = require('fs'); -const path = require('path'); -const {generateTrainingJson} = require('../services/generate-json-yolox.js') - - -const router = express.Router(); - -// Ensure JSON bodies are parsed for all routes -router.use(express.json()); - -router.get('/seed', async (req, res) => { - const result = await seedLabelStudio(); - res.json(result); -}); - - - -// Trigger generate-json-yolox.js - -router.post('/generate-yolox-json', async (req, res) => { - const { project_id } = req.body; - if (!project_id) { - return res.status(400).json({ message: 'Missing project_id in request body' }); - } - try { - // Generate COCO JSONs - // Find all TrainingProjectDetails for this project - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id } }); - if (!detailsRows || detailsRows.length === 0) { - return res.status(404).json({ message: 'No TrainingProjectDetails found for project ' + project_id }); - } - // For each details row, generate coco.jsons and exp.py in projectfolder/project_details_id - const Training = require('../models/training.js'); - const { saveYoloxExp } = require('../services/generate-yolox-exp.js'); - const TrainingProject = require('../models/TrainingProject.js'); - const trainingProject = await TrainingProject.findByPk(project_id); - const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; - for (const details of detailsRows) { - const detailsId = details.id; - await generateTrainingJson(detailsId); - const trainings = await Training.findAll({ where: { project_details_id: detailsId } }); - if (trainings.length === 0) continue; - // For each training, save exp.py in projectfolder/project_details_id - const outDir = path.join(__dirname, '..', projectName, String(detailsId)); - if (!fs.existsSync(outDir)) fs.mkdirSync(outDir, { recursive: true }); - for (const training of trainings) { - const expFilePath = path.join(outDir, 'exp.py'); - await saveYoloxExp(training.id, expFilePath); - } - } - - // Find all trainings for this project - // ...existing code... - res.json({ message: 'YOLOX JSON and exp.py generated for project ' + project_id }); - } catch (err) { - console.error('Error generating YOLOX JSON:', err); - res.status(500).json({ message: 'Failed to generate YOLOX JSON', error: err.message }); - } -}); - -// Start YOLOX training -const { spawn } = require('child_process'); -router.post('/start-yolox-training', async (req, res) => { - try { - const { project_id, training_id } = req.body; - // Get project name - const trainingProject = await TrainingProject.findByPk(project_id); - const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; - // Look up training row by id or project_details_id - const Training = require('../models/training.js'); - let trainingRow = await Training.findByPk(training_id); - if (!trainingRow) { - trainingRow = await Training.findOne({ where: { project_details_id: training_id } }); - } - if (!trainingRow) { - return res.status(404).json({ error: `Training row not found for id or project_details_id ${training_id}` }); - } - const project_details_id = trainingRow.project_details_id; - // Use the generated exp.py from the correct project folder - const outDir = path.join(__dirname, '..', projectName, String(project_details_id)); - const yoloxMainDir = '/home/kitraining/Yolox/YOLOX-main'; - const expSrc = path.join(outDir, 'exp.py'); - if (!fs.existsSync(expSrc)) { - return res.status(500).json({ error: `exp.py not found at ${expSrc}` }); - } - // Source venv and run YOLOX training in YOLOX-main folder - const yoloxVenv = '/home/kitraining/Yolox/yolox_venv/bin/activate'; - // Determine model argument based on selected_model and transfer_learning - let modelArg = ''; - let cmd = ''; - if ( - trainingRow.transfer_learning && - typeof trainingRow.transfer_learning === 'string' && - trainingRow.transfer_learning.toLowerCase() === 'coco' - ) { - // If transfer_learning is 'coco', add -o and modelArg - modelArg = ` -c /home/kitraining/Yolox/YOLOX-main/pretrained/${trainingRow.selected_model}`; - cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16 -o ${modelArg}.pth --cache'`; - } else if ( - trainingRow.selected_model && - trainingRow.selected_model.toLowerCase() === 'coco' && - (!trainingRow.transfer_learning || trainingRow.transfer_learning === false) - ) { - // If selected_model is 'coco' and not transfer_learning, add modelArg only - modelArg = ` -c /pretrained/${trainingRow.selected_model}`; - cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16 -o ${modelArg}.pth --cache'`; - } else { - // Default: no modelArg - cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16' --cache`; - } - console.log(cmd) - const child = spawn(cmd, { shell: true, cwd: yoloxMainDir }); - child.stdout.pipe(process.stdout); - child.stderr.pipe(process.stderr); - - res.json({ message: 'Training started' }); - } catch (err) { - res.status(500).json({ error: 'Failed to start training', details: err.message }); - } -}); - -// Get YOLOX training log -router.get('/training-log', async (req, res) => { - try { - const { project_id, training_id } = req.query; - const trainingProject = await TrainingProject.findByPk(project_id); - const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; - const outDir = path.join(__dirname, '..', projectName, String(training_id)); - const logPath = path.join(outDir, 'training.log'); - if (!fs.existsSync(logPath)) { - return res.status(404).json({ error: 'Log not found' }); - } - const logData = fs.readFileSync(logPath, 'utf8'); - res.json({ log: logData }); - } catch (err) { - res.status(500).json({ error: 'Failed to fetch log', details: err.message }); - } -}); - -router.post('/training-projects', upload.single('project_image'), async (req, res) => { - try { - const { title, description } = req.body; - const classes = JSON.parse(req.body.classes); - const project_image = req.file ? req.file.buffer : null; - const project_image_type = req.file ? req.file.mimetype : null; - await TrainingProject.create({ - title, - description, - classes, - project_image, - project_image_type - }); - res.json({ message: 'Project created!' }); - } catch (error) { - console.error('Error creating project:', error); - res.status(500).json({ message: 'Failed to create project', error: error.message }); - } -}); - -router.get('/training-projects', async (req, res) => { - try { - const projects = await TrainingProject.findAll(); - // Convert BLOB to base64 data URL for each project - const serialized = projects.map(project => { - const plain = project.get({ plain: true }); - if (plain.project_image) { - const base64 = Buffer.from(plain.project_image).toString('base64'); - const mimeType = plain.project_image_type || 'image/png'; - plain.project_image = `data:${mimeType};base64,${base64}`; - } - return plain; - }); - res.json(serialized); - } catch (error) { - res.status(500).json({ message: 'Failed to fetch projects', error: error.message }); - } -}); - -router.get('/update-status', async (req, res) => { - res.json(updateStatus) -}) - -router.get('/label-studio-projects', async (req, res) => { - try { - const LabelStudioProject = require('../models/LabelStudioProject.js'); - const Image = require('../models/Images.js'); - const Annotation = require('../models/Annotation.js'); - const labelStudioProjects = await LabelStudioProject.findAll(); - const projectsWithCounts = await Promise.all(labelStudioProjects.map(async project => { - const plain = project.get({ plain: true }); - // Get all images for this project - const images = await Image.findAll({ where: { project_id: plain.project_id } }); - let annotationCounts = {}; - if (images.length > 0) { - const imageIds = images.map(img => img.image_id); - // Get all annotations for these images - const annotations = await Annotation.findAll({ where: { image_id: imageIds } }); - // Count by label - for (const ann of annotations) { - const label = ann.Label; - annotationCounts[label] = (annotationCounts[label] || 0) + 1; - } - } - plain.annotationCounts = annotationCounts; - return plain; - })); - res.json(projectsWithCounts); - } catch (error) { - res.status(500).json({ message: 'Failed to fetch projects', error: error.message }); - } -}) - - -// POST endpoint to create TrainingProjectDetails with all fields -router.post('/training-project-details', async (req, res) => { - try { - const { - project_id, - annotation_projects, - class_map, - description - } = req.body; - if (!project_id || !annotation_projects) { - return res.status(400).json({ message: 'Missing required fields' }); - } - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const created = await TrainingProjectDetails.create({ - project_id, - annotation_projects, - class_map: class_map || null, - description: description || null - }); - res.json({ message: 'TrainingProjectDetails created', details: created }); - } catch (error) { - res.status(500).json({ message: 'Failed to create TrainingProjectDetails', error: error.message }); - } -}); - -// GET endpoint to fetch all TrainingProjectDetails -router.get('/training-project-details', async (req, res) => { - try { - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const details = await TrainingProjectDetails.findAll(); - res.json(details); - } catch (error) { - res.status(500).json({ message: 'Failed to fetch TrainingProjectDetails', error: error.message }); - } -}); - -// PUT endpoint to update class_map and description in TrainingProjectDetails -router.put('/training-project-details', async (req, res) => { - try { - const { project_id, class_map, description } = req.body; - if (!project_id || !class_map || !description) { - return res.status(400).json({ message: 'Missing required fields' }); - } - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const details = await TrainingProjectDetails.findOne({ where: { project_id } }); - if (!details) { - return res.status(404).json({ message: 'TrainingProjectDetails not found' }); - } - details.class_map = class_map; - details.description = description; - await details.save(); - res.json({ message: 'Class map and description updated', details }); - } catch (error) { - res.status(500).json({ message: 'Failed to update class map or description', error: error.message }); - } -}); - -// POST endpoint to receive YOLOX settings and save to DB (handles multipart/form-data) -router.post('/yolox-settings', upload.any(), async (req, res) => { - try { - const settings = req.body; - // Debug: Log all received fields and types - console.log('--- YOLOX settings received ---'); - console.log('settings:', settings); - if (req.files && req.files.length > 0) { - console.log('Files received:', req.files.map(f => ({ fieldname: f.fieldname, originalname: f.originalname, size: f.size }))); - } - // Declare requiredFields once - const requiredFields = ['project_details_id', 'exp_name', 'max_epoch', 'depth', 'width', 'activation', 'train', 'valid', 'test', 'selected_model', 'transfer_learning']; - // Log types of required fields - requiredFields.forEach(field => { - console.log(`Field '${field}': value='${settings[field]}', type='${typeof settings[field]}'`); - }); - // Map select_model to selected_model if present - if (settings && settings.select_model && !settings.selected_model) { - settings.selected_model = settings.select_model; - delete settings.select_model; - } - // Lookup project_details_id from project_id - if (!settings.project_id || isNaN(Number(settings.project_id))) { - throw new Error('Missing or invalid project_id in request. Cannot assign training to a project.'); - } - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - let details = await TrainingProjectDetails.findOne({ where: { project_id: settings.project_id } }); - if (!details) { - details = await TrainingProjectDetails.create({ - project_id: settings.project_id, - annotation_projects: [], - class_map: null, - description: null - }); - } - settings.project_details_id = details.id; - // Map 'act' from frontend to 'activation' for DB - if (settings.act !== undefined) { - settings.activation = settings.act; - delete settings.act; - } - // Type conversion for DB compatibility - [ - 'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', 'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum', 'print_interval', 'eval_interval', 'test_conf', 'nmsthre', 'multiscale_range', 'degrees', 'translate', 'shear', 'train', 'valid', 'test' - ].forEach(f => { - if (settings[f] !== undefined) settings[f] = Number(settings[f]); - }); - // Improved boolean conversion - ['ema', 'enable_mixup', 'save_history_ckpt'].forEach(f => { - if (settings[f] !== undefined) { - if (typeof settings[f] === 'string') { - settings[f] = settings[f].toLowerCase() === 'true'; - } else { - settings[f] = Boolean(settings[f]); - } - } - }); - // Improved array conversion - ['mosaic_scale', 'mixup_scale', 'scale'].forEach(f => { - if (settings[f] && typeof settings[f] === 'string') { - settings[f] = settings[f] - .split(',') - .map(s => Number(s.trim())) - .filter(n => !isNaN(n)); - } - }); - // Trim all string fields - Object.keys(settings).forEach(f => { - if (typeof settings[f] === 'string') settings[f] = settings[f].trim(); - }); - // Set default for transfer_learning if missing - if (settings.transfer_learning === undefined) settings.transfer_learning = false; - // Convert empty string seed to null - if ('seed' in settings && (settings.seed === '' || settings.seed === undefined)) { - settings.seed = null; - } - // Validate required fields for training table - for (const field of requiredFields) { - if (settings[field] === undefined || settings[field] === null || settings[field] === '') { - console.error('Missing required field:', field, 'Value:', settings[field]); - throw new Error('Missing required field: ' + field); - } - } - console.log('Received YOLOX settings:', settings); - // Handle uploaded model file (ckpt_upload) - if (req.files && req.files.length > 0) { - const ckptFile = req.files.find(f => f.fieldname === 'ckpt_upload'); - if (ckptFile) { - const uploadDir = path.join(__dirname, '..', 'uploads'); - if (!fs.existsSync(uploadDir)) fs.mkdirSync(uploadDir); - const filename = ckptFile.originalname || `uploaded_model_${settings.project_id}.pth`; - const filePath = path.join(uploadDir, filename); - fs.writeFileSync(filePath, ckptFile.buffer); - settings.model_upload = filePath; - } - } - // Save settings to DB only (no file) - const { pushYoloxExpToDb } = require('../services/push-yolox-exp.js'); - const training = await pushYoloxExpToDb(settings); - res.json({ message: 'YOLOX settings saved to DB', training }); - } catch (error) { - console.error('Error in /api/yolox-settings:', error.stack || error); - res.status(500).json({ message: 'Failed to save YOLOX settings', error: error.message }); - } -}); - -// POST endpoint to receive binary model file and save to disk (not DB) -router.post('/yolox-settings/upload', async (req, res) => { - try { - const projectId = req.query.project_id; - if (!projectId) return res.status(400).json({ message: 'Missing project_id in query' }); - // Save file to disk - const uploadDir = path.join(__dirname, '..', 'uploads'); - if (!fs.existsSync(uploadDir)) fs.mkdirSync(uploadDir); - const filename = req.headers['x-upload-filename'] || `uploaded_model_${projectId}.pth`; - const filePath = path.join(uploadDir, filename); - const chunks = []; - req.on('data', chunk => chunks.push(chunk)); - req.on('end', async () => { - const buffer = Buffer.concat(chunks); - fs.writeFile(filePath, buffer, async err => { - if (err) { - console.error('Error saving file:', err); - return res.status(500).json({ message: 'Failed to save model file', error: err.message }); - } - // Update latest training row for this project with file path - try { - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const Training = require('../models/training.js'); - // Find details row for this project - const details = await TrainingProjectDetails.findOne({ where: { project_id: projectId } }); - if (!details) return res.status(404).json({ message: 'No TrainingProjectDetails found for project_id' }); - // Find latest training for this details row - const training = await Training.findOne({ where: { project_details_id: details.id }, order: [['createdAt', 'DESC']] }); - if (!training) return res.status(404).json({ message: 'No training found for project_id' }); - // Save file path to model_upload field - training.model_upload = filePath; - await training.save(); - res.json({ message: 'Model file uploaded and saved to disk', filename, trainingId: training.id }); - } catch (dbErr) { - console.error('Error updating training with file path:', dbErr); - res.status(500).json({ message: 'File saved but failed to update training row', error: dbErr.message }); - } - }); - }); - } catch (error) { - console.error('Error in /api/yolox-settings/upload:', error.stack || error); - res.status(500).json({ message: 'Failed to upload model file', error: error.message }); - } -}); - -// GET endpoint to fetch all trainings (optionally filtered by project_id) -router.get('/trainings', async (req, res) => { - try { - const project_id = req.query.project_id; - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const Training = require('../models/training.js'); - if (project_id) { - // Find all details rows for this project - const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id } }); - if (!detailsRows || detailsRows.length === 0) return res.json([]); - // Get all trainings linked to any details row for this project - const detailsIds = detailsRows.map(d => d.id); - const trainings = await Training.findAll({ where: { project_details_id: detailsIds } }); - return res.json(trainings); - } else { - // Return all trainings if no project_id is specified - const trainings = await Training.findAll(); - return res.json(trainings); - } - } catch (error) { - res.status(500).json({ message: 'Failed to fetch trainings', error: error.message }); - } -}); - -// DELETE endpoint to remove a training by id -router.delete('/trainings/:id', async (req, res) => { - try { - const Training = require('../models/training.js'); - const id = req.params.id; - const deleted = await Training.destroy({ where: { id } }); - if (deleted) { - res.json({ message: 'Training deleted' }); - } else { - res.status(404).json({ message: 'Training not found' }); - } - } catch (error) { - res.status(500).json({ message: 'Failed to delete training', error: error.message }); - } -}); - -// DELETE endpoint to remove a training project and all related entries -router.delete('/training-projects/:id', async (req, res) => { - try { - const projectId = req.params.id; - const TrainingProject = require('../models/TrainingProject.js'); - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const Training = require('../models/training.js'); - // Find details row(s) for this project - const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id: projectId } }); - const detailsIds = detailsRows.map(d => d.id); - // Delete all trainings linked to these details - if (detailsIds.length > 0) { - await Training.destroy({ where: { project_details_id: detailsIds } }); - await TrainingProjectDetails.destroy({ where: { project_id: projectId } }); - } - // Delete the project itself - const deleted = await TrainingProject.destroy({ where: { project_id: projectId } }); - if (deleted) { - res.json({ message: 'Training project and all related entries deleted' }); - } else { - res.status(404).json({ message: 'Training project not found' }); - } - } catch (error) { - res.status(500).json({ message: 'Failed to delete training project', error: error.message }); - } -}); - -module.exports = router; +const express = require('express'); +const multer = require('multer'); +const upload = multer(); +const TrainingProject = require('../models/TrainingProject.js'); +const LabelStudioProject = require('../models/LabelStudioProject.js') +const { seedLabelStudio, updateStatus } = require('../services/seed-label-studio.js'); +const fs = require('fs'); +const path = require('path'); +const {generateTrainingJson} = require('../services/generate-json-yolox.js') + + +const router = express.Router(); + +// Ensure JSON bodies are parsed for all routes +router.use(express.json()); + +router.get('/seed', async (req, res) => { + const result = await seedLabelStudio(); + res.json(result); +}); + + + +// Trigger generate-json-yolox.js + +router.post('/generate-yolox-json', async (req, res) => { + const { project_id } = req.body; + if (!project_id) { + return res.status(400).json({ message: 'Missing project_id in request body' }); + } + try { + // Generate COCO JSONs + // Find all TrainingProjectDetails for this project + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id } }); + if (!detailsRows || detailsRows.length === 0) { + return res.status(404).json({ message: 'No TrainingProjectDetails found for project ' + project_id }); + } + // For each details row, generate coco.jsons and exp.py in projectfolder/project_details_id + const Training = require('../models/training.js'); + const { saveYoloxExp } = require('../services/generate-yolox-exp.js'); + const TrainingProject = require('../models/TrainingProject.js'); + const trainingProject = await TrainingProject.findByPk(project_id); + const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; + for (const details of detailsRows) { + const detailsId = details.id; + await generateTrainingJson(detailsId); + const trainings = await Training.findAll({ where: { project_details_id: detailsId } }); + if (trainings.length === 0) continue; + // For each training, save exp.py in projectfolder/project_details_id + const outDir = path.join(__dirname, '..', projectName, String(detailsId)); + if (!fs.existsSync(outDir)) fs.mkdirSync(outDir, { recursive: true }); + for (const training of trainings) { + const expFilePath = path.join(outDir, 'exp.py'); + await saveYoloxExp(training.id, expFilePath); + } + } + + // Find all trainings for this project + // ...existing code... + res.json({ message: 'YOLOX JSON and exp.py generated for project ' + project_id }); + } catch (err) { + console.error('Error generating YOLOX JSON:', err); + res.status(500).json({ message: 'Failed to generate YOLOX JSON', error: err.message }); + } +}); + +// Start YOLOX training +const { spawn } = require('child_process'); +router.post('/start-yolox-training', async (req, res) => { + try { + const { project_id, training_id } = req.body; + // Get project name + const trainingProject = await TrainingProject.findByPk(project_id); + const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; + // Look up training row by id or project_details_id + const Training = require('../models/training.js'); + let trainingRow = await Training.findByPk(training_id); + if (!trainingRow) { + trainingRow = await Training.findOne({ where: { project_details_id: training_id } }); + } + if (!trainingRow) { + return res.status(404).json({ error: `Training row not found for id or project_details_id ${training_id}` }); + } + const project_details_id = trainingRow.project_details_id; + // Use the generated exp.py from the correct project folder + const outDir = path.join(__dirname, '..', projectName, String(project_details_id)); + const yoloxMainDir = '/home/kitraining/Yolox/YOLOX-main'; + const expSrc = path.join(outDir, 'exp.py'); + if (!fs.existsSync(expSrc)) { + return res.status(500).json({ error: `exp.py not found at ${expSrc}` }); + } + // Source venv and run YOLOX training in YOLOX-main folder + const yoloxVenv = '/home/kitraining/Yolox/yolox_venv/bin/activate'; + // Determine model argument based on selected_model and transfer_learning + let modelArg = ''; + let cmd = ''; + if ( + trainingRow.transfer_learning && + typeof trainingRow.transfer_learning === 'string' && + trainingRow.transfer_learning.toLowerCase() === 'coco' + ) { + // If transfer_learning is 'coco', add -o and modelArg + modelArg = ` -c /home/kitraining/Yolox/YOLOX-main/pretrained/${trainingRow.selected_model}`; + cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16 -o ${modelArg}.pth --cache'`; + } else if ( + trainingRow.selected_model && + trainingRow.selected_model.toLowerCase() === 'coco' && + (!trainingRow.transfer_learning || trainingRow.transfer_learning === false) + ) { + // If selected_model is 'coco' and not transfer_learning, add modelArg only + modelArg = ` -c /pretrained/${trainingRow.selected_model}`; + cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16 -o ${modelArg}.pth --cache'`; + } else { + // Default: no modelArg + cmd = `bash -c 'source ${yoloxVenv} && python tools/train.py -f ${expSrc} -d 1 -b 8 --fp16' --cache`; + } + console.log(cmd) + const child = spawn(cmd, { shell: true, cwd: yoloxMainDir }); + child.stdout.pipe(process.stdout); + child.stderr.pipe(process.stderr); + + res.json({ message: 'Training started' }); + } catch (err) { + res.status(500).json({ error: 'Failed to start training', details: err.message }); + } +}); + +// Get YOLOX training log +router.get('/training-log', async (req, res) => { + try { + const { project_id, training_id } = req.query; + const trainingProject = await TrainingProject.findByPk(project_id); + const projectName = trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${project_id}`; + const outDir = path.join(__dirname, '..', projectName, String(training_id)); + const logPath = path.join(outDir, 'training.log'); + if (!fs.existsSync(logPath)) { + return res.status(404).json({ error: 'Log not found' }); + } + const logData = fs.readFileSync(logPath, 'utf8'); + res.json({ log: logData }); + } catch (err) { + res.status(500).json({ error: 'Failed to fetch log', details: err.message }); + } +}); + +router.post('/training-projects', upload.single('project_image'), async (req, res) => { + try { + const { title, description } = req.body; + const classes = JSON.parse(req.body.classes); + const project_image = req.file ? req.file.buffer : null; + const project_image_type = req.file ? req.file.mimetype : null; + await TrainingProject.create({ + title, + description, + classes, + project_image, + project_image_type + }); + res.json({ message: 'Project created!' }); + } catch (error) { + console.error('Error creating project:', error); + res.status(500).json({ message: 'Failed to create project', error: error.message }); + } +}); + +router.get('/training-projects', async (req, res) => { + try { + const projects = await TrainingProject.findAll(); + // Convert BLOB to base64 data URL for each project + const serialized = projects.map(project => { + const plain = project.get({ plain: true }); + if (plain.project_image) { + const base64 = Buffer.from(plain.project_image).toString('base64'); + const mimeType = plain.project_image_type || 'image/png'; + plain.project_image = `data:${mimeType};base64,${base64}`; + } + return plain; + }); + res.json(serialized); + } catch (error) { + res.status(500).json({ message: 'Failed to fetch projects', error: error.message }); + } +}); + +router.get('/update-status', async (req, res) => { + res.json(updateStatus) +}) + +router.get('/label-studio-projects', async (req, res) => { + try { + const LabelStudioProject = require('../models/LabelStudioProject.js'); + const Image = require('../models/Images.js'); + const Annotation = require('../models/Annotation.js'); + const labelStudioProjects = await LabelStudioProject.findAll(); + const projectsWithCounts = await Promise.all(labelStudioProjects.map(async project => { + const plain = project.get({ plain: true }); + // Get all images for this project + const images = await Image.findAll({ where: { project_id: plain.project_id } }); + let annotationCounts = {}; + if (images.length > 0) { + const imageIds = images.map(img => img.image_id); + // Get all annotations for these images + const annotations = await Annotation.findAll({ where: { image_id: imageIds } }); + // Count by label + for (const ann of annotations) { + const label = ann.Label; + annotationCounts[label] = (annotationCounts[label] || 0) + 1; + } + } + plain.annotationCounts = annotationCounts; + return plain; + })); + res.json(projectsWithCounts); + } catch (error) { + res.status(500).json({ message: 'Failed to fetch projects', error: error.message }); + } +}) + + +// POST endpoint to create TrainingProjectDetails with all fields +router.post('/training-project-details', async (req, res) => { + try { + const { + project_id, + annotation_projects, + class_map, + description + } = req.body; + if (!project_id || !annotation_projects) { + return res.status(400).json({ message: 'Missing required fields' }); + } + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const created = await TrainingProjectDetails.create({ + project_id, + annotation_projects, + class_map: class_map || null, + description: description || null + }); + res.json({ message: 'TrainingProjectDetails created', details: created }); + } catch (error) { + res.status(500).json({ message: 'Failed to create TrainingProjectDetails', error: error.message }); + } +}); + +// GET endpoint to fetch all TrainingProjectDetails +router.get('/training-project-details', async (req, res) => { + try { + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const details = await TrainingProjectDetails.findAll(); + res.json(details); + } catch (error) { + res.status(500).json({ message: 'Failed to fetch TrainingProjectDetails', error: error.message }); + } +}); + +// PUT endpoint to update class_map and description in TrainingProjectDetails +router.put('/training-project-details', async (req, res) => { + try { + const { project_id, class_map, description } = req.body; + if (!project_id || !class_map || !description) { + return res.status(400).json({ message: 'Missing required fields' }); + } + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const details = await TrainingProjectDetails.findOne({ where: { project_id } }); + if (!details) { + return res.status(404).json({ message: 'TrainingProjectDetails not found' }); + } + details.class_map = class_map; + details.description = description; + await details.save(); + res.json({ message: 'Class map and description updated', details }); + } catch (error) { + res.status(500).json({ message: 'Failed to update class map or description', error: error.message }); + } +}); + +// POST endpoint to receive YOLOX settings and save to DB (handles multipart/form-data) +router.post('/yolox-settings', upload.any(), async (req, res) => { + try { + const settings = req.body; + // Debug: Log all received fields and types + console.log('--- YOLOX settings received ---'); + console.log('settings:', settings); + if (req.files && req.files.length > 0) { + console.log('Files received:', req.files.map(f => ({ fieldname: f.fieldname, originalname: f.originalname, size: f.size }))); + } + // Declare requiredFields once + const requiredFields = ['project_details_id', 'exp_name', 'max_epoch', 'depth', 'width', 'activation', 'train', 'valid', 'test', 'selected_model', 'transfer_learning']; + // Log types of required fields + requiredFields.forEach(field => { + console.log(`Field '${field}': value='${settings[field]}', type='${typeof settings[field]}'`); + }); + // Map select_model to selected_model if present + if (settings && settings.select_model && !settings.selected_model) { + settings.selected_model = settings.select_model; + delete settings.select_model; + } + // Lookup project_details_id from project_id + if (!settings.project_id || isNaN(Number(settings.project_id))) { + throw new Error('Missing or invalid project_id in request. Cannot assign training to a project.'); + } + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + let details = await TrainingProjectDetails.findOne({ where: { project_id: settings.project_id } }); + if (!details) { + details = await TrainingProjectDetails.create({ + project_id: settings.project_id, + annotation_projects: [], + class_map: null, + description: null + }); + } + settings.project_details_id = details.id; + // Map 'act' from frontend to 'activation' for DB + if (settings.act !== undefined) { + settings.activation = settings.act; + delete settings.act; + } + // Type conversion for DB compatibility + [ + 'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', 'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum', 'print_interval', 'eval_interval', 'test_conf', 'nmsthre', 'multiscale_range', 'degrees', 'translate', 'shear', 'train', 'valid', 'test' + ].forEach(f => { + if (settings[f] !== undefined) settings[f] = Number(settings[f]); + }); + // Improved boolean conversion + ['ema', 'enable_mixup', 'save_history_ckpt'].forEach(f => { + if (settings[f] !== undefined) { + if (typeof settings[f] === 'string') { + settings[f] = settings[f].toLowerCase() === 'true'; + } else { + settings[f] = Boolean(settings[f]); + } + } + }); + // Improved array conversion + ['mosaic_scale', 'mixup_scale', 'scale'].forEach(f => { + if (settings[f] && typeof settings[f] === 'string') { + settings[f] = settings[f] + .split(',') + .map(s => Number(s.trim())) + .filter(n => !isNaN(n)); + } + }); + // Trim all string fields + Object.keys(settings).forEach(f => { + if (typeof settings[f] === 'string') settings[f] = settings[f].trim(); + }); + // Set default for transfer_learning if missing + if (settings.transfer_learning === undefined) settings.transfer_learning = false; + // Convert empty string seed to null + if ('seed' in settings && (settings.seed === '' || settings.seed === undefined)) { + settings.seed = null; + } + // Validate required fields for training table + for (const field of requiredFields) { + if (settings[field] === undefined || settings[field] === null || settings[field] === '') { + console.error('Missing required field:', field, 'Value:', settings[field]); + throw new Error('Missing required field: ' + field); + } + } + console.log('Received YOLOX settings:', settings); + // Handle uploaded model file (ckpt_upload) + if (req.files && req.files.length > 0) { + const ckptFile = req.files.find(f => f.fieldname === 'ckpt_upload'); + if (ckptFile) { + const uploadDir = path.join(__dirname, '..', 'uploads'); + if (!fs.existsSync(uploadDir)) fs.mkdirSync(uploadDir); + const filename = ckptFile.originalname || `uploaded_model_${settings.project_id}.pth`; + const filePath = path.join(uploadDir, filename); + fs.writeFileSync(filePath, ckptFile.buffer); + settings.model_upload = filePath; + } + } + // Save settings to DB only (no file) + const { pushYoloxExpToDb } = require('../services/push-yolox-exp.js'); + const training = await pushYoloxExpToDb(settings); + res.json({ message: 'YOLOX settings saved to DB', training }); + } catch (error) { + console.error('Error in /api/yolox-settings:', error.stack || error); + res.status(500).json({ message: 'Failed to save YOLOX settings', error: error.message }); + } +}); + +// POST endpoint to receive binary model file and save to disk (not DB) +router.post('/yolox-settings/upload', async (req, res) => { + try { + const projectId = req.query.project_id; + if (!projectId) return res.status(400).json({ message: 'Missing project_id in query' }); + // Save file to disk + const uploadDir = path.join(__dirname, '..', 'uploads'); + if (!fs.existsSync(uploadDir)) fs.mkdirSync(uploadDir); + const filename = req.headers['x-upload-filename'] || `uploaded_model_${projectId}.pth`; + const filePath = path.join(uploadDir, filename); + const chunks = []; + req.on('data', chunk => chunks.push(chunk)); + req.on('end', async () => { + const buffer = Buffer.concat(chunks); + fs.writeFile(filePath, buffer, async err => { + if (err) { + console.error('Error saving file:', err); + return res.status(500).json({ message: 'Failed to save model file', error: err.message }); + } + // Update latest training row for this project with file path + try { + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const Training = require('../models/training.js'); + // Find details row for this project + const details = await TrainingProjectDetails.findOne({ where: { project_id: projectId } }); + if (!details) return res.status(404).json({ message: 'No TrainingProjectDetails found for project_id' }); + // Find latest training for this details row + const training = await Training.findOne({ where: { project_details_id: details.id }, order: [['createdAt', 'DESC']] }); + if (!training) return res.status(404).json({ message: 'No training found for project_id' }); + // Save file path to model_upload field + training.model_upload = filePath; + await training.save(); + res.json({ message: 'Model file uploaded and saved to disk', filename, trainingId: training.id }); + } catch (dbErr) { + console.error('Error updating training with file path:', dbErr); + res.status(500).json({ message: 'File saved but failed to update training row', error: dbErr.message }); + } + }); + }); + } catch (error) { + console.error('Error in /api/yolox-settings/upload:', error.stack || error); + res.status(500).json({ message: 'Failed to upload model file', error: error.message }); + } +}); + +// GET endpoint to fetch all trainings (optionally filtered by project_id) +router.get('/trainings', async (req, res) => { + try { + const project_id = req.query.project_id; + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const Training = require('../models/training.js'); + if (project_id) { + // Find all details rows for this project + const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id } }); + if (!detailsRows || detailsRows.length === 0) return res.json([]); + // Get all trainings linked to any details row for this project + const detailsIds = detailsRows.map(d => d.id); + const trainings = await Training.findAll({ where: { project_details_id: detailsIds } }); + return res.json(trainings); + } else { + // Return all trainings if no project_id is specified + const trainings = await Training.findAll(); + return res.json(trainings); + } + } catch (error) { + res.status(500).json({ message: 'Failed to fetch trainings', error: error.message }); + } +}); + +// DELETE endpoint to remove a training by id +router.delete('/trainings/:id', async (req, res) => { + try { + const Training = require('../models/training.js'); + const id = req.params.id; + const deleted = await Training.destroy({ where: { id } }); + if (deleted) { + res.json({ message: 'Training deleted' }); + } else { + res.status(404).json({ message: 'Training not found' }); + } + } catch (error) { + res.status(500).json({ message: 'Failed to delete training', error: error.message }); + } +}); + +// DELETE endpoint to remove a training project and all related entries +router.delete('/training-projects/:id', async (req, res) => { + try { + const projectId = req.params.id; + const TrainingProject = require('../models/TrainingProject.js'); + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const Training = require('../models/training.js'); + // Find details row(s) for this project + const detailsRows = await TrainingProjectDetails.findAll({ where: { project_id: projectId } }); + const detailsIds = detailsRows.map(d => d.id); + // Delete all trainings linked to these details + if (detailsIds.length > 0) { + await Training.destroy({ where: { project_details_id: detailsIds } }); + await TrainingProjectDetails.destroy({ where: { project_id: projectId } }); + } + // Delete the project itself + const deleted = await TrainingProject.destroy({ where: { project_id: projectId } }); + if (deleted) { + res.json({ message: 'Training project and all related entries deleted' }); + } else { + res.status(404).json({ message: 'Training project not found' }); + } + } catch (error) { + res.status(500).json({ message: 'Failed to delete training project', error: error.message }); + } +}); + +module.exports = router; diff --git a/backend/routes/api.py b/backend/routes/api.py index b9b295c..07cf0f2 100644 --- a/backend/routes/api.py +++ b/backend/routes/api.py @@ -1,541 +1,857 @@ -from flask import Blueprint, request, jsonify, send_file -from werkzeug.utils import secure_filename -import os -import json -import subprocess -from database.database import db -from models.TrainingProject import TrainingProject -from models.TrainingProjectDetails import TrainingProjectDetails -from models.training import Training -from models.LabelStudioProject import LabelStudioProject -from models.Images import Image -from models.Annotation import Annotation - -api_bp = Blueprint('api', __name__) - -# Global update status (similar to Node.js version) -update_status = {"running": False} - -@api_bp.route('/seed', methods=['GET']) -def seed(): - """Trigger seeding from Label Studio""" - from services.seed_label_studio import seed_label_studio - result = seed_label_studio() - return jsonify(result) - -@api_bp.route('/generate-yolox-json', methods=['POST']) -def generate_yolox_json(): - """Generate YOLOX JSON and exp.py for a project""" - try: - data = request.get_json() - project_id = data.get('project_id') - - if not project_id: - return jsonify({'message': 'Missing project_id in request body'}), 400 - - # Find all TrainingProjectDetails for this project - details_rows = TrainingProjectDetails.query.filter_by(project_id=project_id).all() - - if not details_rows: - return jsonify({'message': f'No TrainingProjectDetails found for project {project_id}'}), 404 - - # Get project name - training_project = TrainingProject.query.get(project_id) - project_name = training_project.title.replace(' ', '_') if training_project.title else f'project_{project_id}' - - from services.generate_json_yolox import generate_training_json - from services.generate_yolox_exp import save_yolox_exp - - # For each details row, generate coco.jsons and exp.py - for details in details_rows: - details_id = details.id - generate_training_json(details_id) - - # Find all trainings for this details row - trainings = Training.query.filter_by(project_details_id=details_id).all() - if not trainings: - continue - - # Create output directory - out_dir = os.path.join(os.path.dirname(__file__), '..', project_name, str(details_id)) - os.makedirs(out_dir, exist_ok=True) - - # Save exp.py for each training - for training in trainings: - exp_file_path = os.path.join(out_dir, 'exp.py') - save_yolox_exp(training.id, exp_file_path) - - return jsonify({'message': f'YOLOX JSON and exp.py generated for project {project_id}'}) - - except Exception as err: - print(f'Error generating YOLOX JSON: {err}') - return jsonify({'message': 'Failed to generate YOLOX JSON', 'error': str(err)}), 500 - -@api_bp.route('/start-yolox-training', methods=['POST']) -def start_yolox_training(): - """Start YOLOX training""" - try: - data = request.get_json() - project_id = data.get('project_id') - training_id = data.get('training_id') - - # Get project name - training_project = TrainingProject.query.get(project_id) - project_name = training_project.title.replace(' ', '_') if training_project.title else f'project_{project_id}' - - # Look up training row - training_row = Training.query.get(training_id) - if not training_row: - training_row = Training.query.filter_by(project_details_id=training_id).first() - - if not training_row: - return jsonify({'error': f'Training row not found for id or project_details_id {training_id}'}), 404 - - project_details_id = training_row.project_details_id - - # Path to exp.py - out_dir = os.path.join(os.path.dirname(__file__), '..', project_name, str(project_details_id)) - exp_src = os.path.join(out_dir, 'exp.py') - - if not os.path.exists(exp_src): - return jsonify({'error': f'exp.py not found at {exp_src}'}), 500 - - # YOLOX configuration - yolox_main_dir = '/home/kitraining/Yolox/YOLOX-main' - yolox_venv = '/home/kitraining/Yolox/yolox_venv/bin/activate' - - # Determine model argument - model_arg = '' - cmd = '' - - if (training_row.transfer_learning and - isinstance(training_row.transfer_learning, str) and - training_row.transfer_learning.lower() == 'coco'): - model_arg = f' -c /home/kitraining/Yolox/YOLOX-main/pretrained/{training_row.selected_model}' - cmd = f'bash -c \'source {yolox_venv} && python tools/train.py -f {exp_src} -d 1 -b 8 --fp16 -o {model_arg}.pth --cache\'' - elif (training_row.selected_model and - training_row.selected_model.lower() == 'coco' and - (not training_row.transfer_learning or training_row.transfer_learning == False)): - model_arg = f' -c /pretrained/{training_row.selected_model}' - cmd = f'bash -c \'source {yolox_venv} && python tools/train.py -f {exp_src} -d 1 -b 8 --fp16 -o {model_arg}.pth --cache\'' - else: - cmd = f'bash -c \'source {yolox_venv} && python tools/train.py -f {exp_src} -d 1 -b 8 --fp16 --cache\'' - - print(cmd) - - # Start training in background - subprocess.Popen(cmd, shell=True, cwd=yolox_main_dir) - - return jsonify({'message': 'Training started'}) - - except Exception as err: - return jsonify({'error': 'Failed to start training', 'details': str(err)}), 500 - -@api_bp.route('/training-log', methods=['GET']) -def training_log(): - """Get YOLOX training log""" - try: - project_id = request.args.get('project_id') - training_id = request.args.get('training_id') - - training_project = TrainingProject.query.get(project_id) - project_name = training_project.title.replace(' ', '_') if training_project.title else f'project_{project_id}' - - out_dir = os.path.join(os.path.dirname(__file__), '..', project_name, str(training_id)) - log_path = os.path.join(out_dir, 'training.log') - - if not os.path.exists(log_path): - return jsonify({'error': 'Log not found'}), 404 - - with open(log_path, 'r') as f: - log_data = f.read() - - return jsonify({'log': log_data}) - - except Exception as err: - return jsonify({'error': 'Failed to fetch log', 'details': str(err)}), 500 - -@api_bp.route('/training-projects', methods=['POST']) -def create_training_project(): - """Create a new training project""" - try: - title = request.form.get('title') - description = request.form.get('description') - classes = json.loads(request.form.get('classes', '[]')) - - project_image = None - project_image_type = None - - if 'project_image' in request.files: - file = request.files['project_image'] - project_image = file.read() - project_image_type = file.content_type - - project = TrainingProject( - title=title, - description=description, - classes=classes, - project_image=project_image, - project_image_type=project_image_type - ) - - db.session.add(project) - db.session.commit() - - return jsonify({'message': 'Project created!'}) - - except Exception as error: - print(f'Error creating project: {error}') - db.session.rollback() - return jsonify({'message': 'Failed to create project', 'error': str(error)}), 500 - -@api_bp.route('/training-projects', methods=['GET']) -def get_training_projects(): - """Get all training projects""" - try: - projects = TrainingProject.query.all() - serialized = [project.to_dict() for project in projects] - return jsonify(serialized) - - except Exception as error: - return jsonify({'message': 'Failed to fetch projects', 'error': str(error)}), 500 - -@api_bp.route('/update-status', methods=['GET']) -def get_update_status(): - """Get update status""" - return jsonify(update_status) - -@api_bp.route('/label-studio-projects', methods=['GET']) -def get_label_studio_projects(): - """Get all Label Studio projects with annotation counts""" - try: - from sqlalchemy import func - - # Get all projects - label_studio_projects = LabelStudioProject.query.all() - - # Get annotation counts in one query using SQL aggregation - annotation_counts_query = db.session.query( - Image.project_id, - Annotation.Label, - func.count(Annotation.annotation_id).label('count') - ).join( - Annotation, Image.image_id == Annotation.image_id - ).group_by( - Image.project_id, Annotation.Label - ).all() - - # Organize counts by project_id - counts_by_project = {} - for project_id, label, count in annotation_counts_query: - if project_id not in counts_by_project: - counts_by_project[project_id] = {} - counts_by_project[project_id][label] = count - - # Build result - projects_with_counts = [] - for project in label_studio_projects: - project_dict = project.to_dict() - project_dict['annotationCounts'] = counts_by_project.get(project.project_id, {}) - projects_with_counts.append(project_dict) - - return jsonify(projects_with_counts) - - except Exception as error: - return jsonify({'message': 'Failed to fetch projects', 'error': str(error)}), 500 - -@api_bp.route('/training-project-details', methods=['POST']) -def create_training_project_details(): - """Create TrainingProjectDetails""" - try: - data = request.get_json() - project_id = data.get('project_id') - annotation_projects = data.get('annotation_projects') - class_map = data.get('class_map') - description = data.get('description') - - if not project_id or annotation_projects is None: - return jsonify({'message': 'Missing required fields'}), 400 - - details = TrainingProjectDetails( - project_id=project_id, - annotation_projects=annotation_projects, - class_map=class_map, - description=description - ) - - db.session.add(details) - db.session.commit() - - return jsonify({'message': 'TrainingProjectDetails created', 'details': details.to_dict()}) - - except Exception as error: - db.session.rollback() - return jsonify({'message': 'Failed to create TrainingProjectDetails', 'error': str(error)}), 500 - -@api_bp.route('/training-project-details', methods=['GET']) -def get_training_project_details(): - """Get all TrainingProjectDetails""" - try: - details = TrainingProjectDetails.query.all() - return jsonify([d.to_dict() for d in details]) - - except Exception as error: - return jsonify({'message': 'Failed to fetch TrainingProjectDetails', 'error': str(error)}), 500 - -@api_bp.route('/training-project-details', methods=['PUT']) -def update_training_project_details(): - """Update class_map and description in TrainingProjectDetails""" - try: - data = request.get_json() - project_id = data.get('project_id') - class_map = data.get('class_map') - description = data.get('description') - - if not project_id or not class_map or not description: - return jsonify({'message': 'Missing required fields'}), 400 - - details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() - - if not details: - return jsonify({'message': 'TrainingProjectDetails not found'}), 404 - - details.class_map = class_map - details.description = description - db.session.commit() - - return jsonify({'message': 'Class map and description updated', 'details': details.to_dict()}) - - except Exception as error: - db.session.rollback() - return jsonify({'message': 'Failed to update class map or description', 'error': str(error)}), 500 - -@api_bp.route('/yolox-settings', methods=['POST']) -def yolox_settings(): - """Receive YOLOX settings and save to DB""" - try: - settings = request.form.to_dict() - - print('--- YOLOX settings received ---') - print('settings:', settings) - - # Map select_model to selected_model if present - if 'select_model' in settings and 'selected_model' not in settings: - settings['selected_model'] = settings['select_model'] - del settings['select_model'] - - # Lookup or create project_details_id - if not settings.get('project_id') or not settings['project_id'].isdigit(): - raise ValueError('Missing or invalid project_id in request') - - project_id = int(settings['project_id']) - details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() - - if not details: - details = TrainingProjectDetails( - project_id=project_id, - annotation_projects=[], - class_map=None, - description=None - ) - db.session.add(details) - db.session.commit() - - settings['project_details_id'] = details.id - - # Map 'act' to 'activation' - if 'act' in settings: - settings['activation'] = settings['act'] - del settings['act'] - - # Type conversions - numeric_fields = [ - 'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', - 'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum', - 'print_interval', 'eval_interval', 'test_conf', 'nmsthre', - 'multiscale_range', 'degrees', 'translate', 'shear', - 'train', 'valid', 'test' - ] - - for field in numeric_fields: - if field in settings: - settings[field] = float(settings[field]) - - # Boolean conversions - boolean_fields = ['ema', 'enable_mixup', 'save_history_ckpt'] - for field in boolean_fields: - if field in settings: - if isinstance(settings[field], str): - settings[field] = settings[field].lower() == 'true' - else: - settings[field] = bool(settings[field]) - - # Array conversions - array_fields = ['mosaic_scale', 'mixup_scale', 'scale'] - for field in array_fields: - if field in settings and isinstance(settings[field], str): - settings[field] = [float(x.strip()) for x in settings[field].split(',') if x.strip()] - - # Trim string fields - for key in settings: - if isinstance(settings[key], str): - settings[key] = settings[key].strip() - - # Default for transfer_learning - if 'transfer_learning' not in settings: - settings['transfer_learning'] = False - - # Convert empty seed to None - if 'seed' in settings and (settings['seed'] == '' or settings['seed'] is None): - settings['seed'] = None - - # Validate required fields - required_fields = [ - 'project_details_id', 'exp_name', 'max_epoch', 'depth', 'width', - 'activation', 'train', 'valid', 'test', 'selected_model', 'transfer_learning' - ] - - for field in required_fields: - if field not in settings or settings[field] in [None, '']: - raise ValueError(f'Missing required field: {field}') - - print('Received YOLOX settings:', settings) - - # Handle uploaded model file - if 'ckpt_upload' in request.files: - file = request.files['ckpt_upload'] - upload_dir = os.path.join(os.path.dirname(__file__), '..', 'uploads') - os.makedirs(upload_dir, exist_ok=True) - filename = file.filename or f'uploaded_model_{project_id}.pth' - file_path = os.path.join(upload_dir, filename) - file.save(file_path) - settings['model_upload'] = file_path - - # Save to DB - from services.push_yolox_exp import push_yolox_exp_to_db - training = push_yolox_exp_to_db(settings) - - return jsonify({'message': 'YOLOX settings saved to DB', 'training': training.to_dict()}) - - except Exception as error: - print(f'Error in /api/yolox-settings: {error}') - db.session.rollback() - return jsonify({'message': 'Failed to save YOLOX settings', 'error': str(error)}), 500 - -@api_bp.route('/yolox-settings/upload', methods=['POST']) -def yolox_settings_upload(): - """Upload binary model file""" - try: - project_id = request.args.get('project_id') - if not project_id: - return jsonify({'message': 'Missing project_id in query'}), 400 - - # Save file to disk - upload_dir = os.path.join(os.path.dirname(__file__), '..', 'uploads') - os.makedirs(upload_dir, exist_ok=True) - - filename = request.headers.get('x-upload-filename', f'uploaded_model_{project_id}.pth') - file_path = os.path.join(upload_dir, filename) - - # Read binary data - with open(file_path, 'wb') as f: - f.write(request.data) - - # Update latest training row - details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() - if not details: - return jsonify({'message': 'No TrainingProjectDetails found for project_id'}), 404 - - training = Training.query.filter_by(project_details_id=details.id).order_by(Training.id.desc()).first() - if not training: - return jsonify({'message': 'No training found for project_id'}), 404 - - training.model_upload = file_path - db.session.commit() - - return jsonify({ - 'message': 'Model file uploaded and saved to disk', - 'filename': filename, - 'trainingId': training.id - }) - - except Exception as error: - print(f'Error in /api/yolox-settings/upload: {error}') - db.session.rollback() - return jsonify({'message': 'Failed to upload model file', 'error': str(error)}), 500 - -@api_bp.route('/trainings', methods=['GET']) -def get_trainings(): - """Get all trainings (optionally filtered by project_id)""" - try: - project_id = request.args.get('project_id') - - if project_id: - # Find all details rows for this project - details_rows = TrainingProjectDetails.query.filter_by(project_id=project_id).all() - if not details_rows: - return jsonify([]) - - # Get all trainings linked to any details row for this project - details_ids = [d.id for d in details_rows] - trainings = Training.query.filter(Training.project_details_id.in_(details_ids)).all() - return jsonify([t.to_dict() for t in trainings]) - else: - # Return all trainings - trainings = Training.query.all() - return jsonify([t.to_dict() for t in trainings]) - - except Exception as error: - return jsonify({'message': 'Failed to fetch trainings', 'error': str(error)}), 500 - -@api_bp.route('/trainings/', methods=['DELETE']) -def delete_training(id): - """Delete a training by id""" - try: - training = Training.query.get(id) - if training: - db.session.delete(training) - db.session.commit() - return jsonify({'message': 'Training deleted'}) - else: - return jsonify({'message': 'Training not found'}), 404 - - except Exception as error: - db.session.rollback() - return jsonify({'message': 'Failed to delete training', 'error': str(error)}), 500 - -@api_bp.route('/training-projects/', methods=['DELETE']) -def delete_training_project(id): - """Delete a training project and all related entries""" - try: - # Find details rows for this project - details_rows = TrainingProjectDetails.query.filter_by(project_id=id).all() - details_ids = [d.id for d in details_rows] - - # Delete all trainings linked to these details - if details_ids: - Training.query.filter(Training.project_details_id.in_(details_ids)).delete(synchronize_session=False) - TrainingProjectDetails.query.filter_by(project_id=id).delete() - - # Delete the project itself - project = TrainingProject.query.get(id) - if project: - db.session.delete(project) - db.session.commit() - return jsonify({'message': 'Training project and all related entries deleted'}) - else: - return jsonify({'message': 'Training project not found'}), 404 - - except Exception as error: - db.session.rollback() - return jsonify({'message': 'Failed to delete training project', 'error': str(error)}), 500 - -@api_bp.route('/base-config/', methods=['GET']) -def get_base_config(model_name): - """Get base configuration for a specific YOLOX model""" - try: - from services.generate_yolox_exp import load_base_config - config = load_base_config(model_name) - return jsonify(config) - except Exception as error: - return jsonify({'message': f'Failed to load base config for {model_name}', 'error': str(error)}), 404 +from flask import Blueprint, request, jsonify, send_file +from werkzeug.utils import secure_filename +import os +import json +import subprocess +from database.database import db +from models.TrainingProject import TrainingProject +from models.TrainingProjectDetails import TrainingProjectDetails +from models.training import Training +from models.LabelStudioProject import LabelStudioProject +from models.Images import Image +from models.Annotation import Annotation + +api_bp = Blueprint('api', __name__) + +# Global update status (similar to Node.js version) +update_status = {"running": False} + +@api_bp.route('/seed', methods=['GET']) +def seed(): + """Trigger seeding from Label Studio""" + from services.seed_label_studio import seed_label_studio + result = seed_label_studio() + return jsonify(result) + +@api_bp.route('/generate-yolox-json', methods=['POST']) +def generate_yolox_json(): + """Generate YOLOX JSON and exp.py for a project""" + try: + data = request.get_json() + project_id = data.get('project_id') + + if not project_id: + return jsonify({'message': 'Missing project_id in request body'}), 400 + + # Find all TrainingProjectDetails for this project + details_rows = TrainingProjectDetails.query.filter_by(project_id=project_id).all() + + if not details_rows: + return jsonify({'message': f'No TrainingProjectDetails found for project {project_id}'}), 404 + + # Get project name + training_project = TrainingProject.query.get(project_id) + project_name = training_project.title.replace(' ', '_') if training_project.title else f'project_{project_id}' + + from services.generate_json_yolox import generate_training_json + from services.generate_yolox_exp import save_yolox_exp + + # For each details row, generate coco.jsons and exp.py + for details in details_rows: + details_id = details.id + generate_training_json(details_id) + + # Find all trainings for this details row + trainings = Training.query.filter_by(project_details_id=details_id).all() + if not trainings: + continue + + # Create output directory + out_dir = os.path.join(os.path.dirname(__file__), '..', project_name, str(details_id)) + os.makedirs(out_dir, exist_ok=True) + + # Save exp.py for each training + for training in trainings: + exp_file_path = os.path.join(out_dir, 'exp.py') + save_yolox_exp(training.id, exp_file_path) + + return jsonify({'message': f'YOLOX JSON and exp.py generated for project {project_id}'}) + + except Exception as err: + print(f'Error generating YOLOX JSON: {err}') + return jsonify({'message': 'Failed to generate YOLOX JSON', 'error': str(err)}), 500 + +@api_bp.route('/start-yolox-training', methods=['POST']) +def start_yolox_training(): + """Generate JSONs, exp.py, and start YOLOX training""" + try: + data = request.get_json() + project_id = data.get('project_id') + training_id = data.get('training_id') + + if not project_id or not training_id: + return jsonify({'message': 'Missing project_id or training_id'}), 400 + + # Get training record + training = Training.query.get(training_id) + if not training: + return jsonify({'message': f'Training {training_id} not found'}), 404 + + details_id = training.project_details_id + + # Step 1: Generate COCO JSON files + from services.generate_json_yolox import generate_training_json + print(f'Generating COCO JSON for training {training_id}...') + generate_training_json(details_id) + + # Step 2: Generate exp.py + from services.generate_yolox_exp import save_yolox_exp + from services.settings_service import get_setting + + training_project = TrainingProject.query.get(project_id) + project_name = training_project.title.replace(' ', '_') if training_project and training_project.title else f'project_{project_id}' + + # Use training name + id for folder to support multiple trainings per project + training_folder_name = f"{training.exp_name or training.training_name or 'training'}_{training_id}" + training_folder_name = training_folder_name.replace(' ', '_') + + output_base_path = get_setting('yolox_output_path', './backend') + out_dir = os.path.join(output_base_path, project_name, training_folder_name) + os.makedirs(out_dir, exist_ok=True) + + exp_file_path = os.path.join(out_dir, 'exp.py') + print(f'Generating exp.py at {exp_file_path}...') + save_yolox_exp(training_id, exp_file_path) + + # Step 3: Start training + print(f'Starting YOLOX training for training {training_id}...') + + # Get YOLOX configuration from settings + yolox_main_dir = get_setting('yolox_path', '/home/kitraining/Yolox/YOLOX-main') + yolox_venv = get_setting('yolox_venv_path', '/home/kitraining/Yolox/yolox_venv/bin/activate') + + # Detect platform and build appropriate command + import platform + is_windows = platform.system() == 'Windows' + + # Determine model argument + model_arg = '' + + if (training.transfer_learning and + isinstance(training.transfer_learning, str) and + training.transfer_learning.lower() == 'coco'): + model_arg = f'-c {yolox_main_dir}/pretrained/{training.selected_model}.pth' + elif (training.selected_model and + training.selected_model.lower() == 'coco' and + (not training.transfer_learning or training.transfer_learning == False)): + model_arg = f'-c {yolox_main_dir}/pretrained/{training.selected_model}.pth' + + # Build base training arguments + train_args = f'-f {exp_file_path} -d 1 -b 8 --fp16 --cache' + if model_arg: + train_args += f' {model_arg} -o' + + # Build platform-specific command + if is_windows: + # Windows: Use call to activate venv, then run python + # If venv path doesn't end with .bat, assume it needs Scripts\activate.bat + if not yolox_venv.endswith('.bat'): + venv_activate = os.path.join(yolox_venv, 'Scripts', 'activate.bat') + else: + venv_activate = yolox_venv + cmd = f'cmd /c ""{venv_activate}" && python tools\\train.py {train_args}"' + else: + # Linux: Use bash with source + # If venv path doesn't end with 'activate', assume it needs bin/activate + if not yolox_venv.endswith('activate'): + venv_activate = os.path.join(yolox_venv, 'bin', 'activate') + else: + venv_activate = yolox_venv + cmd = f'bash -c "source {venv_activate} && python tools/train.py {train_args}"' + + print(f'Training command: {cmd}') + + # Start training in background + subprocess.Popen(cmd, shell=True, cwd=yolox_main_dir) + + return jsonify({ + 'message': f'JSONs and exp.py generated, training started for training {training_id}', + 'exp_path': exp_file_path + }) + + except Exception as err: + print(f'Error starting YOLOX training: {err}') + import traceback + traceback.print_exc() + return jsonify({'message': 'Failed to start training', 'error': str(err)}), 500 + +@api_bp.route('/training-log', methods=['GET']) +def training_log(): + """Get YOLOX training log""" + try: + project_id = request.args.get('project_id') + training_id = request.args.get('training_id') + + training_project = TrainingProject.query.get(project_id) + project_name = training_project.title.replace(' ', '_') if training_project.title else f'project_{project_id}' + + out_dir = os.path.join(os.path.dirname(__file__), '..', project_name, str(training_id)) + log_path = os.path.join(out_dir, 'training.log') + + if not os.path.exists(log_path): + return jsonify({'error': 'Log not found'}), 404 + + with open(log_path, 'r') as f: + log_data = f.read() + + return jsonify({'log': log_data}) + + except Exception as err: + return jsonify({'error': 'Failed to fetch log', 'details': str(err)}), 500 + +@api_bp.route('/training-projects', methods=['POST']) +def create_training_project(): + """Create a new training project""" + try: + from models.ProjectClass import ProjectClass + + title = request.form.get('title') + description = request.form.get('description') + classes = json.loads(request.form.get('classes', '[]')) + + project_image = None + project_image_type = None + + if 'project_image' in request.files: + file = request.files['project_image'] + project_image = file.read() + project_image_type = file.content_type + + # Create project without classes field + project = TrainingProject( + title=title, + description=description, + project_image=project_image, + project_image_type=project_image_type + ) + + db.session.add(project) + db.session.flush() # Get project_id before commit + + # Add classes to ProjectClass table + for index, class_name in enumerate(classes): + project_class = ProjectClass( + project_id=project.project_id, + class_name=class_name, + display_order=index + ) + db.session.add(project_class) + + db.session.commit() + + return jsonify({'message': 'Project created!'}) + + except Exception as error: + print(f'Error creating project: {error}') + db.session.rollback() + return jsonify({'message': 'Failed to create project', 'error': str(error)}), 500 + +@api_bp.route('/training-projects', methods=['GET']) +def get_training_projects(): + """Get all training projects""" + try: + projects = TrainingProject.query.all() + serialized = [project.to_dict() for project in projects] + return jsonify(serialized) + + except Exception as error: + return jsonify({'message': 'Failed to fetch projects', 'error': str(error)}), 500 + +@api_bp.route('/update-status', methods=['GET']) +def get_update_status(): + """Get update status""" + return jsonify(update_status) + +@api_bp.route('/label-studio-projects', methods=['GET']) +def get_label_studio_projects(): + """Get all Label Studio projects with annotation counts""" + try: + from sqlalchemy import func + + # Get all projects + label_studio_projects = LabelStudioProject.query.all() + + # Get annotation counts in one query using SQL aggregation + annotation_counts_query = db.session.query( + Image.project_id, + Annotation.Label, + func.count(Annotation.annotation_id).label('count') + ).join( + Annotation, Image.image_id == Annotation.image_id + ).group_by( + Image.project_id, Annotation.Label + ).all() + + # Organize counts by project_id + counts_by_project = {} + for project_id, label, count in annotation_counts_query: + if project_id not in counts_by_project: + counts_by_project[project_id] = {} + counts_by_project[project_id][label] = count + + # Build result + projects_with_counts = [] + for project in label_studio_projects: + project_dict = project.to_dict() + project_dict['annotationCounts'] = counts_by_project.get(project.project_id, {}) + projects_with_counts.append(project_dict) + + return jsonify(projects_with_counts) + + except Exception as error: + return jsonify({'message': 'Failed to fetch projects', 'error': str(error)}), 500 + +@api_bp.route('/training-project-details', methods=['POST']) +def create_training_project_details(): + """Create TrainingProjectDetails""" + try: + from models.AnnotationProjectMapping import AnnotationProjectMapping + from models.ClassMapping import ClassMapping + + data = request.get_json() + project_id = data.get('project_id') + annotation_projects = data.get('annotation_projects') # Array of project IDs + class_map = data.get('class_map') # Dict: {source: target} + description = data.get('description') + + if not project_id or annotation_projects is None: + return jsonify({'message': 'Missing required fields'}), 400 + + # Create TrainingProjectDetails without JSON fields + details = TrainingProjectDetails( + project_id=project_id, + description_text=description + ) + + db.session.add(details) + db.session.flush() # Get details.id + + # Add annotation project mappings + for ls_project_id in annotation_projects: + mapping = AnnotationProjectMapping( + project_details_id=details.id, + label_studio_project_id=ls_project_id + ) + db.session.add(mapping) + + # Add class mappings if provided + if class_map: + for source_class, target_class in class_map.items(): + # For initial creation, we don't have per-project mappings yet + # Will be replaced when user sets up mappings in UI + mapping = ClassMapping( + project_details_id=details.id, + label_studio_project_id=annotation_projects[0] if annotation_projects else 0, + source_class=source_class, + target_class=target_class + ) + db.session.add(mapping) + + db.session.commit() + db.session.commit() + + return jsonify({'message': 'TrainingProjectDetails created', 'details': details.to_dict()}) + + except Exception as error: + db.session.rollback() + return jsonify({'message': 'Failed to create TrainingProjectDetails', 'error': str(error)}), 500 + +@api_bp.route('/training-project-details', methods=['GET']) +def get_training_project_details(): + """Get all TrainingProjectDetails""" + try: + details = TrainingProjectDetails.query.all() + result = [] + for d in details: + try: + result.append(d.to_dict()) + except Exception as e: + print(f'Error serializing detail {d.id}: {e}') + # Return basic info if full serialization fails + result.append({ + 'id': d.id, + 'project_id': d.project_id, + 'description': d.description_text, + 'annotation_projects': [], + 'class_map': {} + }) + return jsonify(result) + + except Exception as error: + print(f'Error fetching training project details: {error}') + return jsonify({'message': 'Failed to fetch TrainingProjectDetails', 'error': str(error)}), 500 + +@api_bp.route('/training-project-details', methods=['PUT']) +def update_training_project_details(): + """Update class_map and description in TrainingProjectDetails""" + try: + from models.ClassMapping import ClassMapping + + data = request.get_json() + print(f'[DEBUG] Received PUT data: {data}') + + project_id = data.get('project_id') + class_map_data = data.get('class_map') # Array: [[labelStudioProjectId, [[class, target], ...]], ...] + description_data = data.get('description') # Array: [[projectId, desc], ...] + + print(f'[DEBUG] project_id: {project_id}') + print(f'[DEBUG] class_map_data: {class_map_data}') + print(f'[DEBUG] description_data: {description_data}') + + if not project_id or class_map_data is None or description_data is None: + return jsonify({'message': 'Missing required fields'}), 400 + + details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() + + if not details: + return jsonify({'message': 'TrainingProjectDetails not found'}), 404 + + # Update description - combine all descriptions + combined_description = '\n\n'.join([desc[1] for desc in description_data if len(desc) > 1 and desc[1]]) + details.description_text = combined_description + + # Delete existing class mappings + ClassMapping.query.filter_by(project_details_id=details.id).delete() + + # Add new class mappings - iterate through all label studio projects + # class_map_data format: [[labelStudioProjectId, [[class, target], ...]], ...] + for project_mapping in class_map_data: + if len(project_mapping) >= 2: + label_studio_project_id = project_mapping[0] + class_mappings = project_mapping[1] # [[class1, target1], [class2, target2], ...] + + for class_pair in class_mappings: + if len(class_pair) >= 2: + source_class = class_pair[0] + target_class = class_pair[1] + + # Create mapping with label_studio_project_id + mapping = ClassMapping( + project_details_id=details.id, + label_studio_project_id=label_studio_project_id, + source_class=source_class, + target_class=target_class + ) + db.session.add(mapping) + + db.session.commit() + + return jsonify({'message': 'Class map and description updated', 'details': details.to_dict()}) + + except Exception as error: + db.session.rollback() + print(f'[ERROR] Failed to update training project details: {error}') + import traceback + traceback.print_exc() + return jsonify({'message': 'Failed to update class map or description', 'error': str(error)}), 500 + +@api_bp.route('/yolox-settings', methods=['POST']) +def yolox_settings(): + """Receive YOLOX settings and save to DB""" + try: + settings = request.form.to_dict() + + print('--- YOLOX settings received ---') + print('settings:', settings) + + # Map select_model to selected_model if present + if 'select_model' in settings and 'selected_model' not in settings: + settings['selected_model'] = settings['select_model'] + del settings['select_model'] + + # Lookup or create project_details_id + if not settings.get('project_id') or not settings['project_id'].isdigit(): + raise ValueError('Missing or invalid project_id in request') + + project_id = int(settings['project_id']) + details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() + + if not details: + # Create TrainingProjectDetails without JSON fields + details = TrainingProjectDetails( + project_id=project_id, + description_text=None + ) + db.session.add(details) + db.session.flush() # Get details.id + + settings['project_details_id'] = details.id + + # Map 'act' to 'activation' + if 'act' in settings: + settings['activation'] = settings['act'] + del settings['act'] + + # Type conversions + numeric_fields = [ + 'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', + 'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum', + 'print_interval', 'eval_interval', 'test_conf', 'nmsthre', + 'multiscale_range', 'degrees', 'translate', 'shear', + 'train', 'valid', 'test' + ] + + for field in numeric_fields: + if field in settings: + settings[field] = float(settings[field]) + + # Boolean conversions + boolean_fields = ['ema', 'enable_mixup', 'save_history_ckpt'] + for field in boolean_fields: + if field in settings: + if isinstance(settings[field], str): + settings[field] = settings[field].lower() == 'true' + else: + settings[field] = bool(settings[field]) + + # Array conversions + array_fields = ['mosaic_scale', 'mixup_scale', 'scale'] + for field in array_fields: + if field in settings and isinstance(settings[field], str): + settings[field] = [float(x.strip()) for x in settings[field].split(',') if x.strip()] + + # Trim string fields + for key in settings: + if isinstance(settings[key], str): + settings[key] = settings[key].strip() + + # Default for transfer_learning + if 'transfer_learning' not in settings: + settings['transfer_learning'] = False + + # Convert empty seed to None + if 'seed' in settings and (settings['seed'] == '' or settings['seed'] is None): + settings['seed'] = None + + # Validate required fields + required_fields = [ + 'project_details_id', 'exp_name', 'max_epoch', 'depth', 'width', + 'activation', 'train', 'valid', 'test', 'selected_model', 'transfer_learning' + ] + + for field in required_fields: + if field not in settings or settings[field] in [None, '']: + raise ValueError(f'Missing required field: {field}') + + print('Received YOLOX settings:', settings) + + # Handle uploaded model file + if 'ckpt_upload' in request.files: + file = request.files['ckpt_upload'] + upload_dir = os.path.join(os.path.dirname(__file__), '..', 'uploads') + os.makedirs(upload_dir, exist_ok=True) + filename = file.filename or f'uploaded_model_{project_id}.pth' + file_path = os.path.join(upload_dir, filename) + file.save(file_path) + settings['model_upload'] = file_path + + # Save to DB + from services.push_yolox_exp import push_yolox_exp_to_db + training = push_yolox_exp_to_db(settings) + + return jsonify({'message': 'YOLOX settings saved to DB', 'training': training.to_dict()}) + + except Exception as error: + print(f'Error in /api/yolox-settings: {error}') + db.session.rollback() + return jsonify({'message': 'Failed to save YOLOX settings', 'error': str(error)}), 500 + +@api_bp.route('/yolox-settings/upload', methods=['POST']) +def yolox_settings_upload(): + """Upload binary model file""" + try: + project_id = request.args.get('project_id') + if not project_id: + return jsonify({'message': 'Missing project_id in query'}), 400 + + # Save file to disk + upload_dir = os.path.join(os.path.dirname(__file__), '..', 'uploads') + os.makedirs(upload_dir, exist_ok=True) + + filename = request.headers.get('x-upload-filename', f'uploaded_model_{project_id}.pth') + file_path = os.path.join(upload_dir, filename) + + # Read binary data + with open(file_path, 'wb') as f: + f.write(request.data) + + # Update latest training row + details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() + if not details: + return jsonify({'message': 'No TrainingProjectDetails found for project_id'}), 404 + + training = Training.query.filter_by(project_details_id=details.id).order_by(Training.id.desc()).first() + if not training: + return jsonify({'message': 'No training found for project_id'}), 404 + + training.model_upload = file_path + db.session.commit() + + return jsonify({ + 'message': 'Model file uploaded and saved to disk', + 'filename': filename, + 'trainingId': training.id + }) + + except Exception as error: + print(f'Error in /api/yolox-settings/upload: {error}') + db.session.rollback() + return jsonify({'message': 'Failed to upload model file', 'error': str(error)}), 500 + +@api_bp.route('/trainings', methods=['GET']) +def get_trainings(): + """Get all trainings (optionally filtered by project_id)""" + try: + project_id = request.args.get('project_id') + + if project_id: + # Find all details rows for this project + details_rows = TrainingProjectDetails.query.filter_by(project_id=project_id).all() + if not details_rows: + return jsonify([]) + + # Get all trainings linked to any details row for this project + details_ids = [d.id for d in details_rows] + trainings = Training.query.filter(Training.project_details_id.in_(details_ids)).all() + return jsonify([t.to_dict() for t in trainings]) + else: + # Return all trainings + trainings = Training.query.all() + return jsonify([t.to_dict() for t in trainings]) + + except Exception as error: + return jsonify({'message': 'Failed to fetch trainings', 'error': str(error)}), 500 + +@api_bp.route('/trainings/', methods=['DELETE']) +def delete_training(id): + """Delete a training by id""" + try: + training = Training.query.get(id) + if training: + db.session.delete(training) + db.session.commit() + return jsonify({'message': 'Training deleted'}) + else: + return jsonify({'message': 'Training not found'}), 404 + + except Exception as error: + db.session.rollback() + return jsonify({'message': 'Failed to delete training', 'error': str(error)}), 500 + +@api_bp.route('/training-projects/', methods=['DELETE']) +def delete_training_project(id): + """Delete a training project and all related entries""" + try: + # Find details rows for this project + details_rows = TrainingProjectDetails.query.filter_by(project_id=id).all() + details_ids = [d.id for d in details_rows] + + # Delete all trainings linked to these details + if details_ids: + Training.query.filter(Training.project_details_id.in_(details_ids)).delete(synchronize_session=False) + TrainingProjectDetails.query.filter_by(project_id=id).delete() + + # Delete the project itself + project = TrainingProject.query.get(id) + if project: + db.session.delete(project) + db.session.commit() + return jsonify({'message': 'Training project and all related entries deleted'}) + else: + return jsonify({'message': 'Training project not found'}), 404 + + except Exception as error: + db.session.rollback() + return jsonify({'message': 'Failed to delete training project', 'error': str(error)}), 500 + +@api_bp.route('/base-config/', methods=['GET']) +def get_base_config(model_name): + """Get base configuration for a specific YOLOX model""" + try: + from services.generate_yolox_exp import load_base_config + config = load_base_config(model_name) + return jsonify(config) + except Exception as error: + return jsonify({'message': f'Failed to load base config for {model_name}', 'error': str(error)}), 404 + +# Settings endpoints +@api_bp.route('/settings', methods=['GET']) +def get_settings(): + """Get all settings""" + from services.settings_service import get_all_settings_detailed + settings = get_all_settings_detailed() + return jsonify(settings) + +@api_bp.route('/settings/', methods=['GET']) +def get_setting(key): + """Get a specific setting""" + from services.settings_service import get_setting as get_setting_value + from models.Settings import Settings + + setting = Settings.query.filter_by(key=key).first() + if setting: + return jsonify(setting.to_dict()) + else: + return jsonify({'message': f'Setting {key} not found'}), 404 + +@api_bp.route('/settings', methods=['POST']) +def update_settings(): + """Update multiple settings""" + try: + data = request.get_json() + from services.settings_service import set_setting + + for key, value in data.items(): + set_setting(key, value) + + return jsonify({'message': 'Settings updated successfully'}) + except Exception as error: + return jsonify({'message': 'Failed to update settings', 'error': str(error)}), 500 + +@api_bp.route('/settings/', methods=['PUT']) +def update_setting(key): + """Update a specific setting""" + try: + data = request.get_json() + value = data.get('value') + description = data.get('description') + + from services.settings_service import set_setting + setting = set_setting(key, value, description) + + return jsonify(setting.to_dict()) + except Exception as error: + return jsonify({'message': f'Failed to update setting {key}', 'error': str(error)}), 500 + +@api_bp.route('/settings/test/labelstudio', methods=['POST']) +def test_labelstudio_connection(): + """Test Label Studio connection""" + try: + data = request.get_json() + api_url = data.get('api_url') + api_token = data.get('api_token') + + if not api_url or not api_token: + return jsonify({'success': False, 'message': 'Missing api_url or api_token'}), 400 + + import requests + response = requests.get( + f'{api_url}/projects/', + headers={'Authorization': f'Token {api_token}'}, + timeout=5 + ) + + if response.ok: + projects = response.json() + return jsonify({ + 'success': True, + 'message': f'Connection successful! Found {len(projects.get("results", projects))} projects.' + }) + else: + return jsonify({ + 'success': False, + 'message': f'Connection failed: {response.status_code} {response.reason}' + }), 400 + + except requests.exceptions.Timeout: + return jsonify({'success': False, 'message': 'Connection timeout'}), 400 + except requests.exceptions.ConnectionError: + return jsonify({'success': False, 'message': 'Cannot connect to Label Studio'}), 400 + except Exception as error: + return jsonify({'success': False, 'message': str(error)}), 500 + +@api_bp.route('/settings/test/yolox', methods=['POST']) +def test_yolox_path(): + """Test YOLOX path and venv path validity""" + try: + data = request.get_json() + yolox_path = data.get('yolox_path') + yolox_venv_path = data.get('yolox_venv_path') + + if not yolox_path: + return jsonify({'success': False, 'message': 'Missing yolox_path'}), 400 + + # Check if YOLOX path exists + if not os.path.exists(yolox_path): + return jsonify({'success': False, 'message': 'YOLOX path does not exist'}), 400 + + # Check for key YOLOX files/directories + required_items = ['yolox', 'exps', 'tools'] + found_items = [] + missing_items = [] + + for item in required_items: + item_path = os.path.join(yolox_path, item) + if os.path.exists(item_path): + found_items.append(item) + else: + missing_items.append(item) + + if len(found_items) < 2: # At least 2 out of 3 key items required + return jsonify({ + 'success': False, + 'message': f'Invalid YOLOX path. Missing: {", ".join(missing_items)}', + 'found': found_items, + 'missing': missing_items + }), 400 + + # Check venv path if provided + venv_message = '' + if yolox_venv_path: + venv_valid = False + venv_details = [] + + # Normalize path + venv_path_normalized = os.path.normpath(yolox_venv_path) + + # Check if it's an activation script (Linux/Mac: bin/activate, Windows: Scripts/activate.bat or Scripts/Activate.ps1) + if os.path.isfile(venv_path_normalized): + # Direct path to activation script + if 'activate' in os.path.basename(venv_path_normalized).lower(): + venv_valid = True + venv_details.append(f'Activation script found: {os.path.basename(venv_path_normalized)}') + else: + return jsonify({ + 'success': False, + 'message': 'Venv path points to a file but not an activation script' + }), 400 + elif os.path.isdir(venv_path_normalized): + # Check if it's a venv directory + # Look for activation scripts in common locations + possible_activations = [ + os.path.join(venv_path_normalized, 'bin', 'activate'), # Linux/Mac + os.path.join(venv_path_normalized, 'Scripts', 'activate.bat'), # Windows CMD + os.path.join(venv_path_normalized, 'Scripts', 'Activate.ps1'), # Windows PowerShell + os.path.join(venv_path_normalized, 'Scripts', 'activate'), # Windows Git Bash + ] + + found_activations = [] + for act_path in possible_activations: + if os.path.exists(act_path): + found_activations.append(os.path.basename(act_path)) + venv_valid = True + + if venv_valid: + venv_details.append(f'Venv directory valid. Found: {", ".join(found_activations)}') + else: + return jsonify({ + 'success': False, + 'message': 'Venv directory does not contain activation scripts' + }), 400 + else: + return jsonify({ + 'success': False, + 'message': 'Venv path does not exist' + }), 400 + + venv_message = ' ' + '. '.join(venv_details) + + return jsonify({ + 'success': True, + 'message': f'Valid YOLOX installation found. Found: {", ".join(found_items)}.{venv_message}', + 'found': found_items, + 'missing': missing_items + }) + + except Exception as error: + return jsonify({'success': False, 'message': str(error)}), 500 diff --git a/backend/server.js b/backend/server.js index 2834ed3..4ab6676 100644 --- a/backend/server.js +++ b/backend/server.js @@ -1,34 +1,34 @@ -const express = require('express'); -const cors = require('cors'); -const path = require('path'); -const sequelize = require('./database/database'); - - -const app = express(); -app.use(express.json()); -const port = 3000; - -const apiRouter = require('./routes/api.js'); -app.use('/api', apiRouter); - - -app.use(cors()); -app.use(express.json()); -app.use(express.static(path.join(__dirname, '..'))); - - - -// Initialize DB and start server -(async () => { - try { - await sequelize.authenticate(); - console.log('DB connection established.'); - await sequelize.sync(); // Only if you want Sequelize to ensure schema matches - - app.listen(port, '0.0.0.0', () => - console.log(`Server running at http://0.0.0.0:${port}`) - ); - } catch (err) { - console.error('Failed to start:', err); - } -})(); +const express = require('express'); +const cors = require('cors'); +const path = require('path'); +const sequelize = require('./database/database'); + + +const app = express(); +app.use(express.json()); +const port = 3000; + +const apiRouter = require('./routes/api.js'); +app.use('/api', apiRouter); + + +app.use(cors()); +app.use(express.json()); +app.use(express.static(path.join(__dirname, '..'))); + + + +// Initialize DB and start server +(async () => { + try { + await sequelize.authenticate(); + console.log('DB connection established.'); + await sequelize.sync(); // Only if you want Sequelize to ensure schema matches + + app.listen(port, '0.0.0.0', () => + console.log(`Server running at http://0.0.0.0:${port}`) + ); + } catch (err) { + console.error('Failed to start:', err); + } +})(); diff --git a/backend/services/__init__.py b/backend/services/__init__.py index 0557eb6..c7f87b7 100644 --- a/backend/services/__init__.py +++ b/backend/services/__init__.py @@ -1 +1 @@ -# Services module +# Services module diff --git a/backend/services/fetch-labelstudio.js b/backend/services/fetch-labelstudio.js index 2e8bf6c..a24a4e5 100644 --- a/backend/services/fetch-labelstudio.js +++ b/backend/services/fetch-labelstudio.js @@ -1,92 +1,92 @@ -const API_URL = 'http://192.168.1.19:8080/api'; -const API_TOKEN = 'c1cef980b7c73004f4ee880a42839313b863869f'; - - - - - - -const fetch = require('node-fetch'); - -async function fetchLableStudioProject(projectid) { - // 1. Trigger export - const exportUrl = `${API_URL}/projects/${projectid}/export?exportType=JSON_MIN`; - const headers = { Authorization: `Token ${API_TOKEN}` }; - let res = await fetch(exportUrl, { headers }); - if (!res.ok) { - let errorText = await res.text().catch(() => ''); - console.error(`Failed to trigger export: ${res.status} ${res.statusText} - ${errorText}`); - throw new Error(`Failed to trigger export: ${res.status} ${res.statusText}`); - } - let data = await res.json(); - // If data is an array, it's ready - if (Array.isArray(data)) return data; - // If not, poll for the export file - let fileUrl = data.download_url || data.url || null; - let tries = 0; - while (!fileUrl && tries < 20) { - await new Promise(r => setTimeout(r, 2000)); - res = await fetch(exportUrl, { headers }); - if (!res.ok) { - let errorText = await res.text().catch(() => ''); - console.error(`Failed to poll export: ${res.status} ${res.statusText} - ${errorText}`); - throw new Error(`Failed to poll export: ${res.status} ${res.statusText}`); - } - data = await res.json(); - fileUrl = data.download_url || data.url || null; - tries++; - } - if (!fileUrl) throw new Error('Label Studio export did not become ready'); - // 2. Download the export file - res = await fetch(fileUrl.startsWith('http') ? fileUrl : `${API_URL.replace('/api','')}${fileUrl}`, { headers }); - if (!res.ok) { - let errorText = await res.text().catch(() => ''); - console.error(`Failed to download export: ${res.status} ${res.statusText} - ${errorText}`); - throw new Error(`Failed to download export: ${res.status} ${res.statusText}`); - } - return await res.json(); -} - - - -async function fetchProjectIdsAndTitles() { - try { - const response = await fetch(`${API_URL}/projects/`, { - headers: { - 'Authorization': `Token ${API_TOKEN}`, - 'Content-Type': 'application/json' - } - }); - - if (!response.ok) { - let errorText = await response.text().catch(() => ''); - console.error(`Failed to fetch projects: ${response.status} ${response.statusText} - ${errorText}`); - throw new Error(`HTTP error! status: ${response.status}`); - } - - const data = await response.json(); - - if (!data.results || !Array.isArray(data.results)) { - throw new Error('API response does not contain results array'); - } - - // Extract id and title from each project - const projects = data.results.map(project => ({ - id: project.id, - title: project.title - })); - console.log(projects) - return projects; - - } catch (error) { - console.error('Failed to fetch projects:', error); - return []; - } -} - -module.exports = { fetchLableStudioProject, fetchProjectIdsAndTitles }; - - - -//getLableStudioProject(20) -//fetchProjectIdsAndTitles() +const API_URL = 'http://192.168.1.19:8080/api'; +const API_TOKEN = 'c1cef980b7c73004f4ee880a42839313b863869f'; + + + + + + +const fetch = require('node-fetch'); + +async function fetchLableStudioProject(projectid) { + // 1. Trigger export + const exportUrl = `${API_URL}/projects/${projectid}/export?exportType=JSON_MIN`; + const headers = { Authorization: `Token ${API_TOKEN}` }; + let res = await fetch(exportUrl, { headers }); + if (!res.ok) { + let errorText = await res.text().catch(() => ''); + console.error(`Failed to trigger export: ${res.status} ${res.statusText} - ${errorText}`); + throw new Error(`Failed to trigger export: ${res.status} ${res.statusText}`); + } + let data = await res.json(); + // If data is an array, it's ready + if (Array.isArray(data)) return data; + // If not, poll for the export file + let fileUrl = data.download_url || data.url || null; + let tries = 0; + while (!fileUrl && tries < 20) { + await new Promise(r => setTimeout(r, 2000)); + res = await fetch(exportUrl, { headers }); + if (!res.ok) { + let errorText = await res.text().catch(() => ''); + console.error(`Failed to poll export: ${res.status} ${res.statusText} - ${errorText}`); + throw new Error(`Failed to poll export: ${res.status} ${res.statusText}`); + } + data = await res.json(); + fileUrl = data.download_url || data.url || null; + tries++; + } + if (!fileUrl) throw new Error('Label Studio export did not become ready'); + // 2. Download the export file + res = await fetch(fileUrl.startsWith('http') ? fileUrl : `${API_URL.replace('/api','')}${fileUrl}`, { headers }); + if (!res.ok) { + let errorText = await res.text().catch(() => ''); + console.error(`Failed to download export: ${res.status} ${res.statusText} - ${errorText}`); + throw new Error(`Failed to download export: ${res.status} ${res.statusText}`); + } + return await res.json(); +} + + + +async function fetchProjectIdsAndTitles() { + try { + const response = await fetch(`${API_URL}/projects/`, { + headers: { + 'Authorization': `Token ${API_TOKEN}`, + 'Content-Type': 'application/json' + } + }); + + if (!response.ok) { + let errorText = await response.text().catch(() => ''); + console.error(`Failed to fetch projects: ${response.status} ${response.statusText} - ${errorText}`); + throw new Error(`HTTP error! status: ${response.status}`); + } + + const data = await response.json(); + + if (!data.results || !Array.isArray(data.results)) { + throw new Error('API response does not contain results array'); + } + + // Extract id and title from each project + const projects = data.results.map(project => ({ + id: project.id, + title: project.title + })); + console.log(projects) + return projects; + + } catch (error) { + console.error('Failed to fetch projects:', error); + return []; + } +} + +module.exports = { fetchLableStudioProject, fetchProjectIdsAndTitles }; + + + +//getLableStudioProject(20) +//fetchProjectIdsAndTitles() diff --git a/backend/services/fetch_labelstudio.py b/backend/services/fetch_labelstudio.py index 710b070..2f1fa72 100644 --- a/backend/services/fetch_labelstudio.py +++ b/backend/services/fetch_labelstudio.py @@ -1,85 +1,93 @@ -import requests -import time - -API_URL = 'http://192.168.1.19:8080/api' -API_TOKEN = 'c1cef980b7c73004f4ee880a42839313b863869f' - -def fetch_label_studio_project(project_id): - """Fetch Label Studio project annotations""" - export_url = f'{API_URL}/projects/{project_id}/export?exportType=JSON_MIN' - headers = {'Authorization': f'Token {API_TOKEN}'} - - # Trigger export - res = requests.get(export_url, headers=headers) - if not res.ok: - error_text = res.text if res.text else '' - print(f'Failed to trigger export: {res.status_code} {res.reason} - {error_text}') - raise Exception(f'Failed to trigger export: {res.status_code} {res.reason}') - - data = res.json() - - # If data is an array, it's ready - if isinstance(data, list): - return data - - # If not, poll for the export file - file_url = data.get('download_url') or data.get('url') - tries = 0 - - while not file_url and tries < 20: - time.sleep(2) - res = requests.get(export_url, headers=headers) - if not res.ok: - error_text = res.text if res.text else '' - print(f'Failed to poll export: {res.status_code} {res.reason} - {error_text}') - raise Exception(f'Failed to poll export: {res.status_code} {res.reason}') - - data = res.json() - file_url = data.get('download_url') or data.get('url') - tries += 1 - - if not file_url: - raise Exception('Label Studio export did not become ready') - - # Download the export file - full_url = file_url if file_url.startswith('http') else f"{API_URL.replace('/api', '')}{file_url}" - res = requests.get(full_url, headers=headers) - if not res.ok: - error_text = res.text if res.text else '' - print(f'Failed to download export: {res.status_code} {res.reason} - {error_text}') - raise Exception(f'Failed to download export: {res.status_code} {res.reason}') - - return res.json() - -def fetch_project_ids_and_titles(): - """Fetch all Label Studio project IDs and titles""" - try: - response = requests.get( - f'{API_URL}/projects/', - headers={ - 'Authorization': f'Token {API_TOKEN}', - 'Content-Type': 'application/json' - } - ) - - if not response.ok: - error_text = response.text if response.text else '' - print(f'Failed to fetch projects: {response.status_code} {response.reason} - {error_text}') - raise Exception(f'HTTP error! status: {response.status_code}') - - data = response.json() - - if 'results' not in data or not isinstance(data['results'], list): - raise Exception('API response does not contain results array') - - # Extract id and title from each project - projects = [ - {'id': project['id'], 'title': project['title']} - for project in data['results'] - ] - print(projects) - return projects - - except Exception as error: - print(f'Failed to fetch projects: {error}') - return [] +import requests +import time +from services.settings_service import get_setting + +def get_api_credentials(): + """Get Label Studio API credentials from settings""" + api_url = get_setting('labelstudio_api_url', 'http://192.168.1.19:8080/api') + api_token = get_setting('labelstudio_api_token', 'c1cef980b7c73004f4ee880a42839313b863869f') + return api_url, api_token + +def fetch_label_studio_project(project_id): + """Fetch Label Studio project annotations""" + API_URL, API_TOKEN = get_api_credentials() + + export_url = f'{API_URL}/projects/{project_id}/export?exportType=JSON_MIN' + headers = {'Authorization': f'Token {API_TOKEN}'} + + # Trigger export + res = requests.get(export_url, headers=headers) + if not res.ok: + error_text = res.text if res.text else '' + print(f'Failed to trigger export: {res.status_code} {res.reason} - {error_text}') + raise Exception(f'Failed to trigger export: {res.status_code} {res.reason}') + + data = res.json() + + # If data is an array, it's ready + if isinstance(data, list): + return data + + # If not, poll for the export file + file_url = data.get('download_url') or data.get('url') + tries = 0 + + while not file_url and tries < 20: + time.sleep(2) + res = requests.get(export_url, headers=headers) + if not res.ok: + error_text = res.text if res.text else '' + print(f'Failed to poll export: {res.status_code} {res.reason} - {error_text}') + raise Exception(f'Failed to poll export: {res.status_code} {res.reason}') + + data = res.json() + file_url = data.get('download_url') or data.get('url') + tries += 1 + + if not file_url: + raise Exception('Label Studio export did not become ready') + + # Download the export file + full_url = file_url if file_url.startswith('http') else f"{API_URL.replace('/api', '')}{file_url}" + res = requests.get(full_url, headers=headers) + if not res.ok: + error_text = res.text if res.text else '' + print(f'Failed to download export: {res.status_code} {res.reason} - {error_text}') + raise Exception(f'Failed to download export: {res.status_code} {res.reason}') + + return res.json() + +def fetch_project_ids_and_titles(): + """Fetch all Label Studio project IDs and titles""" + API_URL, API_TOKEN = get_api_credentials() + + try: + response = requests.get( + f'{API_URL}/projects/', + headers={ + 'Authorization': f'Token {API_TOKEN}', + 'Content-Type': 'application/json' + } + ) + + if not response.ok: + error_text = response.text if response.text else '' + print(f'Failed to fetch projects: {response.status_code} {response.reason} - {error_text}') + raise Exception(f'HTTP error! status: {response.status_code}') + + data = response.json() + + if 'results' not in data or not isinstance(data['results'], list): + raise Exception('API response does not contain results array') + + # Extract id and title from each project + projects = [ + {'id': project['id'], 'title': project['title']} + for project in data['results'] + ] + print(projects) + return projects + + except Exception as error: + print(f'Failed to fetch projects: {error}') + return [] diff --git a/backend/services/generate-json-yolox.js b/backend/services/generate-json-yolox.js index 295d034..886c768 100644 --- a/backend/services/generate-json-yolox.js +++ b/backend/services/generate-json-yolox.js @@ -1,176 +1,176 @@ -const TrainingProject = require('../models/TrainingProject.js'); -const TrainingProjectDetails = require('../models/TrainingProjectDetails.js') -const LabelStudioProject = require('../models/LabelStudioProject.js') -const Annotation = require('../models/Annotation.js') -const Images = require('../models/Images.js') -const fs = require('fs'); - - -async function generateTrainingJson(trainingId){ - // trainingId is now project_details_id - const trainingProjectDetails = await TrainingProjectDetails.findByPk(trainingId); - if (!trainingProjectDetails) throw new Error('No TrainingProjectDetails found for project_details_id ' + trainingId); - const detailsObj = trainingProjectDetails.get({ plain: true }); - // Get parent project for name - const trainingProject = await TrainingProject.findByPk(detailsObj.project_id); - // Get split percentages (assume they are stored as train_percent, valid_percent, test_percent) - const trainPercent = detailsObj.train_percent || 85; - const validPercent = detailsObj.valid_percent || 10; - const testPercent = detailsObj.test_percent || 5; - - let cocoImages = []; - let cocoAnnotations = []; - let cocoCategories = []; - let categoryMap = {}; - let categoryId = 0; - let imageid = 0; - let annotationid = 0; - - for (const cls of detailsObj.class_map) { - const asgMap = []; - const listAsg = cls[1]; - for(const asg of listAsg){ - asgMap.push ({ original: asg[0], mapped: asg[1] }); - // Build category list and mapping - if (asg[1] && !(asg[1] in categoryMap)) { - categoryMap[asg[1]] = categoryId; - cocoCategories.push({ id: categoryId, name: asg[1], supercategory: '' }); - categoryId++; - } - } - const images = await Images.findAll({ where: { project_id: cls[0] } }); - for(const image of images){ - imageid += 1; - let fileName = image.image_path; - if (fileName.includes('%20')) { - fileName = fileName.replace(/%20/g, ' '); - } - if (fileName && fileName.startsWith('/data/local-files/?d=')) { - fileName = fileName.replace('/data/local-files/?d=', ''); - fileName = fileName.replace('/home/kitraining/home/kitraining/', ''); - } - if (fileName && fileName.startsWith('home/kitraining/To_Annotate/')) { - fileName = fileName.replace('home/kitraining/To_Annotate/',''); - } - // Get annotations for this image - const annotations = await Annotation.findAll({ where: { image_id: image.image_id } }); - // Use image.width and image.height from DB (populated from original_width/original_height) - cocoImages.push({ - id: imageid, - file_name: fileName, - width: image.width || 0, - height: image.height || 0 - }); - for (const annotation of annotations) { - // Translate class name using asgMap - let mappedClass = annotation.Label; - for (const mapEntry of asgMap) { - if (annotation.Label === mapEntry.original) { - mappedClass = mapEntry.mapped; - break; - } - } - // Only add annotation if mappedClass is valid - if (mappedClass && mappedClass in categoryMap) { - annotationid += 1; - let area = 0; - if (annotation.width && annotation.height) { - area = annotation.width * annotation.height; - } - cocoAnnotations.push({ - id: annotationid, - image_id: imageid, - category_id: categoryMap[mappedClass], - bbox: [annotation.x, annotation.y, annotation.width, annotation.height], - area: area, - iscrowd: annotation.iscrowd || 0 - }); - } - } - } - } - - // Shuffle images for random split using seed - function seededRandom(seed) { - let x = Math.sin(seed++) * 10000; - return x - Math.floor(x); - } - function shuffle(array, seed) { - for (let i = array.length - 1; i > 0; i--) { - const j = Math.floor(seededRandom(seed + i) * (i + 1)); - [array[i], array[j]] = [array[j], array[i]]; - } - } - // Use seed from detailsObj if present, else default to 42 - const splitSeed = detailsObj.seed !== undefined && detailsObj.seed !== null ? Number(detailsObj.seed) : 42; - shuffle(cocoImages, splitSeed); - - // Split images - const totalImages = cocoImages.length; - const trainCount = Math.floor(totalImages * trainPercent / 100); - const validCount = Math.floor(totalImages * validPercent / 100); - const testCount = totalImages - trainCount - validCount; - - const trainImages = cocoImages.slice(0, trainCount); - const validImages = cocoImages.slice(trainCount, trainCount + validCount); - const testImages = cocoImages.slice(trainCount + validCount); - - // Helper to get image ids for each split - const trainImageIds = new Set(trainImages.map(img => img.id)); - const validImageIds = new Set(validImages.map(img => img.id)); - const testImageIds = new Set(testImages.map(img => img.id)); - - // Split annotations - const trainAnnotations = cocoAnnotations.filter(ann => trainImageIds.has(ann.image_id)); - const validAnnotations = cocoAnnotations.filter(ann => validImageIds.has(ann.image_id)); - const testAnnotations = cocoAnnotations.filter(ann => testImageIds.has(ann.image_id)); - - // Build final COCO JSONs with info section - const buildCocoJson = (images, annotations, categories) => ({ - images, - annotations, - categories - }); - - // Build COCO JSONs with info section - const trainJson = buildCocoJson(trainImages, trainAnnotations, cocoCategories); - const validJson = buildCocoJson(validImages, validAnnotations, cocoCategories); - const testJson = buildCocoJson(testImages, testAnnotations, cocoCategories); - - // Create output directory: projectname/trainingid/annotations - const projectName = trainingProject && trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${detailsObj.project_id}`; - const outDir = `${projectName}/${trainingId}`; - const annotationsDir = `/home/kitraining/To_Annotate/annotations`; - if (!fs.existsSync(annotationsDir)) { - fs.mkdirSync(annotationsDir, { recursive: true }); - } - - // Write to files in the annotations directory - const trainPath = `${annotationsDir}/coco_project_${trainingId}_train.json`; - const validPath = `${annotationsDir}/coco_project_${trainingId}_valid.json`; - const testPath = `${annotationsDir}/coco_project_${trainingId}_test.json`; - fs.writeFileSync(trainPath, JSON.stringify(trainJson, null, 2)); - fs.writeFileSync(validPath, JSON.stringify(validJson, null, 2)); - fs.writeFileSync(testPath, JSON.stringify(testJson, null, 2)); - console.log(`COCO JSON splits written to ${annotationsDir} for trainingId ${trainingId}`); - - - - // Also generate inference exp.py in the same output directory as exp.py (project folder in workspace) - const { generateYoloxInferenceExp } = require('./generate-yolox-exp'); - const path = require('path'); - const projectFolder = path.join(__dirname, '..', projectName, String(trainingId)); - if (!fs.existsSync(projectFolder)) { - fs.mkdirSync(projectFolder, { recursive: true }); - } - const inferenceExpPath = path.join(projectFolder, 'exp_infer.py'); - generateYoloxInferenceExp(trainingId).then(expContent => { - fs.writeFileSync(inferenceExpPath, expContent); - console.log(`Inference exp.py written to ${inferenceExpPath}`); - }).catch(err => { - console.error('Failed to generate inference exp.py:', err); - }); -} - - +const TrainingProject = require('../models/TrainingProject.js'); +const TrainingProjectDetails = require('../models/TrainingProjectDetails.js') +const LabelStudioProject = require('../models/LabelStudioProject.js') +const Annotation = require('../models/Annotation.js') +const Images = require('../models/Images.js') +const fs = require('fs'); + + +async function generateTrainingJson(trainingId){ + // trainingId is now project_details_id + const trainingProjectDetails = await TrainingProjectDetails.findByPk(trainingId); + if (!trainingProjectDetails) throw new Error('No TrainingProjectDetails found for project_details_id ' + trainingId); + const detailsObj = trainingProjectDetails.get({ plain: true }); + // Get parent project for name + const trainingProject = await TrainingProject.findByPk(detailsObj.project_id); + // Get split percentages (assume they are stored as train_percent, valid_percent, test_percent) + const trainPercent = detailsObj.train_percent || 85; + const validPercent = detailsObj.valid_percent || 10; + const testPercent = detailsObj.test_percent || 5; + + let cocoImages = []; + let cocoAnnotations = []; + let cocoCategories = []; + let categoryMap = {}; + let categoryId = 0; + let imageid = 0; + let annotationid = 0; + + for (const cls of detailsObj.class_map) { + const asgMap = []; + const listAsg = cls[1]; + for(const asg of listAsg){ + asgMap.push ({ original: asg[0], mapped: asg[1] }); + // Build category list and mapping + if (asg[1] && !(asg[1] in categoryMap)) { + categoryMap[asg[1]] = categoryId; + cocoCategories.push({ id: categoryId, name: asg[1], supercategory: '' }); + categoryId++; + } + } + const images = await Images.findAll({ where: { project_id: cls[0] } }); + for(const image of images){ + imageid += 1; + let fileName = image.image_path; + if (fileName.includes('%20')) { + fileName = fileName.replace(/%20/g, ' '); + } + if (fileName && fileName.startsWith('/data/local-files/?d=')) { + fileName = fileName.replace('/data/local-files/?d=', ''); + fileName = fileName.replace('/home/kitraining/home/kitraining/', ''); + } + if (fileName && fileName.startsWith('home/kitraining/To_Annotate/')) { + fileName = fileName.replace('home/kitraining/To_Annotate/',''); + } + // Get annotations for this image + const annotations = await Annotation.findAll({ where: { image_id: image.image_id } }); + // Use image.width and image.height from DB (populated from original_width/original_height) + cocoImages.push({ + id: imageid, + file_name: fileName, + width: image.width || 0, + height: image.height || 0 + }); + for (const annotation of annotations) { + // Translate class name using asgMap + let mappedClass = annotation.Label; + for (const mapEntry of asgMap) { + if (annotation.Label === mapEntry.original) { + mappedClass = mapEntry.mapped; + break; + } + } + // Only add annotation if mappedClass is valid + if (mappedClass && mappedClass in categoryMap) { + annotationid += 1; + let area = 0; + if (annotation.width && annotation.height) { + area = annotation.width * annotation.height; + } + cocoAnnotations.push({ + id: annotationid, + image_id: imageid, + category_id: categoryMap[mappedClass], + bbox: [annotation.x, annotation.y, annotation.width, annotation.height], + area: area, + iscrowd: annotation.iscrowd || 0 + }); + } + } + } + } + + // Shuffle images for random split using seed + function seededRandom(seed) { + let x = Math.sin(seed++) * 10000; + return x - Math.floor(x); + } + function shuffle(array, seed) { + for (let i = array.length - 1; i > 0; i--) { + const j = Math.floor(seededRandom(seed + i) * (i + 1)); + [array[i], array[j]] = [array[j], array[i]]; + } + } + // Use seed from detailsObj if present, else default to 42 + const splitSeed = detailsObj.seed !== undefined && detailsObj.seed !== null ? Number(detailsObj.seed) : 42; + shuffle(cocoImages, splitSeed); + + // Split images + const totalImages = cocoImages.length; + const trainCount = Math.floor(totalImages * trainPercent / 100); + const validCount = Math.floor(totalImages * validPercent / 100); + const testCount = totalImages - trainCount - validCount; + + const trainImages = cocoImages.slice(0, trainCount); + const validImages = cocoImages.slice(trainCount, trainCount + validCount); + const testImages = cocoImages.slice(trainCount + validCount); + + // Helper to get image ids for each split + const trainImageIds = new Set(trainImages.map(img => img.id)); + const validImageIds = new Set(validImages.map(img => img.id)); + const testImageIds = new Set(testImages.map(img => img.id)); + + // Split annotations + const trainAnnotations = cocoAnnotations.filter(ann => trainImageIds.has(ann.image_id)); + const validAnnotations = cocoAnnotations.filter(ann => validImageIds.has(ann.image_id)); + const testAnnotations = cocoAnnotations.filter(ann => testImageIds.has(ann.image_id)); + + // Build final COCO JSONs with info section + const buildCocoJson = (images, annotations, categories) => ({ + images, + annotations, + categories + }); + + // Build COCO JSONs with info section + const trainJson = buildCocoJson(trainImages, trainAnnotations, cocoCategories); + const validJson = buildCocoJson(validImages, validAnnotations, cocoCategories); + const testJson = buildCocoJson(testImages, testAnnotations, cocoCategories); + + // Create output directory: projectname/trainingid/annotations + const projectName = trainingProject && trainingProject.name ? trainingProject.name.replace(/\s+/g, '_') : `project_${detailsObj.project_id}`; + const outDir = `${projectName}/${trainingId}`; + const annotationsDir = `/home/kitraining/To_Annotate/annotations`; + if (!fs.existsSync(annotationsDir)) { + fs.mkdirSync(annotationsDir, { recursive: true }); + } + + // Write to files in the annotations directory + const trainPath = `${annotationsDir}/coco_project_${trainingId}_train.json`; + const validPath = `${annotationsDir}/coco_project_${trainingId}_valid.json`; + const testPath = `${annotationsDir}/coco_project_${trainingId}_test.json`; + fs.writeFileSync(trainPath, JSON.stringify(trainJson, null, 2)); + fs.writeFileSync(validPath, JSON.stringify(validJson, null, 2)); + fs.writeFileSync(testPath, JSON.stringify(testJson, null, 2)); + console.log(`COCO JSON splits written to ${annotationsDir} for trainingId ${trainingId}`); + + + + // Also generate inference exp.py in the same output directory as exp.py (project folder in workspace) + const { generateYoloxInferenceExp } = require('./generate-yolox-exp'); + const path = require('path'); + const projectFolder = path.join(__dirname, '..', projectName, String(trainingId)); + if (!fs.existsSync(projectFolder)) { + fs.mkdirSync(projectFolder, { recursive: true }); + } + const inferenceExpPath = path.join(projectFolder, 'exp_infer.py'); + generateYoloxInferenceExp(trainingId).then(expContent => { + fs.writeFileSync(inferenceExpPath, expContent); + console.log(`Inference exp.py written to ${inferenceExpPath}`); + }).catch(err => { + console.error('Failed to generate inference exp.py:', err); + }); +} + + module.exports = {generateTrainingJson}; \ No newline at end of file diff --git a/backend/services/generate-yolox-exp.js b/backend/services/generate-yolox-exp.js index d18e0a0..4cbdb6f 100644 --- a/backend/services/generate-yolox-exp.js +++ b/backend/services/generate-yolox-exp.js @@ -1,135 +1,135 @@ -const fs = require('fs'); -const path = require('path'); -const Training = require('../models/training.js'); -const TrainingProject = require('../models/TrainingProject.js'); - -// Remove Python comments and legacy code -const exp_names = [ - 'YOLOX-s', - 'YOLOX-m', - 'YOLOX-l', - 'YOLOX-x', - 'YOLOX-Darknet53', //todo - 'YOLOX-Nano', - 'YOLOX-Tiny' -] - -//TODO: Clean up generation of exp_names.py and remove second exp creation!!! - - -// Refactored: Accept trainingId, fetch info from DB -async function generateYoloxExp(trainingId) { - // Fetch training row from DB by project_details_id if not found by PK - let training = await Training.findByPk(trainingId); - if (!training) { - training = await Training.findOne({ where: { project_details_id: trainingId } }); - } - if (!training) throw new Error('Training not found for trainingId or project_details_id: ' + trainingId); - - // If transfer_learning is 'coco', just return the path to the default exp.py - if (training.transfer_learning === 'coco') { - const selectedModel = training.selected_model.toLowerCase().replace('-', '_'); - const expSourcePath = `/home/kitraining/Yolox/YOLOX-main/exps/default/${selectedModel}.py`; - if (!fs.existsSync(expSourcePath)) { - throw new Error(`Default exp.py not found for model: ${selectedModel} at ${expSourcePath}`); - } - // Copy to project folder (e.g., /home/kitraining/coco_tool/backend/project_XX/YY/exp.py) - const projectDetailsId = training.project_details_id; - const projectFolder = path.resolve(__dirname, `../project_23/${projectDetailsId}`); - if (!fs.existsSync(projectFolder)) { - fs.mkdirSync(projectFolder, { recursive: true }); - } - const expDestPath = path.join(projectFolder, 'exp.py'); - fs.copyFileSync(expSourcePath, expDestPath); - return { type: 'default', expPath: expDestPath }; - } - - // If transfer_learning is 'sketch', generate a custom exp.py as before - if (training.transfer_learning === 'sketch') { - // ...existing custom exp.py generation logic here (copy from previous implementation)... - // For brevity, you can call generateYoloxInferenceExp or similar here, or inline the logic. - // Example: - const expContent = await generateYoloxInferenceExp(trainingId); - return { type: 'custom', expContent }; - } - - throw new Error('Unknown transfer_learning type: ' + training.transfer_learning); -} - -async function saveYoloxExp(trainingId, outPath) { - const expResult = await generateYoloxExp(trainingId); - if (expResult.type === 'custom' && expResult.expContent) { - fs.writeFileSync(outPath, expResult.expContent); - return outPath; - } else if (expResult.type === 'default' && expResult.expPath) { - // Optionally copy the file if outPath is different - if (expResult.expPath !== outPath) { - fs.copyFileSync(expResult.expPath, outPath); - } - return outPath; - } else { - throw new Error('Unknown expResult type or missing content'); - } -} - -// Generate a second exp.py for inference, using the provided template and DB values -async function generateYoloxInferenceExp(trainingId, options = {}) { - let training = await Training.findByPk(trainingId); - if (!training) { - training = await Training.findOne({ where: { project_details_id: trainingId } }); - } - if (!training) throw new Error('Training not found for trainingId or project_details_id: ' + trainingId); - // Always use the trainingId (project_details_id) for annotation file names - const projectDetailsId = training.project_details_id; - const dataDir = options.data_dir || '/home/kitraining/To_Annotate/'; - const trainAnn = options.train_ann || `coco_project_${trainingId}_train.json`; - const valAnn = options.val_ann || `coco_project_${trainingId}_valid.json`; - const testAnn = options.test_ann || `coco_project_${trainingId}_test.json`; - // Get num_classes from TrainingProject.classes JSON - let numClasses = 80; - try { - const trainingProject = await TrainingProject.findByPk(projectDetailsId); - if (trainingProject && trainingProject.classes) { - let classesArr = trainingProject.classes; - if (typeof classesArr === 'string') { - classesArr = JSON.parse(classesArr); - } - if (Array.isArray(classesArr)) { - numClasses = classesArr.filter(c => c !== null && c !== undefined && c !== '').length; - } else if (typeof classesArr === 'object' && classesArr !== null) { - numClasses = Object.keys(classesArr).filter(k => classesArr[k] !== null && classesArr[k] !== undefined && classesArr[k] !== '').length; - } - } - } catch (e) { - console.warn('Could not determine num_classes from TrainingProject.classes:', e); - } - const depth = options.depth || training.depth || 1.00; - const width = options.width || training.width || 1.00; - const inputSize = options.input_size || training.input_size || [640, 640]; - const mosaicScale = options.mosaic_scale || training.mosaic_scale || [0.1, 2]; - const randomSize = options.random_size || training.random_size || [10, 20]; - const testSize = options.test_size || training.test_size || [640, 640]; - const expName = options.exp_name || 'inference_exp'; - const enableMixup = options.enable_mixup !== undefined ? options.enable_mixup : false; - let expContent = ''; - expContent += `#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n# Copyright (c) Megvii, Inc. and its affiliates.\n\nimport os\n\nfrom yolox.exp import Exp as MyExp\n\n\nclass Exp(MyExp):\n def __init__(self):\n super(Exp, self).__init__()\n self.data_dir = "${dataDir}"\n self.train_ann = "${trainAnn}"\n self.val_ann = "${valAnn}"\n self.test_ann = "coco_project_${trainingId}_test.json"\n self.num_classes = ${numClasses}\n`; - // Set pretrained_ckpt if transfer_learning is 'coco' - if (training.transfer_learning && typeof training.transfer_learning === 'string' && training.transfer_learning.toLowerCase() === 'coco') { - const yoloxBaseDir = '/home/kitraining/Yolox/YOLOX-main'; - const selectedModel = training.selected_model ? training.selected_model.replace(/\.pth$/i, '') : ''; - if (selectedModel) { - expContent += ` self.pretrained_ckpt = r'${yoloxBaseDir}/pretrained/${selectedModel}.pth'\n`; - } - } - expContent += ` self.depth = ${depth}\n self.width = ${width}\n self.input_size = (${Array.isArray(inputSize) ? inputSize.join(', ') : inputSize})\n self.mosaic_scale = (${Array.isArray(mosaicScale) ? mosaicScale.join(', ') : mosaicScale})\n self.random_size = (${Array.isArray(randomSize) ? randomSize.join(', ') : randomSize})\n self.test_size = (${Array.isArray(testSize) ? testSize.join(', ') : testSize})\n self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]\n self.enable_mixup = ${enableMixup ? 'True' : 'False'}\n`; - return expContent; -} - -// Save inference exp.py to a custom path -async function saveYoloxInferenceExp(trainingId, outPath, options = {}) { - const expContent = await generateYoloxInferenceExp(trainingId, options); - fs.writeFileSync(outPath, expContent); - return outPath; -} - +const fs = require('fs'); +const path = require('path'); +const Training = require('../models/training.js'); +const TrainingProject = require('../models/TrainingProject.js'); + +// Remove Python comments and legacy code +const exp_names = [ + 'YOLOX-s', + 'YOLOX-m', + 'YOLOX-l', + 'YOLOX-x', + 'YOLOX-Darknet53', //todo + 'YOLOX-Nano', + 'YOLOX-Tiny' +] + +//TODO: Clean up generation of exp_names.py and remove second exp creation!!! + + +// Refactored: Accept trainingId, fetch info from DB +async function generateYoloxExp(trainingId) { + // Fetch training row from DB by project_details_id if not found by PK + let training = await Training.findByPk(trainingId); + if (!training) { + training = await Training.findOne({ where: { project_details_id: trainingId } }); + } + if (!training) throw new Error('Training not found for trainingId or project_details_id: ' + trainingId); + + // If transfer_learning is 'coco', just return the path to the default exp.py + if (training.transfer_learning === 'coco') { + const selectedModel = training.selected_model.toLowerCase().replace('-', '_'); + const expSourcePath = `/home/kitraining/Yolox/YOLOX-main/exps/default/${selectedModel}.py`; + if (!fs.existsSync(expSourcePath)) { + throw new Error(`Default exp.py not found for model: ${selectedModel} at ${expSourcePath}`); + } + // Copy to project folder (e.g., /home/kitraining/coco_tool/backend/project_XX/YY/exp.py) + const projectDetailsId = training.project_details_id; + const projectFolder = path.resolve(__dirname, `../project_23/${projectDetailsId}`); + if (!fs.existsSync(projectFolder)) { + fs.mkdirSync(projectFolder, { recursive: true }); + } + const expDestPath = path.join(projectFolder, 'exp.py'); + fs.copyFileSync(expSourcePath, expDestPath); + return { type: 'default', expPath: expDestPath }; + } + + // If transfer_learning is 'sketch', generate a custom exp.py as before + if (training.transfer_learning === 'sketch') { + // ...existing custom exp.py generation logic here (copy from previous implementation)... + // For brevity, you can call generateYoloxInferenceExp or similar here, or inline the logic. + // Example: + const expContent = await generateYoloxInferenceExp(trainingId); + return { type: 'custom', expContent }; + } + + throw new Error('Unknown transfer_learning type: ' + training.transfer_learning); +} + +async function saveYoloxExp(trainingId, outPath) { + const expResult = await generateYoloxExp(trainingId); + if (expResult.type === 'custom' && expResult.expContent) { + fs.writeFileSync(outPath, expResult.expContent); + return outPath; + } else if (expResult.type === 'default' && expResult.expPath) { + // Optionally copy the file if outPath is different + if (expResult.expPath !== outPath) { + fs.copyFileSync(expResult.expPath, outPath); + } + return outPath; + } else { + throw new Error('Unknown expResult type or missing content'); + } +} + +// Generate a second exp.py for inference, using the provided template and DB values +async function generateYoloxInferenceExp(trainingId, options = {}) { + let training = await Training.findByPk(trainingId); + if (!training) { + training = await Training.findOne({ where: { project_details_id: trainingId } }); + } + if (!training) throw new Error('Training not found for trainingId or project_details_id: ' + trainingId); + // Always use the trainingId (project_details_id) for annotation file names + const projectDetailsId = training.project_details_id; + const dataDir = options.data_dir || '/home/kitraining/To_Annotate/'; + const trainAnn = options.train_ann || `coco_project_${trainingId}_train.json`; + const valAnn = options.val_ann || `coco_project_${trainingId}_valid.json`; + const testAnn = options.test_ann || `coco_project_${trainingId}_test.json`; + // Get num_classes from TrainingProject.classes JSON + let numClasses = 80; + try { + const trainingProject = await TrainingProject.findByPk(projectDetailsId); + if (trainingProject && trainingProject.classes) { + let classesArr = trainingProject.classes; + if (typeof classesArr === 'string') { + classesArr = JSON.parse(classesArr); + } + if (Array.isArray(classesArr)) { + numClasses = classesArr.filter(c => c !== null && c !== undefined && c !== '').length; + } else if (typeof classesArr === 'object' && classesArr !== null) { + numClasses = Object.keys(classesArr).filter(k => classesArr[k] !== null && classesArr[k] !== undefined && classesArr[k] !== '').length; + } + } + } catch (e) { + console.warn('Could not determine num_classes from TrainingProject.classes:', e); + } + const depth = options.depth || training.depth || 1.00; + const width = options.width || training.width || 1.00; + const inputSize = options.input_size || training.input_size || [640, 640]; + const mosaicScale = options.mosaic_scale || training.mosaic_scale || [0.1, 2]; + const randomSize = options.random_size || training.random_size || [10, 20]; + const testSize = options.test_size || training.test_size || [640, 640]; + const expName = options.exp_name || 'inference_exp'; + const enableMixup = options.enable_mixup !== undefined ? options.enable_mixup : false; + let expContent = ''; + expContent += `#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n# Copyright (c) Megvii, Inc. and its affiliates.\n\nimport os\n\nfrom yolox.exp import Exp as MyExp\n\n\nclass Exp(MyExp):\n def __init__(self):\n super(Exp, self).__init__()\n self.data_dir = "${dataDir}"\n self.train_ann = "${trainAnn}"\n self.val_ann = "${valAnn}"\n self.test_ann = "coco_project_${trainingId}_test.json"\n self.num_classes = ${numClasses}\n`; + // Set pretrained_ckpt if transfer_learning is 'coco' + if (training.transfer_learning && typeof training.transfer_learning === 'string' && training.transfer_learning.toLowerCase() === 'coco') { + const yoloxBaseDir = '/home/kitraining/Yolox/YOLOX-main'; + const selectedModel = training.selected_model ? training.selected_model.replace(/\.pth$/i, '') : ''; + if (selectedModel) { + expContent += ` self.pretrained_ckpt = r'${yoloxBaseDir}/pretrained/${selectedModel}.pth'\n`; + } + } + expContent += ` self.depth = ${depth}\n self.width = ${width}\n self.input_size = (${Array.isArray(inputSize) ? inputSize.join(', ') : inputSize})\n self.mosaic_scale = (${Array.isArray(mosaicScale) ? mosaicScale.join(', ') : mosaicScale})\n self.random_size = (${Array.isArray(randomSize) ? randomSize.join(', ') : randomSize})\n self.test_size = (${Array.isArray(testSize) ? testSize.join(', ') : testSize})\n self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0]\n self.enable_mixup = ${enableMixup ? 'True' : 'False'}\n`; + return expContent; +} + +// Save inference exp.py to a custom path +async function saveYoloxInferenceExp(trainingId, outPath, options = {}) { + const expContent = await generateYoloxInferenceExp(trainingId, options); + fs.writeFileSync(outPath, expContent); + return outPath; +} + module.exports = { generateYoloxExp, saveYoloxExp, generateYoloxInferenceExp, saveYoloxInferenceExp }; \ No newline at end of file diff --git a/backend/services/generate_json_yolox.py b/backend/services/generate_json_yolox.py index 0129c96..3592b55 100644 --- a/backend/services/generate_json_yolox.py +++ b/backend/services/generate_json_yolox.py @@ -1,179 +1,288 @@ -import json -import os -import math -from models.TrainingProject import TrainingProject -from models.TrainingProjectDetails import TrainingProjectDetails -from models.Images import Image -from models.Annotation import Annotation - -def generate_training_json(training_id): - """Generate COCO JSON for training, validation, and test sets""" - # training_id is now project_details_id - training_project_details = TrainingProjectDetails.query.get(training_id) - - if not training_project_details: - raise Exception(f'No TrainingProjectDetails found for project_details_id {training_id}') - - details_obj = training_project_details.to_dict() - - # Get parent project for name - training_project = TrainingProject.query.get(details_obj['project_id']) - - # Get split percentages (default values if not set) - train_percent = details_obj.get('train_percent', 85) - valid_percent = details_obj.get('valid_percent', 10) - test_percent = details_obj.get('test_percent', 5) - - coco_images = [] - coco_annotations = [] - coco_categories = [] - category_map = {} - category_id = 0 - image_id = 0 - annotation_id = 0 - - for cls in details_obj['class_map']: - asg_map = [] - list_asg = cls[1] - - for asg in list_asg: - asg_map.append({'original': asg[0], 'mapped': asg[1]}) - # Build category list and mapping - if asg[1] and asg[1] not in category_map: - category_map[asg[1]] = category_id - coco_categories.append({'id': category_id, 'name': asg[1], 'supercategory': ''}) - category_id += 1 - - # Get images for this project - images = Image.query.filter_by(project_id=cls[0]).all() - - for image in images: - image_id += 1 - file_name = image.image_path - - # Clean up file path - if '%20' in file_name: - file_name = file_name.replace('%20', ' ') - if file_name and file_name.startswith('/data/local-files/?d='): - file_name = file_name.replace('/data/local-files/?d=', '') - file_name = file_name.replace('/home/kitraining/home/kitraining/', '') - if file_name and file_name.startswith('home/kitraining/To_Annotate/'): - file_name = file_name.replace('home/kitraining/To_Annotate/', '') - - # Get annotations for this image - annotations = Annotation.query.filter_by(image_id=image.image_id).all() - - coco_images.append({ - 'id': image_id, - 'file_name': file_name, - 'width': image.width or 0, - 'height': image.height or 0 - }) - - for annotation in annotations: - # Translate class name using asg_map - mapped_class = annotation.Label - for map_entry in asg_map: - if annotation.Label == map_entry['original']: - mapped_class = map_entry['mapped'] - break - - # Only add annotation if mapped_class is valid - if mapped_class and mapped_class in category_map: - annotation_id += 1 - area = 0 - if annotation.width and annotation.height: - area = annotation.width * annotation.height - - coco_annotations.append({ - 'id': annotation_id, - 'image_id': image_id, - 'category_id': category_map[mapped_class], - 'bbox': [annotation.x, annotation.y, annotation.width, annotation.height], - 'area': area, - 'iscrowd': 0 - }) - - # Shuffle images for random split using seed - def seeded_random(seed): - x = math.sin(seed) * 10000 - return x - math.floor(x) - - def shuffle(array, seed): - for i in range(len(array) - 1, 0, -1): - j = int(seeded_random(seed + i) * (i + 1)) - array[i], array[j] = array[j], array[i] - - # Use seed from details_obj if present, else default to 42 - split_seed = details_obj.get('seed', 42) - if split_seed is not None: - split_seed = int(split_seed) - else: - split_seed = 42 - - shuffle(coco_images, split_seed) - - # Split images - total_images = len(coco_images) - train_count = int(total_images * train_percent / 100) - valid_count = int(total_images * valid_percent / 100) - test_count = total_images - train_count - valid_count - - train_images = coco_images[0:train_count] - valid_images = coco_images[train_count:train_count + valid_count] - test_images = coco_images[train_count + valid_count:] - - # Helper to get image ids for each split - train_image_ids = {img['id'] for img in train_images} - valid_image_ids = {img['id'] for img in valid_images} - test_image_ids = {img['id'] for img in test_images} - - # Split annotations - train_annotations = [ann for ann in coco_annotations if ann['image_id'] in train_image_ids] - valid_annotations = [ann for ann in coco_annotations if ann['image_id'] in valid_image_ids] - test_annotations = [ann for ann in coco_annotations if ann['image_id'] in test_image_ids] - - # Build final COCO JSONs - def build_coco_json(images, annotations, categories): - return { - 'images': images, - 'annotations': annotations, - 'categories': categories - } - - train_json = build_coco_json(train_images, train_annotations, coco_categories) - valid_json = build_coco_json(valid_images, valid_annotations, coco_categories) - test_json = build_coco_json(test_images, test_annotations, coco_categories) - - # Create output directory - project_name = training_project.title.replace(' ', '_') if training_project and training_project.title else f'project_{details_obj["project_id"]}' - annotations_dir = '/home/kitraining/To_Annotate/annotations' - os.makedirs(annotations_dir, exist_ok=True) - - # Write to files - train_path = f'{annotations_dir}/coco_project_{training_id}_train.json' - valid_path = f'{annotations_dir}/coco_project_{training_id}_valid.json' - test_path = f'{annotations_dir}/coco_project_{training_id}_test.json' - - with open(train_path, 'w') as f: - json.dump(train_json, f, indent=2) - with open(valid_path, 'w') as f: - json.dump(valid_json, f, indent=2) - with open(test_path, 'w') as f: - json.dump(test_json, f, indent=2) - - print(f'COCO JSON splits written to {annotations_dir} for trainingId {training_id}') - - # Also generate inference exp.py - from services.generate_yolox_exp import generate_yolox_inference_exp - project_folder = os.path.join(os.path.dirname(__file__), '..', project_name, str(training_id)) - os.makedirs(project_folder, exist_ok=True) - - inference_exp_path = os.path.join(project_folder, 'exp_infer.py') - try: - exp_content = generate_yolox_inference_exp(training_id) - with open(inference_exp_path, 'w') as f: - f.write(exp_content) - print(f'Inference exp.py written to {inference_exp_path}') - except Exception as err: - print(f'Failed to generate inference exp.py: {err}') +import json +import os +import math +from models.TrainingProject import TrainingProject +from models.TrainingProjectDetails import TrainingProjectDetails +from models.Images import Image +from models.Annotation import Annotation + +def generate_training_json(training_id): + """Generate COCO JSON for training, validation, and test sets""" + # training_id is now project_details_id + training_project_details = TrainingProjectDetails.query.get(training_id) + + if not training_project_details: + raise Exception(f'No TrainingProjectDetails found for project_details_id {training_id}') + + details_obj = training_project_details.to_dict() + + # Get parent project for name + training_project = TrainingProject.query.get(details_obj['project_id']) + + # Get the data directory setting for image paths + from services.settings_service import get_setting + data_dir = get_setting('yolox_data_dir', '/home/kitraining/To_Annotate/') + + # Fix UNC path if it's missing the \\ prefix + # Check if it looks like a UNC path without proper prefix (e.g., "192.168.1.19\...") + if data_dir and not data_dir.startswith('\\\\') and not data_dir.startswith('/'): + # Check if it starts with an IP address pattern + import re + if re.match(r'^\d+\.\d+\.\d+\.\d+[/\\]', data_dir): + data_dir = '\\\\' + data_dir + + # Ensure data_dir ends with separator + if not data_dir.endswith(os.sep) and not data_dir.endswith('/'): + data_dir += os.sep + + # Get split percentages (default values if not set) + train_percent = details_obj.get('train_percent', 85) + valid_percent = details_obj.get('valid_percent', 10) + test_percent = details_obj.get('test_percent', 5) + + coco_images = [] + coco_annotations = [] + coco_categories = [] + category_map = {} + category_id = 0 + image_id = 0 + annotation_id = 0 + + # Build category list and mapping from class_map dictionary {source: target} + class_map = details_obj.get('class_map', {}) + + for source_class, target_class in class_map.items(): + if target_class and target_class not in category_map: + category_map[target_class] = category_id + coco_categories.append({'id': category_id, 'name': target_class, 'supercategory': ''}) + category_id += 1 + + # Get all annotation projects (Label Studio project IDs) + annotation_projects = details_obj.get('annotation_projects', []) + + # Get class mappings from database grouped by Label Studio project + from models.ClassMapping import ClassMapping + all_mappings = ClassMapping.query.filter_by(project_details_id=training_id).all() + + # Group mappings by Label Studio project ID + mappings_by_project = {} + for mapping in all_mappings: + ls_proj_id = mapping.label_studio_project_id + if ls_proj_id not in mappings_by_project: + mappings_by_project[ls_proj_id] = {} + mappings_by_project[ls_proj_id][mapping.source_class] = mapping.target_class + + # Also add target class to category map if not present + if mapping.target_class and mapping.target_class not in category_map: + category_map[mapping.target_class] = category_id + coco_categories.append({'id': category_id, 'name': mapping.target_class, 'supercategory': ''}) + category_id += 1 + + # Iterate through each annotation project to collect images and annotations + for ls_project_id in annotation_projects: + # Get images for this Label Studio project + images = Image.query.filter_by(project_id=ls_project_id).all() + + for image in images: + image_id += 1 + file_name = image.image_path + + # Clean up file path from Label Studio format + if '%20' in file_name: + file_name = file_name.replace('%20', ' ') + if file_name and file_name.startswith('/data/local-files/?d='): + file_name = file_name.replace('/data/local-files/?d=', '') + + # Remove any Label Studio prefixes but keep full path + # Common Label Studio patterns + prefixes_to_remove = [ + '//192.168.1.19/home/kitraining/To_Annotate/', + '192.168.1.19/home/kitraining/To_Annotate/', + '/home/kitraining/home/kitraining/', + 'home/kitraining/To_Annotate/', + '/home/kitraining/To_Annotate/', + ] + + # Try each prefix + for prefix in prefixes_to_remove: + if file_name.startswith(prefix): + file_name = file_name[len(prefix):] + break + + # Construct ABSOLUTE path using data_dir + # Detect platform for proper path handling + import platform + is_windows = platform.system() == 'Windows' + + # Normalize path separators in file_name to forward slashes first (OS-agnostic) + file_name = file_name.replace('\\', '/') + + # Normalize data_dir to use forward slashes + normalized_data_dir = data_dir.rstrip('/\\').replace('\\', '/') + + # Check if file_name is already an absolute path + is_absolute = False + if is_windows: + # Windows: Check for drive letter (C:/) or UNC path (//server/) + is_absolute = (len(file_name) > 1 and file_name[1] == ':') or file_name.startswith('//') + else: + # Linux/Mac: Check for leading / + is_absolute = file_name.startswith('/') + + if not is_absolute: + # It's a relative path, combine with data_dir + if normalized_data_dir.startswith('//'): + # UNC path on Windows + file_name = normalized_data_dir + '/' + file_name + else: + # Regular path - use os.path.join but with forward slashes + file_name = os.path.join(normalized_data_dir, file_name).replace('\\', '/') + + # Final OS-specific normalization + if is_windows: + # Convert to Windows-style backslashes + file_name = file_name.replace('/', '\\') + else: + # Keep as forward slashes for Linux/Mac + file_name = file_name.replace('\\', '/') + + # Get annotations for this image + annotations = Annotation.query.filter_by(image_id=image.image_id).all() + + # Ensure width and height are integers and valid + # If missing or invalid, skip this image or use default dimensions + img_width = int(image.width) if image.width else 0 + img_height = int(image.height) if image.height else 0 + + # Skip images with invalid dimensions + if img_width <= 0 or img_height <= 0: + print(f'Warning: Skipping image {file_name} with invalid dimensions: {img_width}x{img_height}') + continue + + coco_images.append({ + 'id': image_id, + 'file_name': file_name, # Use absolute path + 'width': img_width, + 'height': img_height + }) + + for annotation in annotations: + # Translate class name using class_map for this specific Label Studio project + original_class = annotation.Label + project_class_map = mappings_by_project.get(ls_project_id, {}) + mapped_class = project_class_map.get(original_class, original_class) + + # Only add annotation if mapped_class is valid + if mapped_class and mapped_class in category_map: + annotation_id += 1 + area = 0 + if annotation.width and annotation.height: + area = annotation.width * annotation.height + + coco_annotations.append({ + 'id': annotation_id, + 'image_id': image_id, + 'category_id': category_map[mapped_class], + 'bbox': [annotation.x, annotation.y, annotation.width, annotation.height], + 'area': area, + 'iscrowd': 0 + }) + + # Shuffle images for random split using seed + def seeded_random(seed): + x = math.sin(seed) * 10000 + return x - math.floor(x) + + def shuffle(array, seed): + for i in range(len(array) - 1, 0, -1): + j = int(seeded_random(seed + i) * (i + 1)) + array[i], array[j] = array[j], array[i] + + # Use seed from details_obj if present, else default to 42 + split_seed = details_obj.get('seed', 42) + if split_seed is not None: + split_seed = int(split_seed) + else: + split_seed = 42 + + shuffle(coco_images, split_seed) + + # Split images + total_images = len(coco_images) + train_count = int(total_images * train_percent / 100) + valid_count = int(total_images * valid_percent / 100) + test_count = total_images - train_count - valid_count + + train_images = coco_images[0:train_count] + valid_images = coco_images[train_count:train_count + valid_count] + test_images = coco_images[train_count + valid_count:] + + # Helper to get image ids for each split + train_image_ids = {img['id'] for img in train_images} + valid_image_ids = {img['id'] for img in valid_images} + test_image_ids = {img['id'] for img in test_images} + + # Split annotations + train_annotations = [ann for ann in coco_annotations if ann['image_id'] in train_image_ids] + valid_annotations = [ann for ann in coco_annotations if ann['image_id'] in valid_image_ids] + test_annotations = [ann for ann in coco_annotations if ann['image_id'] in test_image_ids] + + # Build final COCO JSONs + def build_coco_json(images, annotations, categories): + return { + 'images': images, + 'annotations': annotations, + 'categories': categories + } + + train_json = build_coco_json(train_images, train_annotations, coco_categories) + valid_json = build_coco_json(valid_images, valid_annotations, coco_categories) + test_json = build_coco_json(test_images, test_annotations, coco_categories) + + # Create output directory + from services.settings_service import get_setting + from models.training import Training + + output_base_path = get_setting('yolox_output_path', './backend') + + project_name = training_project.title.replace(' ', '_') if training_project and training_project.title else f'project_{details_obj["project_id"]}' + + # Get training record to use its name for folder + training_record = Training.query.filter_by(project_details_id=training_id).first() + training_folder_name = f"{training_record.exp_name or training_record.training_name or 'training'}_{training_record.id}" if training_record else str(training_id) + training_folder_name = training_folder_name.replace(' ', '_') + + # Use training_record.id for file names to match what generate_yolox_exp expects + training_file_id = training_record.id if training_record else training_id + + # Save annotations to the configured output folder + annotations_dir = os.path.join(output_base_path, project_name, training_folder_name, 'annotations') + os.makedirs(annotations_dir, exist_ok=True) + + # Write to files + train_path = os.path.join(annotations_dir, f'coco_project_{training_file_id}_train.json') + valid_path = os.path.join(annotations_dir, f'coco_project_{training_file_id}_valid.json') + test_path = os.path.join(annotations_dir, f'coco_project_{training_file_id}_test.json') + + with open(train_path, 'w') as f: + json.dump(train_json, f, indent=2) + with open(valid_path, 'w') as f: + json.dump(valid_json, f, indent=2) + with open(test_path, 'w') as f: + json.dump(test_json, f, indent=2) + + print(f'COCO JSON splits written to {annotations_dir} for trainingId {training_id}') + + # Also generate inference exp.py + from services.generate_yolox_exp import generate_yolox_inference_exp + project_folder = os.path.join(output_base_path, project_name, str(training_id)) + os.makedirs(project_folder, exist_ok=True) + + inference_exp_path = os.path.join(project_folder, 'exp_infer.py') + try: + exp_content = generate_yolox_inference_exp(training_id) + with open(inference_exp_path, 'w') as f: + f.write(exp_content) + print(f'Inference exp.py written to {inference_exp_path}') + except Exception as err: + print(f'Failed to generate inference exp.py: {err}') diff --git a/backend/services/generate_yolox_exp.py b/backend/services/generate_yolox_exp.py index 3377f5d..0f30c91 100644 --- a/backend/services/generate_yolox_exp.py +++ b/backend/services/generate_yolox_exp.py @@ -1,228 +1,329 @@ -import os -import shutil -import importlib.util -from models.training import Training -from models.TrainingProject import TrainingProject - -def load_base_config(selected_model): - """Load base configuration for a specific YOLOX model""" - model_name = selected_model.lower().replace('-', '_').replace('.pth', '') - base_config_path = os.path.join(os.path.dirname(__file__), '..', 'data', f'{model_name}.py') - - if not os.path.exists(base_config_path): - raise Exception(f'Base configuration not found for model: {model_name} at {base_config_path}') - - # Load the module dynamically - spec = importlib.util.spec_from_file_location(f"base_config_{model_name}", base_config_path) - module = importlib.util.module_from_spec(spec) - spec.loader.exec_module(module) - - # Extract all attributes from BaseExp class - base_exp = module.BaseExp() - base_config = {} - for attr in dir(base_exp): - if not attr.startswith('_'): - base_config[attr] = getattr(base_exp, attr) - - return base_config - -def generate_yolox_exp(training_id): - """Generate YOLOX exp.py file""" - # Fetch training row from DB - training = Training.query.get(training_id) - if not training: - training = Training.query.filter_by(project_details_id=training_id).first() - - if not training: - raise Exception(f'Training not found for trainingId or project_details_id: {training_id}') - - # If transfer_learning is 'coco', generate exp using base config + custom settings - if training.transfer_learning == 'coco': - exp_content = generate_yolox_inference_exp(training_id, use_base_config=True) - return {'type': 'custom', 'expContent': exp_content} - - # If transfer_learning is 'sketch', generate custom exp.py - if training.transfer_learning == 'sketch': - exp_content = generate_yolox_inference_exp(training_id, use_base_config=False) - return {'type': 'custom', 'expContent': exp_content} - - raise Exception(f'Unknown transfer_learning type: {training.transfer_learning}') - -def save_yolox_exp(training_id, out_path): - """Save YOLOX exp.py to specified path""" - exp_result = generate_yolox_exp(training_id) - - if exp_result['type'] == 'custom' and 'expContent' in exp_result: - with open(out_path, 'w') as f: - f.write(exp_result['expContent']) - return out_path - elif exp_result['type'] == 'default' and 'expPath' in exp_result: - # Optionally copy the file if outPath is different - if exp_result['expPath'] != out_path: - shutil.copyfile(exp_result['expPath'], out_path) - return out_path - else: - raise Exception('Unknown expResult type or missing content') - -def generate_yolox_inference_exp(training_id, options=None, use_base_config=False): - """Generate inference exp.py using DB values - - Args: - training_id: The training/project_details ID - options: Optional overrides for data paths - use_base_config: If True, load base config and only override with user-defined values - """ - if options is None: - options = {} - - training = Training.query.get(training_id) - if not training: - training = Training.query.filter_by(project_details_id=training_id).first() - - if not training: - raise Exception(f'Training not found for trainingId or project_details_id: {training_id}') - - # Always use the training_id (project_details_id) for annotation file names - project_details_id = training.project_details_id - - data_dir = options.get('data_dir', '/home/kitraining/To_Annotate/') - train_ann = options.get('train_ann', f'coco_project_{training_id}_train.json') - val_ann = options.get('val_ann', f'coco_project_{training_id}_valid.json') - test_ann = options.get('test_ann', f'coco_project_{training_id}_test.json') - - # Get num_classes from TrainingProject.classes JSON - num_classes = 80 - try: - training_project = TrainingProject.query.get(project_details_id) - if training_project and training_project.classes: - classes_arr = training_project.classes - if isinstance(classes_arr, str): - import json - classes_arr = json.loads(classes_arr) - - if isinstance(classes_arr, list): - num_classes = len([c for c in classes_arr if c not in [None, '']]) - elif isinstance(classes_arr, dict): - num_classes = len([k for k, v in classes_arr.items() if v not in [None, '']]) - except Exception as e: - print(f'Could not determine num_classes from TrainingProject.classes: {e}') - - # Initialize config dictionary - config = {} - - # If using base config (transfer learning from COCO), load protected parameters first - if use_base_config and training.selected_model: - try: - base_config = load_base_config(training.selected_model) - config.update(base_config) - print(f'Loaded base config for {training.selected_model}: {list(base_config.keys())}') - except Exception as e: - print(f'Warning: Could not load base config for {training.selected_model}: {e}') - print('Falling back to custom settings only') - - # Override with user-defined values from training table (only if they exist and are not None) - user_overrides = { - 'depth': training.depth, - 'width': training.width, - 'input_size': training.input_size, - 'mosaic_scale': training.mosaic_scale, - 'test_size': training.test_size, - 'enable_mixup': training.enable_mixup, - 'max_epoch': training.max_epoch, - 'warmup_epochs': training.warmup_epochs, - 'warmup_lr': training.warmup_lr, - 'basic_lr_per_img': training.basic_lr_per_img, - 'scheduler': training.scheduler, - 'no_aug_epochs': training.no_aug_epochs, - 'min_lr_ratio': training.min_lr_ratio, - 'ema': training.ema, - 'weight_decay': training.weight_decay, - 'momentum': training.momentum, - 'print_interval': training.print_interval, - 'eval_interval': training.eval_interval, - 'test_conf': training.test_conf, - 'nms_thre': training.nms_thre, - 'mosaic_prob': training.mosaic_prob, - 'mixup_prob': training.mixup_prob, - 'hsv_prob': training.hsv_prob, - 'flip_prob': training.flip_prob, - 'degrees': training.degrees, - 'translate': training.translate, - 'shear': training.shear, - 'mixup_scale': training.mixup_scale, - 'activation': training.activation, - } - - # Only override if value is explicitly set (not None) - for key, value in user_overrides.items(): - if value is not None: - config[key] = value - - # Apply any additional options overrides - config.update(options) - - # Set defaults for any missing required parameters - config.setdefault('depth', 1.00) - config.setdefault('width', 1.00) - config.setdefault('input_size', [640, 640]) - config.setdefault('mosaic_scale', [0.1, 2]) - config.setdefault('random_size', [10, 20]) - config.setdefault('test_size', [640, 640]) - config.setdefault('enable_mixup', False) - config.setdefault('exp_name', 'inference_exp') - - # Build exp content - exp_content = f'''#!/usr/bin/env python3 -# -*- coding:utf-8 -*- -# Copyright (c) Megvii, Inc. and its affiliates. - -import os - -from yolox.exp import Exp as MyExp - - -class Exp(MyExp): - def __init__(self): - super(Exp, self).__init__() - self.data_dir = "{data_dir}" - self.train_ann = "{train_ann}" - self.val_ann = "{val_ann}" - self.test_ann = "{test_ann}" - self.num_classes = {num_classes} -''' - - # Set pretrained_ckpt if transfer_learning is 'coco' - if training.transfer_learning and isinstance(training.transfer_learning, str) and training.transfer_learning.lower() == 'coco': - yolox_base_dir = '/home/kitraining/Yolox/YOLOX-main' - selected_model = training.selected_model.replace('.pth', '') if training.selected_model else '' - if selected_model: - exp_content += f" self.pretrained_ckpt = r'{yolox_base_dir}/pretrained/{selected_model}.pth'\n" - - # Format arrays - def format_value(val): - if isinstance(val, (list, tuple)): - return '(' + ', '.join(map(str, val)) + ')' - elif isinstance(val, bool): - return str(val) - elif isinstance(val, str): - return f'"{val}"' - else: - return str(val) - - # Add all config parameters to exp - for key, value in config.items(): - if key not in ['exp_name']: # exp_name is handled separately - exp_content += f" self.{key} = {format_value(value)}\n" - - # Add exp_name at the end (uses dynamic path) - exp_content += f''' self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] -''' - - return exp_content - -def save_yolox_inference_exp(training_id, out_path, options=None): - """Save inference exp.py to custom path""" - exp_content = generate_yolox_inference_exp(training_id, options, use_base_config=False) - with open(out_path, 'w') as f: - f.write(exp_content) - return out_path +import os +import shutil +import importlib.util +from models.training import Training +from models.TrainingProject import TrainingProject + +def load_base_config(selected_model): + """Load base configuration for a specific YOLOX model""" + model_name = selected_model.lower().replace('-', '_').replace('.pth', '') + base_config_path = os.path.join(os.path.dirname(__file__), '..', 'data', f'{model_name}.py') + + if not os.path.exists(base_config_path): + raise Exception(f'Base configuration not found for model: {model_name} at {base_config_path}') + + # Load the module dynamically + spec = importlib.util.spec_from_file_location(f"base_config_{model_name}", base_config_path) + module = importlib.util.module_from_spec(spec) + spec.loader.exec_module(module) + + # Extract all attributes from BaseExp class + base_exp = module.BaseExp() + base_config = {} + for attr in dir(base_exp): + if not attr.startswith('_'): + base_config[attr] = getattr(base_exp, attr) + + return base_config + +def generate_yolox_exp(training_id): + """Generate YOLOX exp.py file""" + # Fetch training row from DB + training = Training.query.get(training_id) + if not training: + training = Training.query.filter_by(project_details_id=training_id).first() + + if not training: + raise Exception(f'Training not found for trainingId or project_details_id: {training_id}') + + # If transfer_learning is 'coco', generate exp using base config + custom settings + if training.transfer_learning == 'coco': + exp_content = generate_yolox_inference_exp(training_id, use_base_config=True) + return {'type': 'custom', 'expContent': exp_content} + + # If transfer_learning is 'sketch', generate custom exp.py + if training.transfer_learning == 'sketch': + exp_content = generate_yolox_inference_exp(training_id, use_base_config=False) + return {'type': 'custom', 'expContent': exp_content} + + raise Exception(f'Unknown transfer_learning type: {training.transfer_learning}') + +def save_yolox_exp(training_id, out_path): + """Save YOLOX exp.py to specified path""" + exp_result = generate_yolox_exp(training_id) + + if exp_result['type'] == 'custom' and 'expContent' in exp_result: + with open(out_path, 'w') as f: + f.write(exp_result['expContent']) + return out_path + elif exp_result['type'] == 'default' and 'expPath' in exp_result: + # Optionally copy the file if outPath is different + if exp_result['expPath'] != out_path: + shutil.copyfile(exp_result['expPath'], out_path) + return out_path + else: + raise Exception('Unknown expResult type or missing content') + +def generate_yolox_inference_exp(training_id, options=None, use_base_config=False): + """Generate inference exp.py using DB values + + Args: + training_id: The training/project_details ID + options: Optional overrides for data paths + use_base_config: If True, load base config and only override with user-defined values + """ + if options is None: + options = {} + + training = Training.query.get(training_id) + if not training: + training = Training.query.filter_by(project_details_id=training_id).first() + + if not training: + raise Exception(f'Training not found for trainingId or project_details_id: {training_id}') + + # Always use the project_details_id for annotation file names and paths + project_details_id = training.project_details_id + + # Get annotation file names from options or use defaults + # Use training.id (not project_details_id) for consistency with generate_training_json + train_ann = options.get('train_ann', f'coco_project_{training_id}_train.json') + val_ann = options.get('val_ann', f'coco_project_{training_id}_valid.json') + test_ann = options.get('test_ann', f'coco_project_{training_id}_test.json') + + # Get data_dir - this should point to where IMAGES are located (not annotations) + # YOLOX will combine data_dir + file_name from COCO JSON to find images + # The annotations are in a separate location (output folder) + from services.settings_service import get_setting + from models.TrainingProjectDetails import TrainingProjectDetails + + if 'data_dir' in options: + data_dir = options['data_dir'] + else: + # Use the yolox_data_dir setting - this is where training images are stored + data_dir = get_setting('yolox_data_dir', '/home/kitraining/To_Annotate/') + # Ensure it ends with a separator + if not data_dir.endswith(os.sep) and not data_dir.endswith('/'): + data_dir += os.sep + + # Get num_classes from ProjectClass table (3NF) + num_classes = 80 + try: + from models.ProjectClass import ProjectClass + training_project = TrainingProject.query.get(project_details_id) + if training_project: + # Count classes from ProjectClass table + class_count = ProjectClass.query.filter_by(project_id=training_project.project_id).count() + if class_count > 0: + num_classes = class_count + except Exception as e: + print(f'Could not determine num_classes from ProjectClass: {e}') + + # Initialize config dictionary + config = {} + + # If using base config (transfer learning from COCO), load protected parameters first + if use_base_config and training.selected_model: + try: + base_config = load_base_config(training.selected_model) + config.update(base_config) + print(f'Loaded base config for {training.selected_model}: {list(base_config.keys())}') + except Exception as e: + print(f'Warning: Could not load base config for {training.selected_model}: {e}') + print('Falling back to custom settings only') + + # Get size arrays from TrainingSize table (3NF) + from models.TrainingSize import TrainingSize + + def get_size_array(training_id, size_type): + """Helper to get size array from TrainingSize table""" + sizes = TrainingSize.query.filter_by( + training_id=training_id, + size_type=size_type + ).order_by(TrainingSize.value_order).all() + return [s.value for s in sizes] if sizes else None + + input_size = get_size_array(training.id, 'input_size') + test_size = get_size_array(training.id, 'test_size') + mosaic_scale = get_size_array(training.id, 'mosaic_scale') + mixup_scale = get_size_array(training.id, 'mixup_scale') + + # Override with user-defined values from training table (only if they exist and are not None) + user_overrides = { + 'depth': training.depth, + 'width': training.width, + 'input_size': input_size, + 'mosaic_scale': mosaic_scale, + 'test_size': test_size, + 'enable_mixup': training.enable_mixup, + 'max_epoch': training.max_epoch, + 'warmup_epochs': training.warmup_epochs, + 'warmup_lr': training.warmup_lr, + 'basic_lr_per_img': training.basic_lr_per_img, + 'scheduler': training.scheduler, + 'no_aug_epochs': training.no_aug_epochs, + 'min_lr_ratio': training.min_lr_ratio, + 'ema': training.ema, + 'weight_decay': training.weight_decay, + 'momentum': training.momentum, + 'print_interval': training.print_interval, + 'eval_interval': training.eval_interval, + 'test_conf': training.test_conf, + 'nms_thre': training.nms_thre, + 'mosaic_prob': training.mosaic_prob, + 'mixup_prob': training.mixup_prob, + 'hsv_prob': training.hsv_prob, + 'flip_prob': training.flip_prob, + # Convert single values to tuples for YOLOX augmentation parameters + 'degrees': (training.degrees, training.degrees) if training.degrees is not None and not isinstance(training.degrees, (list, tuple)) else training.degrees, + 'translate': (training.translate, training.translate) if training.translate is not None and not isinstance(training.translate, (list, tuple)) else training.translate, + 'shear': (training.shear, training.shear) if training.shear is not None and not isinstance(training.shear, (list, tuple)) else training.shear, + 'mixup_scale': mixup_scale, + 'activation': training.activation, + } + + # Only override if value is explicitly set (not None) + for key, value in user_overrides.items(): + if value is not None: + config[key] = value + + # Apply any additional options overrides + config.update(options) + + # Set defaults for any missing required parameters + config.setdefault('depth', 1.00) + config.setdefault('width', 1.00) + config.setdefault('input_size', [640, 640]) + config.setdefault('mosaic_scale', [0.1, 2]) + config.setdefault('random_size', [10, 20]) + config.setdefault('test_size', [640, 640]) + config.setdefault('enable_mixup', False) + config.setdefault('exp_name', 'inference_exp') + + # Prepare data_dir for template - escape backslashes and remove trailing separator + data_dir_clean = data_dir.rstrip('/\\') + data_dir_escaped = data_dir_clean.replace('\\', '\\\\') + + # Calculate annotations directory (where JSON files are stored) + # This is in the output folder, not with the images + from models.TrainingProjectDetails import TrainingProjectDetails + details = TrainingProjectDetails.query.get(project_details_id) + if details: + training_project = TrainingProject.query.get(details.project_id) + project_name = training_project.title.replace(' ', '_') if training_project and training_project.title else f'project_{details.project_id}' + else: + project_name = f'project_{project_details_id}' + + training_folder_name = f"{training.exp_name or training.training_name or 'training'}_{training_id}" + training_folder_name = training_folder_name.replace(' ', '_') + + output_base_path = get_setting('yolox_output_path', './backend') + annotations_parent_dir = os.path.join(output_base_path, project_name, training_folder_name) + annotations_parent_escaped = annotations_parent_dir.replace('\\', '\\\\') + + # Build exp content + exp_content = f'''#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "{data_dir_escaped}" # Where images are located + self.annotations_dir = "{annotations_parent_escaped}" # Where annotation JSONs are located + self.train_ann = "{train_ann}" + self.val_ann = "{val_ann}" + self.test_ann = "{test_ann}" + self.num_classes = {num_classes} + # Disable train2017 subdirectory - our images are directly in data_dir + self.name = "" + # Set data workers for training + self.data_num_workers = 8 +''' + + # Set pretrained_ckpt if transfer_learning is 'coco' + if training.transfer_learning and isinstance(training.transfer_learning, str) and training.transfer_learning.lower() == 'coco': + yolox_base_dir = '/home/kitraining/Yolox/YOLOX-main' + selected_model = training.selected_model.replace('.pth', '') if training.selected_model else '' + if selected_model: + exp_content += f" self.pretrained_ckpt = r'{yolox_base_dir}/pretrained/{selected_model}.pth'\n" + + # Format arrays + def format_value(val): + if isinstance(val, (list, tuple)): + # Convert float values to int for size-related parameters + formatted_items = [] + for item in val: + # Convert to int if it's a whole number float + if isinstance(item, float) and item.is_integer(): + formatted_items.append(str(int(item))) + else: + formatted_items.append(str(item)) + return '(' + ', '.join(formatted_items) + ')' + elif isinstance(val, bool): + return str(val) + elif isinstance(val, str): + return f'"{val}"' + elif isinstance(val, float) and val.is_integer(): + # Convert whole number floats to ints + return str(int(val)) + else: + return str(val) + + # Add all config parameters to exp + for key, value in config.items(): + if key not in ['exp_name']: # exp_name is handled separately + exp_content += f" self.{key} = {format_value(value)}\n" + + # Add get_dataset override using name parameter for image directory + exp_content += ''' + def get_dataset(self, cache=False, cache_type="ram"): + """Override to use name parameter for images directory""" + from yolox.data import COCODataset + + # COCODataset constructs image paths as: os.path.join(data_dir, name, file_name) + # YOLOX adds "annotations/" to data_dir automatically, so we pass annotations_dir directly + # Use empty string for name since we have absolute paths in JSON + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.train_ann, + name="", + img_size=self.input_size, + preproc=self.preproc if hasattr(self, 'preproc') else None, + cache=cache, + cache_type=cache_type, + ) + + def get_eval_dataset(self, **kwargs): + """Override eval dataset using name parameter""" + from yolox.data import COCODataset + + testdev = kwargs.get("testdev", False) + legacy = kwargs.get("legacy", False) + + return COCODataset( + data_dir=self.annotations_dir, + json_file=self.val_ann if not testdev else self.test_ann, + name="", + img_size=self.test_size, + preproc=None, # No preprocessing for evaluation + ) +''' + + # Add exp_name at the end (uses dynamic path) + exp_content += f''' self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] +''' + + return exp_content + +def save_yolox_inference_exp(training_id, out_path, options=None): + """Save inference exp.py to custom path""" + exp_content = generate_yolox_inference_exp(training_id, options, use_base_config=False) + with open(out_path, 'w') as f: + f.write(exp_content) + return out_path diff --git a/backend/services/push-yolox-exp.js b/backend/services/push-yolox-exp.js index 6481287..e1ec2af 100644 --- a/backend/services/push-yolox-exp.js +++ b/backend/services/push-yolox-exp.js @@ -1,48 +1,48 @@ -const Training = require('../models/training.js'); -const fs = require('fs'); -const path = require('path'); - -async function pushYoloxExpToDb(settings) { - // Normalize boolean and array fields for DB - const normalized = { ...settings }; - // Map 'act' from frontend to 'activation' for DB - if (normalized.act !== undefined) { - normalized.activation = normalized.act; - delete normalized.act; - } - // Convert 'on'/'off' to boolean for save_history_ckpt - if (typeof normalized.save_history_ckpt === 'string') { - normalized.save_history_ckpt = normalized.save_history_ckpt === 'on' ? true : false; - } - // Convert comma-separated strings to arrays for input_size, test_size, mosaic_scale, mixup_scale - ['input_size', 'test_size', 'mosaic_scale', 'mixup_scale'].forEach(key => { - if (typeof normalized[key] === 'string') { - const arr = normalized[key].split(',').map(v => parseFloat(v.trim())); - normalized[key] = arr.length === 1 ? arr[0] : arr; - } - }); - // Find TrainingProjectDetails for this project - const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); - const details = await TrainingProjectDetails.findOne({ where: { project_id: normalized.project_id } }); - if (!details) throw new Error('TrainingProjectDetails not found for project_id ' + normalized.project_id); - normalized.project_details_id = details.id; - // Create DB row - const training = await Training.create(normalized); - return training; -} - -async function generateYoloxExpFromDb(trainingId) { - // Fetch training row from DB - const training = await Training.findByPk(trainingId); - if (!training) throw new Error('Training not found'); - // Template for exp.py - const expTemplate = `#!/usr/bin/env python3\n# Copyright (c) Megvii Inc. All rights reserved.\n\nimport os\nimport random\n\nimport torch\nimport torch.distributed as dist\nimport torch.nn as nn\n\nfrom .base_exp import BaseExp\n\n__all__ = [\"Exp\", \"check_exp_value\"]\n\nclass Exp(BaseExp):\n def __init__(self):\n super().__init__()\n\n # ---------------- model config ---------------- #\n self.num_classes = ${training.num_classes || 80}\n self.depth = ${training.depth || 1.00}\n self.width = ${training.width || 1.00}\n self.act = \"${training.activation || training.act || 'silu'}\"\n\n # ---------------- dataloader config ---------------- #\n self.data_num_workers = ${training.data_num_workers || 4}\n self.input_size = (${Array.isArray(training.input_size) ? training.input_size.join(', ') : '640, 640'})\n self.multiscale_range = ${training.multiscale_range || 5}\n self.data_dir = ${training.data_dir ? `\"${training.data_dir}\"` : 'None'}\n self.train_ann = \"${training.train_ann || 'instances_train2017.json'}\"\n self.val_ann = \"${training.val_ann || 'instances_val2017.json'}\"\n self.test_ann = \"${training.test_ann || 'instances_test2017.json'}\"\n\n # --------------- transform config ----------------- #\n self.mosaic_prob = ${training.mosaic_prob !== undefined ? training.mosaic_prob : 1.0}\n self.mixup_prob = ${training.mixup_prob !== undefined ? training.mixup_prob : 1.0}\n self.hsv_prob = ${training.hsv_prob !== undefined ? training.hsv_prob : 1.0}\n self.flip_prob = ${training.flip_prob !== undefined ? training.flip_prob : 0.5}\n self.degrees = ${training.degrees !== undefined ? training.degrees : 10.0}\n self.translate = ${training.translate !== undefined ? training.translate : 0.1}\n self.mosaic_scale = (${Array.isArray(training.mosaic_scale) ? training.mosaic_scale.join(', ') : '0.1, 2'})\n self.enable_mixup = ${training.enable_mixup !== undefined ? training.enable_mixup : true}\n self.mixup_scale = (${Array.isArray(training.mixup_scale) ? training.mixup_scale.join(', ') : '0.5, 1.5'})\n self.shear = ${training.shear !== undefined ? training.shear : 2.0}\n\n # -------------- training config --------------------- #\n self.warmup_epochs = ${training.warmup_epochs !== undefined ? training.warmup_epochs : 5}\n self.max_epoch = ${training.max_epoch !== undefined ? training.max_epoch : 300}\n self.warmup_lr = ${training.warmup_lr !== undefined ? training.warmup_lr : 0}\n self.min_lr_ratio = ${training.min_lr_ratio !== undefined ? training.min_lr_ratio : 0.05}\n self.basic_lr_per_img = ${training.basic_lr_per_img !== undefined ? training.basic_lr_per_img : 0.01 / 64.0}\n self.scheduler = \"${training.scheduler || 'yoloxwarmcos'}\"\n self.no_aug_epochs = ${training.no_aug_epochs !== undefined ? training.no_aug_epochs : 15}\n self.ema = ${training.ema !== undefined ? training.ema : true}\n self.weight_decay = ${training.weight_decay !== undefined ? training.weight_decay : 5e-4}\n self.momentum = ${training.momentum !== undefined ? training.momentum : 0.9}\n self.print_interval = ${training.print_interval !== undefined ? training.print_interval : 10}\n self.eval_interval = ${training.eval_interval !== undefined ? training.eval_interval : 10}\n self.save_history_ckpt = ${training.save_history_ckpt !== undefined ? training.save_history_ckpt : true}\n self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(\".\")[0]\n\n # ----------------- testing config ------------------ #\n self.test_size = (${Array.isArray(training.test_size) ? training.test_size.join(', ') : '640, 640'})\n self.test_conf = ${training.test_conf !== undefined ? training.test_conf : 0.01}\n self.nmsthre = ${training.nmsthre !== undefined ? training.nmsthre : 0.65}\n\n # ... rest of the template ...\n\ndef check_exp_value(exp: Exp):\n h, w = exp.input_size\n assert h % 32 == 0 and w % 32 == 0, \"input size must be multiples of 32\"\n`; - // Save to file in output directory - const outDir = path.join(__dirname, '../../', training.project_id ? `project_${training.project_id}/${trainingId}` : 'exp_files'); - if (!fs.existsSync(outDir)) fs.mkdirSync(outDir, { recursive: true }); - const filePath = path.join(outDir, 'exp.py'); - fs.writeFileSync(filePath, expTemplate); - return filePath; -} - +const Training = require('../models/training.js'); +const fs = require('fs'); +const path = require('path'); + +async function pushYoloxExpToDb(settings) { + // Normalize boolean and array fields for DB + const normalized = { ...settings }; + // Map 'act' from frontend to 'activation' for DB + if (normalized.act !== undefined) { + normalized.activation = normalized.act; + delete normalized.act; + } + // Convert 'on'/'off' to boolean for save_history_ckpt + if (typeof normalized.save_history_ckpt === 'string') { + normalized.save_history_ckpt = normalized.save_history_ckpt === 'on' ? true : false; + } + // Convert comma-separated strings to arrays for input_size, test_size, mosaic_scale, mixup_scale + ['input_size', 'test_size', 'mosaic_scale', 'mixup_scale'].forEach(key => { + if (typeof normalized[key] === 'string') { + const arr = normalized[key].split(',').map(v => parseFloat(v.trim())); + normalized[key] = arr.length === 1 ? arr[0] : arr; + } + }); + // Find TrainingProjectDetails for this project + const TrainingProjectDetails = require('../models/TrainingProjectDetails.js'); + const details = await TrainingProjectDetails.findOne({ where: { project_id: normalized.project_id } }); + if (!details) throw new Error('TrainingProjectDetails not found for project_id ' + normalized.project_id); + normalized.project_details_id = details.id; + // Create DB row + const training = await Training.create(normalized); + return training; +} + +async function generateYoloxExpFromDb(trainingId) { + // Fetch training row from DB + const training = await Training.findByPk(trainingId); + if (!training) throw new Error('Training not found'); + // Template for exp.py + const expTemplate = `#!/usr/bin/env python3\n# Copyright (c) Megvii Inc. All rights reserved.\n\nimport os\nimport random\n\nimport torch\nimport torch.distributed as dist\nimport torch.nn as nn\n\nfrom .base_exp import BaseExp\n\n__all__ = [\"Exp\", \"check_exp_value\"]\n\nclass Exp(BaseExp):\n def __init__(self):\n super().__init__()\n\n # ---------------- model config ---------------- #\n self.num_classes = ${training.num_classes || 80}\n self.depth = ${training.depth || 1.00}\n self.width = ${training.width || 1.00}\n self.act = \"${training.activation || training.act || 'silu'}\"\n\n # ---------------- dataloader config ---------------- #\n self.data_num_workers = ${training.data_num_workers || 4}\n self.input_size = (${Array.isArray(training.input_size) ? training.input_size.join(', ') : '640, 640'})\n self.multiscale_range = ${training.multiscale_range || 5}\n self.data_dir = ${training.data_dir ? `\"${training.data_dir}\"` : 'None'}\n self.train_ann = \"${training.train_ann || 'instances_train2017.json'}\"\n self.val_ann = \"${training.val_ann || 'instances_val2017.json'}\"\n self.test_ann = \"${training.test_ann || 'instances_test2017.json'}\"\n\n # --------------- transform config ----------------- #\n self.mosaic_prob = ${training.mosaic_prob !== undefined ? training.mosaic_prob : 1.0}\n self.mixup_prob = ${training.mixup_prob !== undefined ? training.mixup_prob : 1.0}\n self.hsv_prob = ${training.hsv_prob !== undefined ? training.hsv_prob : 1.0}\n self.flip_prob = ${training.flip_prob !== undefined ? training.flip_prob : 0.5}\n self.degrees = ${training.degrees !== undefined ? training.degrees : 10.0}\n self.translate = ${training.translate !== undefined ? training.translate : 0.1}\n self.mosaic_scale = (${Array.isArray(training.mosaic_scale) ? training.mosaic_scale.join(', ') : '0.1, 2'})\n self.enable_mixup = ${training.enable_mixup !== undefined ? training.enable_mixup : true}\n self.mixup_scale = (${Array.isArray(training.mixup_scale) ? training.mixup_scale.join(', ') : '0.5, 1.5'})\n self.shear = ${training.shear !== undefined ? training.shear : 2.0}\n\n # -------------- training config --------------------- #\n self.warmup_epochs = ${training.warmup_epochs !== undefined ? training.warmup_epochs : 5}\n self.max_epoch = ${training.max_epoch !== undefined ? training.max_epoch : 300}\n self.warmup_lr = ${training.warmup_lr !== undefined ? training.warmup_lr : 0}\n self.min_lr_ratio = ${training.min_lr_ratio !== undefined ? training.min_lr_ratio : 0.05}\n self.basic_lr_per_img = ${training.basic_lr_per_img !== undefined ? training.basic_lr_per_img : 0.01 / 64.0}\n self.scheduler = \"${training.scheduler || 'yoloxwarmcos'}\"\n self.no_aug_epochs = ${training.no_aug_epochs !== undefined ? training.no_aug_epochs : 15}\n self.ema = ${training.ema !== undefined ? training.ema : true}\n self.weight_decay = ${training.weight_decay !== undefined ? training.weight_decay : 5e-4}\n self.momentum = ${training.momentum !== undefined ? training.momentum : 0.9}\n self.print_interval = ${training.print_interval !== undefined ? training.print_interval : 10}\n self.eval_interval = ${training.eval_interval !== undefined ? training.eval_interval : 10}\n self.save_history_ckpt = ${training.save_history_ckpt !== undefined ? training.save_history_ckpt : true}\n self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(\".\")[0]\n\n # ----------------- testing config ------------------ #\n self.test_size = (${Array.isArray(training.test_size) ? training.test_size.join(', ') : '640, 640'})\n self.test_conf = ${training.test_conf !== undefined ? training.test_conf : 0.01}\n self.nmsthre = ${training.nmsthre !== undefined ? training.nmsthre : 0.65}\n\n # ... rest of the template ...\n\ndef check_exp_value(exp: Exp):\n h, w = exp.input_size\n assert h % 32 == 0 and w % 32 == 0, \"input size must be multiples of 32\"\n`; + // Save to file in output directory + const outDir = path.join(__dirname, '../../', training.project_id ? `project_${training.project_id}/${trainingId}` : 'exp_files'); + if (!fs.existsSync(outDir)) fs.mkdirSync(outDir, { recursive: true }); + const filePath = path.join(outDir, 'exp.py'); + fs.writeFileSync(filePath, expTemplate); + return filePath; +} + module.exports = { pushYoloxExpToDb, generateYoloxExpFromDb }; \ No newline at end of file diff --git a/backend/services/push_yolox_exp.py b/backend/services/push_yolox_exp.py index 8cc5e76..e4505c8 100644 --- a/backend/services/push_yolox_exp.py +++ b/backend/services/push_yolox_exp.py @@ -1,92 +1,113 @@ -from models.training import Training -from models.TrainingProjectDetails import TrainingProjectDetails -from database.database import db - -def push_yolox_exp_to_db(settings): - """Save YOLOX settings to database""" - normalized = dict(settings) - - # Map common frontend aliases to DB column names - alias_map = { - 'act': 'activation', - 'nmsthre': 'nms_thre', - 'select_model': 'selected_model' - } - for a, b in alias_map.items(): - if a in normalized and b not in normalized: - normalized[b] = normalized.pop(a) - - # Convert 'on'/'off' or 'true'/'false' strings to boolean for known boolean fields - for bool_field in ['save_history_ckpt', 'ema', 'enable_mixup']: - if bool_field in normalized: - val = normalized[bool_field] - if isinstance(val, str): - normalized[bool_field] = val.lower() in ('1', 'true', 'on') - else: - normalized[bool_field] = bool(val) - - # Convert comma-separated strings to arrays for JSON fields - for key in ['input_size', 'test_size', 'mosaic_scale', 'mixup_scale']: - if key in normalized and isinstance(normalized[key], str): - parts = [p.strip() for p in normalized[key].split(',') if p.strip()] - try: - arr = [float(p) for p in parts] - except Exception: - arr = parts - normalized[key] = arr[0] if len(arr) == 1 else arr - - # Ensure we have a TrainingProjectDetails row for project_id - project_id = normalized.get('project_id') - if not project_id: - raise Exception('Missing project_id in settings') - details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() - if not details: - raise Exception(f'TrainingProjectDetails not found for project_id {project_id}') - normalized['project_details_id'] = details.id - - # Filter normalized to only columns that exist on the Training model - valid_cols = {c.name: c for c in Training.__table__.columns} - filtered = {} - for k, v in normalized.items(): - if k in valid_cols: - col_type = valid_cols[k].type.__class__.__name__ - # Try to coerce types for numeric/boolean columns - try: - if 'Integer' in col_type: - if v is None or v == '': - filtered[k] = None - else: - filtered[k] = int(float(v)) - elif 'Float' in col_type: - if v is None or v == '': - filtered[k] = None - else: - filtered[k] = float(v) - elif 'Boolean' in col_type: - if isinstance(v, str): - filtered[k] = v.lower() in ('1', 'true', 'on') - else: - filtered[k] = bool(v) - elif 'JSON' in col_type: - filtered[k] = v - elif 'LargeBinary' in col_type: - # If a file path was passed, store its bytes; otherwise store raw bytes - if isinstance(v, str): - try: - filtered[k] = v.encode('utf-8') - except Exception: - filtered[k] = None - else: - filtered[k] = v - else: - filtered[k] = v - except Exception: - # If conversion fails, just assign raw value - filtered[k] = v - - # Create DB row - training = Training(**filtered) - db.session.add(training) - db.session.commit() - - return training +from models.training import Training +from models.TrainingProjectDetails import TrainingProjectDetails +from models.TrainingSize import TrainingSize +from database.database import db + +def push_yolox_exp_to_db(settings): + """Save YOLOX settings to database""" + normalized = dict(settings) + + # Map common frontend aliases to DB column names + alias_map = { + 'act': 'activation', + 'nmsthre': 'nms_thre', + 'select_model': 'selected_model' + } + for a, b in alias_map.items(): + if a in normalized and b not in normalized: + normalized[b] = normalized.pop(a) + + # Convert 'on'/'off' or 'true'/'false' strings to boolean for known boolean fields + for bool_field in ['save_history_ckpt', 'ema', 'enable_mixup']: + if bool_field in normalized: + val = normalized[bool_field] + if isinstance(val, str): + normalized[bool_field] = val.lower() in ('1', 'true', 'on') + else: + normalized[bool_field] = bool(val) + + # Extract size arrays for separate TrainingSize table (3NF) + size_arrays = {} + for key in ['input_size', 'test_size', 'mosaic_scale', 'mixup_scale']: + if key in normalized: + if isinstance(normalized[key], str): + parts = [p.strip() for p in normalized[key].split(',') if p.strip()] + try: + arr = [float(p) for p in parts] + except Exception: + arr = parts + size_arrays[key] = arr[0] if len(arr) == 1 else (arr if isinstance(arr, list) else [arr]) + elif isinstance(normalized[key], list): + size_arrays[key] = normalized[key] + elif normalized[key] is not None: + size_arrays[key] = [float(normalized[key])] + # Remove from normalized dict since it won't be stored in training table + del normalized[key] + + # Ensure we have a TrainingProjectDetails row for project_id + project_id = normalized.get('project_id') + if not project_id: + raise Exception('Missing project_id in settings') + details = TrainingProjectDetails.query.filter_by(project_id=project_id).first() + if not details: + raise Exception(f'TrainingProjectDetails not found for project_id {project_id}') + normalized['project_details_id'] = details.id + + # Filter normalized to only columns that exist on the Training model + valid_cols = {c.name: c for c in Training.__table__.columns} + filtered = {} + for k, v in normalized.items(): + if k in valid_cols: + col_type = valid_cols[k].type.__class__.__name__ + # Try to coerce types for numeric/boolean columns + try: + if 'Integer' in col_type: + if v is None or v == '': + filtered[k] = None + else: + filtered[k] = int(float(v)) + elif 'Float' in col_type: + if v is None or v == '': + filtered[k] = None + else: + filtered[k] = float(v) + elif 'Boolean' in col_type: + if isinstance(v, str): + filtered[k] = v.lower() in ('1', 'true', 'on') + else: + filtered[k] = bool(v) + elif 'LargeBinary' in col_type: + # If a file path was passed, store its bytes; otherwise store raw bytes + if isinstance(v, str): + try: + filtered[k] = v.encode('utf-8') + except Exception: + filtered[k] = None + else: + filtered[k] = v + else: + filtered[k] = v + except Exception: + # If conversion fails, just assign raw value + filtered[k] = v + + # Create DB row + training = Training(**filtered) + db.session.add(training) + db.session.flush() # Get training.id + + # Save size arrays to TrainingSize table (3NF) + for size_type, values in size_arrays.items(): + if values and isinstance(values, list): + for order, value in enumerate(values): + size_record = TrainingSize( + training_id=training.id, + size_type=size_type, + value_order=order, + value=float(value) + ) + db.session.add(size_record) + + db.session.commit() + + return training diff --git a/backend/services/seed-label-studio.js b/backend/services/seed-label-studio.js index fe6e545..25fa93e 100644 --- a/backend/services/seed-label-studio.js +++ b/backend/services/seed-label-studio.js @@ -1,120 +1,120 @@ -const sequelize = require('../database/database.js'); -const { Project, Img, Ann } = require('../models'); -const { fetchLableStudioProject, fetchProjectIdsAndTitles } = require('./fetch-labelstudio.js'); - -const updateStatus = { running: false }; - -async function seedLabelStudio() { - updateStatus.running = true; - console.log('Seeding started'); - try { - await sequelize.sync(); - const projects = await fetchProjectIdsAndTitles(); - - for (const project of projects) { - console.log(`Processing project ${project.id} (${project.title})`); - - // Upsert project in DB - await Project.upsert({ project_id: project.id, title: project.title }); - - // Fetch project data (annotations array) - const data = await fetchLableStudioProject(project.id); - if (!Array.isArray(data) || data.length === 0) { - console.log(`No annotation data for project ${project.id}`); - continue; - } - - // Remove old images and annotations for this project - const oldImages = await Img.findAll({ where: { project_id: project.id } }); - const oldImageIds = oldImages.map(img => img.image_id); - if (oldImageIds.length > 0) { - await Ann.destroy({ where: { image_id: oldImageIds } }); - await Img.destroy({ where: { project_id: project.id } }); - console.log(`Deleted ${oldImageIds.length} old images and their annotations for project ${project.id}`); - } - - // Prepare arrays - const imagesBulk = []; - const annsBulk = []; - - for (const ann of data) { - // Extract width/height - let width = null; - let height = null; - if (Array.isArray(ann.label_rectangles) && ann.label_rectangles.length > 0) { - width = ann.label_rectangles[0].original_width; - height = ann.label_rectangles[0].original_height; - } else if (Array.isArray(ann.label) && ann.label.length > 0 && ann.label[0].original_width && ann.label[0].original_height) { - width = ann.label[0].original_width; - height = ann.label[0].original_height; - } - - // Only push image and annotations if width and height are valid - if (width && height) { - imagesBulk.push({ - project_id: project.id, - image_path: ann.image, - width, - height - }); - - // Handle multiple annotations per image - if (Array.isArray(ann.label_rectangles)) { - for (const ann_detail of ann.label_rectangles) { - annsBulk.push({ - image_path: ann.image, - x: (ann_detail.x * width) / 100, - y: (ann_detail.y * height) / 100, - width: (ann_detail.width * width) / 100, - height: (ann_detail.height * height) / 100, - Label: Array.isArray(ann_detail.rectanglelabels) ? (ann_detail.rectanglelabels[0] || 'unknown') : (ann_detail.rectanglelabels || 'unknown') - }); - } - } else if (Array.isArray(ann.label)) { - for (const ann_detail of ann.label) { - annsBulk.push({ - image_path: ann.image, - x: (ann_detail.x * width) / 100, - y: (ann_detail.y * height) / 100, - width: (ann_detail.width * width) / 100, - height: (ann_detail.height * height) / 100, - Label: Array.isArray(ann_detail.rectanglelabels) ? (ann_detail.rectanglelabels[0] || 'unknown') : (ann_detail.rectanglelabels || 'unknown') - }); - } - } - } - } - - // 1) Insert images and get generated IDs - const insertedImages = await Img.bulkCreate(imagesBulk, { returning: true }); - - // 2) Map image_path -> image_id - const imageMap = {}; - for (const img of insertedImages) { - imageMap[img.image_path] = img.image_id; - } - - // 3) Assign correct image_id to each annotation - for (const ann of annsBulk) { - ann.image_id = imageMap[ann.image_path]; - delete ann.image_path; // cleanup - } - - // 4) Insert annotations - await Ann.bulkCreate(annsBulk); - - console.log(`Inserted ${imagesBulk.length} images and ${annsBulk.length} annotations for project ${project.id}`); - } - - console.log('Seeding done'); - return { success: true, message: 'Data inserted successfully!' }; - } catch (error) { - console.error('Error inserting data:', error); - return { success: false, message: error.message }; - } finally { - updateStatus.running = false; - console.log('updateStatus.running set to false'); - } -} - -module.exports = { seedLabelStudio, updateStatus }; +const sequelize = require('../database/database.js'); +const { Project, Img, Ann } = require('../models'); +const { fetchLableStudioProject, fetchProjectIdsAndTitles } = require('./fetch-labelstudio.js'); + +const updateStatus = { running: false }; + +async function seedLabelStudio() { + updateStatus.running = true; + console.log('Seeding started'); + try { + await sequelize.sync(); + const projects = await fetchProjectIdsAndTitles(); + + for (const project of projects) { + console.log(`Processing project ${project.id} (${project.title})`); + + // Upsert project in DB + await Project.upsert({ project_id: project.id, title: project.title }); + + // Fetch project data (annotations array) + const data = await fetchLableStudioProject(project.id); + if (!Array.isArray(data) || data.length === 0) { + console.log(`No annotation data for project ${project.id}`); + continue; + } + + // Remove old images and annotations for this project + const oldImages = await Img.findAll({ where: { project_id: project.id } }); + const oldImageIds = oldImages.map(img => img.image_id); + if (oldImageIds.length > 0) { + await Ann.destroy({ where: { image_id: oldImageIds } }); + await Img.destroy({ where: { project_id: project.id } }); + console.log(`Deleted ${oldImageIds.length} old images and their annotations for project ${project.id}`); + } + + // Prepare arrays + const imagesBulk = []; + const annsBulk = []; + + for (const ann of data) { + // Extract width/height + let width = null; + let height = null; + if (Array.isArray(ann.label_rectangles) && ann.label_rectangles.length > 0) { + width = ann.label_rectangles[0].original_width; + height = ann.label_rectangles[0].original_height; + } else if (Array.isArray(ann.label) && ann.label.length > 0 && ann.label[0].original_width && ann.label[0].original_height) { + width = ann.label[0].original_width; + height = ann.label[0].original_height; + } + + // Only push image and annotations if width and height are valid + if (width && height) { + imagesBulk.push({ + project_id: project.id, + image_path: ann.image, + width, + height + }); + + // Handle multiple annotations per image + if (Array.isArray(ann.label_rectangles)) { + for (const ann_detail of ann.label_rectangles) { + annsBulk.push({ + image_path: ann.image, + x: (ann_detail.x * width) / 100, + y: (ann_detail.y * height) / 100, + width: (ann_detail.width * width) / 100, + height: (ann_detail.height * height) / 100, + Label: Array.isArray(ann_detail.rectanglelabels) ? (ann_detail.rectanglelabels[0] || 'unknown') : (ann_detail.rectanglelabels || 'unknown') + }); + } + } else if (Array.isArray(ann.label)) { + for (const ann_detail of ann.label) { + annsBulk.push({ + image_path: ann.image, + x: (ann_detail.x * width) / 100, + y: (ann_detail.y * height) / 100, + width: (ann_detail.width * width) / 100, + height: (ann_detail.height * height) / 100, + Label: Array.isArray(ann_detail.rectanglelabels) ? (ann_detail.rectanglelabels[0] || 'unknown') : (ann_detail.rectanglelabels || 'unknown') + }); + } + } + } + } + + // 1) Insert images and get generated IDs + const insertedImages = await Img.bulkCreate(imagesBulk, { returning: true }); + + // 2) Map image_path -> image_id + const imageMap = {}; + for (const img of insertedImages) { + imageMap[img.image_path] = img.image_id; + } + + // 3) Assign correct image_id to each annotation + for (const ann of annsBulk) { + ann.image_id = imageMap[ann.image_path]; + delete ann.image_path; // cleanup + } + + // 4) Insert annotations + await Ann.bulkCreate(annsBulk); + + console.log(`Inserted ${imagesBulk.length} images and ${annsBulk.length} annotations for project ${project.id}`); + } + + console.log('Seeding done'); + return { success: true, message: 'Data inserted successfully!' }; + } catch (error) { + console.error('Error inserting data:', error); + return { success: false, message: error.message }; + } finally { + updateStatus.running = false; + console.log('updateStatus.running set to false'); + } +} + +module.exports = { seedLabelStudio, updateStatus }; diff --git a/backend/services/seed_label_studio.py b/backend/services/seed_label_studio.py index e7b5a6f..be0bd93 100644 --- a/backend/services/seed_label_studio.py +++ b/backend/services/seed_label_studio.py @@ -1,149 +1,149 @@ -from database.database import db -from models.LabelStudioProject import LabelStudioProject -from models.Images import Image -from models.Annotation import Annotation -from services.fetch_labelstudio import fetch_label_studio_project, fetch_project_ids_and_titles - -update_status = {"running": False} - -def seed_label_studio(): - """Seed database with Label Studio project data""" - update_status["running"] = True - print('Seeding started') - - try: - projects = fetch_project_ids_and_titles() - - for project in projects: - print(f"Processing project {project['id']} ({project['title']})") - - # Upsert project in DB - existing_project = LabelStudioProject.query.filter_by(project_id=project['id']).first() - if existing_project: - existing_project.title = project['title'] - else: - new_project = LabelStudioProject(project_id=project['id'], title=project['title']) - db.session.add(new_project) - db.session.commit() - - # Fetch project data (annotations array) - data = fetch_label_studio_project(project['id']) - if not isinstance(data, list) or len(data) == 0: - print(f"No annotation data for project {project['id']}") - continue - - # Remove old images and annotations for this project - old_images = Image.query.filter_by(project_id=project['id']).all() - old_image_ids = [img.image_id for img in old_images] - - if old_image_ids: - Annotation.query.filter(Annotation.image_id.in_(old_image_ids)).delete(synchronize_session=False) - Image.query.filter_by(project_id=project['id']).delete() - db.session.commit() - print(f"Deleted {len(old_image_ids)} old images and their annotations for project {project['id']}") - - # Prepare arrays - images_bulk = [] - anns_bulk = [] - - for ann in data: - # Extract width/height - width = None - height = None - - if isinstance(ann.get('label_rectangles'), list) and len(ann['label_rectangles']) > 0: - width = ann['label_rectangles'][0].get('original_width') - height = ann['label_rectangles'][0].get('original_height') - elif isinstance(ann.get('label'), list) and len(ann['label']) > 0: - if ann['label'][0].get('original_width') and ann['label'][0].get('original_height'): - width = ann['label'][0]['original_width'] - height = ann['label'][0]['original_height'] - - # Only process if width and height are valid - if width and height: - image_data = { - 'project_id': project['id'], - 'image_path': ann.get('image'), - 'width': width, - 'height': height - } - images_bulk.append(image_data) - - # Handle multiple annotations per image - if isinstance(ann.get('label_rectangles'), list): - for ann_detail in ann['label_rectangles']: - # Get label safely - rectanglelabels = ann_detail.get('rectanglelabels', []) - if isinstance(rectanglelabels, list) and len(rectanglelabels) > 0: - label = rectanglelabels[0] - elif isinstance(rectanglelabels, str): - label = rectanglelabels - else: - label = 'unknown' - - ann_data = { - 'image_path': ann.get('image'), - 'x': (ann_detail['x'] * width) / 100, - 'y': (ann_detail['y'] * height) / 100, - 'width': (ann_detail['width'] * width) / 100, - 'height': (ann_detail['height'] * height) / 100, - 'Label': label - } - anns_bulk.append(ann_data) - elif isinstance(ann.get('label'), list): - for ann_detail in ann['label']: - # Get label safely - rectanglelabels = ann_detail.get('rectanglelabels', []) - if isinstance(rectanglelabels, list) and len(rectanglelabels) > 0: - label = rectanglelabels[0] - elif isinstance(rectanglelabels, str): - label = rectanglelabels - else: - label = 'unknown' - - ann_data = { - 'image_path': ann.get('image'), - 'x': (ann_detail['x'] * width) / 100, - 'y': (ann_detail['y'] * height) / 100, - 'width': (ann_detail['width'] * width) / 100, - 'height': (ann_detail['height'] * height) / 100, - 'Label': label - } - anns_bulk.append(ann_data) - - # Insert images and get generated IDs - inserted_images = [] - for img_data in images_bulk: - new_image = Image(**img_data) - db.session.add(new_image) - db.session.flush() # Flush to get the ID - inserted_images.append(new_image) - db.session.commit() - - # Map image_path -> image_id - image_map = {img.image_path: img.image_id for img in inserted_images} - - # Assign correct image_id to each annotation - for ann_data in anns_bulk: - ann_data['image_id'] = image_map.get(ann_data['image_path']) - del ann_data['image_path'] - - # Insert annotations - for ann_data in anns_bulk: - new_annotation = Annotation(**ann_data) - db.session.add(new_annotation) - db.session.commit() - - print(f"Inserted {len(images_bulk)} images and {len(anns_bulk)} annotations for project {project['id']}") - - print('Seeding done') - return {'success': True, 'message': 'Data inserted successfully!'} - - except Exception as error: - print(f'Error inserting data: {error}') - db.session.rollback() - return {'success': False, 'message': str(error)} - - finally: - update_status["running"] = False - print('updateStatus.running set to false') +from database.database import db +from models.LabelStudioProject import LabelStudioProject +from models.Images import Image +from models.Annotation import Annotation +from services.fetch_labelstudio import fetch_label_studio_project, fetch_project_ids_and_titles + +update_status = {"running": False} + +def seed_label_studio(): + """Seed database with Label Studio project data""" + update_status["running"] = True + print('Seeding started') + + try: + projects = fetch_project_ids_and_titles() + + for project in projects: + print(f"Processing project {project['id']} ({project['title']})") + + # Upsert project in DB + existing_project = LabelStudioProject.query.filter_by(project_id=project['id']).first() + if existing_project: + existing_project.title = project['title'] + else: + new_project = LabelStudioProject(project_id=project['id'], title=project['title']) + db.session.add(new_project) + db.session.commit() + + # Fetch project data (annotations array) + data = fetch_label_studio_project(project['id']) + if not isinstance(data, list) or len(data) == 0: + print(f"No annotation data for project {project['id']}") + continue + + # Remove old images and annotations for this project + old_images = Image.query.filter_by(project_id=project['id']).all() + old_image_ids = [img.image_id for img in old_images] + + if old_image_ids: + Annotation.query.filter(Annotation.image_id.in_(old_image_ids)).delete(synchronize_session=False) + Image.query.filter_by(project_id=project['id']).delete() + db.session.commit() + print(f"Deleted {len(old_image_ids)} old images and their annotations for project {project['id']}") + + # Prepare arrays + images_bulk = [] + anns_bulk = [] + + for ann in data: + # Extract width/height + width = None + height = None + + if isinstance(ann.get('label_rectangles'), list) and len(ann['label_rectangles']) > 0: + width = ann['label_rectangles'][0].get('original_width') + height = ann['label_rectangles'][0].get('original_height') + elif isinstance(ann.get('label'), list) and len(ann['label']) > 0: + if ann['label'][0].get('original_width') and ann['label'][0].get('original_height'): + width = ann['label'][0]['original_width'] + height = ann['label'][0]['original_height'] + + # Only process if width and height are valid + if width and height: + image_data = { + 'project_id': project['id'], + 'image_path': ann.get('image'), + 'width': int(width), # Ensure integer + 'height': int(height) # Ensure integer + } + images_bulk.append(image_data) + + # Handle multiple annotations per image + if isinstance(ann.get('label_rectangles'), list): + for ann_detail in ann['label_rectangles']: + # Get label safely + rectanglelabels = ann_detail.get('rectanglelabels', []) + if isinstance(rectanglelabels, list) and len(rectanglelabels) > 0: + label = rectanglelabels[0] + elif isinstance(rectanglelabels, str): + label = rectanglelabels + else: + label = 'unknown' + + ann_data = { + 'image_path': ann.get('image'), + 'x': (ann_detail['x'] * width) / 100, + 'y': (ann_detail['y'] * height) / 100, + 'width': (ann_detail['width'] * width) / 100, + 'height': (ann_detail['height'] * height) / 100, + 'Label': label + } + anns_bulk.append(ann_data) + elif isinstance(ann.get('label'), list): + for ann_detail in ann['label']: + # Get label safely + rectanglelabels = ann_detail.get('rectanglelabels', []) + if isinstance(rectanglelabels, list) and len(rectanglelabels) > 0: + label = rectanglelabels[0] + elif isinstance(rectanglelabels, str): + label = rectanglelabels + else: + label = 'unknown' + + ann_data = { + 'image_path': ann.get('image'), + 'x': (ann_detail['x'] * width) / 100, + 'y': (ann_detail['y'] * height) / 100, + 'width': (ann_detail['width'] * width) / 100, + 'height': (ann_detail['height'] * height) / 100, + 'Label': label + } + anns_bulk.append(ann_data) + + # Insert images and get generated IDs + inserted_images = [] + for img_data in images_bulk: + new_image = Image(**img_data) + db.session.add(new_image) + db.session.flush() # Flush to get the ID + inserted_images.append(new_image) + db.session.commit() + + # Map image_path -> image_id + image_map = {img.image_path: img.image_id for img in inserted_images} + + # Assign correct image_id to each annotation + for ann_data in anns_bulk: + ann_data['image_id'] = image_map.get(ann_data['image_path']) + del ann_data['image_path'] + + # Insert annotations + for ann_data in anns_bulk: + new_annotation = Annotation(**ann_data) + db.session.add(new_annotation) + db.session.commit() + + print(f"Inserted {len(images_bulk)} images and {len(anns_bulk)} annotations for project {project['id']}") + + print('Seeding done') + return {'success': True, 'message': 'Data inserted successfully!'} + + except Exception as error: + print(f'Error inserting data: {error}') + db.session.rollback() + return {'success': False, 'message': str(error)} + + finally: + update_status["running"] = False + print('updateStatus.running set to false') diff --git a/backend/services/settings_service.py b/backend/services/settings_service.py new file mode 100644 index 0000000..b914537 --- /dev/null +++ b/backend/services/settings_service.py @@ -0,0 +1,71 @@ +""" +Settings Service - Manages global application settings +""" +from models.Settings import Settings +from database.database import db + +def get_setting(key, default=None): + """Get a setting value by key""" + setting = Settings.query.filter_by(key=key).first() + return setting.value if setting else default + +def set_setting(key, value, description=None): + """Set a setting value""" + setting = Settings.query.filter_by(key=key).first() + if setting: + setting.value = value + if description: + setting.description = description + else: + setting = Settings(key=key, value=value, description=description) + db.session.add(setting) + + db.session.commit() + return setting + +def get_all_settings(): + """Get all settings as a dictionary""" + settings = Settings.query.all() + return {s.key: s.value for s in settings} + +def get_all_settings_detailed(): + """Get all settings with full details""" + settings = Settings.query.all() + return [s.to_dict() for s in settings] + +def initialize_default_settings(): + """Initialize default settings if they don't exist""" + defaults = { + 'labelstudio_api_url': { + 'value': 'http://192.168.1.19:8080/api', + 'description': 'Label Studio API URL' + }, + 'labelstudio_api_token': { + 'value': 'c1cef980b7c73004f4ee880a42839313b863869f', + 'description': 'Label Studio API Token' + }, + 'yolox_path': { + 'value': 'C:/YOLOX', + 'description': 'Path to YOLOX installation directory' + }, + 'yolox_venv_path': { + 'value': '/home/kitraining/Yolox/yolox_venv/bin/activate', + 'description': 'Path to YOLOX virtual environment activation script' + }, + 'yolox_output_path': { + 'value': './backend', + 'description': 'Output folder for YOLOX experiment files and JSONs' + }, + 'yolox_data_dir': { + 'value': '/home/kitraining/To_Annotate/', + 'description': 'Data directory path for YOLOX training (where images are located)' + } + } + + for key, data in defaults.items(): + existing = Settings.query.filter_by(key=key).first() + if not existing: + setting = Settings(key=key, value=data['value'], description=data['description']) + db.session.add(setting) + + db.session.commit() diff --git a/backend/start.py b/backend/start.py index a8d1dfe..83a33c1 100644 --- a/backend/start.py +++ b/backend/start.py @@ -1,14 +1,14 @@ -#!/usr/bin/env python3 -""" -Start the Flask backend server -""" -import sys -import os - -# Add the backend directory to Python path -sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) - -from app import app - -if __name__ == '__main__': - app.run(host='0.0.0.0', port=3000, debug=True) +#!/usr/bin/env python3 +""" +Start the Flask backend server +""" +import sys +import os + +# Add the backend directory to Python path +sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) + +from app import app + +if __name__ == '__main__': + app.run(host='0.0.0.0', port=3000, debug=True) diff --git a/backend/test/7/exp.py b/backend/test/7/exp.py new file mode 100644 index 0000000..f0df26f --- /dev/null +++ b/backend/test/7/exp.py @@ -0,0 +1,47 @@ +#!/usr/bin/env python3 +# -*- coding:utf-8 -*- +# Copyright (c) Megvii, Inc. and its affiliates. + +import os + +from yolox.exp import Exp as MyExp + + +class Exp(MyExp): + def __init__(self): + super(Exp, self).__init__() + self.data_dir = "/home/kitraining/To_Annotate/" + self.train_ann = "coco_project_3_train.json" + self.val_ann = "coco_project_3_valid.json" + self.test_ann = "coco_project_3_test.json" + self.num_classes = 2 + self.depth = 1.0 + self.width = 1.0 + self.input_size = (640.0, 640.0) + self.mosaic_scale = (0.1, 2.0) + self.test_size = (640.0, 640.0) + self.enable_mixup = True + self.max_epoch = 300 + self.warmup_epochs = 5 + self.warmup_lr = 0.0 + self.scheduler = "yoloxwarmcos" + self.no_aug_epochs = 15 + self.min_lr_ratio = 0.05 + self.ema = True + self.weight_decay = 0.0005 + self.momentum = 0.9 + self.print_interval = 10 + self.eval_interval = 10 + self.test_conf = 0.01 + self.nms_thre = 0.65 + self.mosaic_prob = 1.0 + self.mixup_prob = 1.0 + self.hsv_prob = 1.0 + self.flip_prob = 0.5 + self.degrees = 10.0 + self.translate = 0.1 + self.shear = 2.0 + self.mixup_scale = (0.5, 1.5) + self.activation = "silu" + self.random_size = (10, 20) + self.exp_name = os.path.split(os.path.realpath(__file__))[1].split(".")[0] diff --git a/documentation/Projektdoku.pdf b/documentation/Projektdoku.pdf new file mode 100644 index 0000000000000000000000000000000000000000..cbd1b0ccf8328d2ca5fe5603925866344d7c345d GIT binary patch literal 1631626 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