gitgnore

.gitignore

@@ -3,3 +3,5 @@ backend/uploads/*.pth
 *.pth
 backend/node_modules/
 backend/.venv/
+key
+key.pub

TRANSFER_LEARNING_FEATURE.md

@@ -1,217 +0,0 @@
-# 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 → user overrides → defaults
-
-**Behavior:**
-- `transfer_learning='coco'` → loads base config + applies user overrides
-- `transfer_learning='sketch'` → 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/<model_name>', 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
-<div id="base-config-info" style="display:none; ...">
-    🔒 Base Configuration Active
-    Protected parameters are loaded from [model] base config
-</div>
-```
-
-**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/<model>`
-
-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: "🔒 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=<project_id>` in browser
-   - Select "YOLOX-s" model
-   - Select "Train on coco" → fields should grey out
-   - Select "Train from sketch" → fields should become editable
-   - Switch to "YOLOX-l" (in COCO mode) → 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 → POST to `/api/yolox-settings`
-   - Verify payload includes protected parameters (depth, width, etc.)
-   - Check Flask logs for successful save
-
-### Expected Behaviors:
-
-✅ **COCO mode + YOLOX-s:**
-- depth: 0.33 (greyed out)
-- width: 0.50 (greyed out)
-- activation: silu (greyed out)
-- Info banner visible
-
-✅ **COCO mode + YOLOX-l:**
-- depth: 1.0 (greyed out)
-- width: 1.0 (greyed out)
-- activation: silu (greyed out)
-
-✅ **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

add-project.html

@@ -29,6 +29,14 @@
             <icon class="header-icon" onclick="window.location.href='/index.html'" , onmouseover=""
                 style="cursor: pointer;" src="./media/logo.png" alt="Logo"></icon>
             <div class="button-row">
+                <!-- Training Notification Bell -->
+                <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+                  style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+                  🔔
+                  <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+                    color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+                    text-align: center; font-weight: bold;">0</span>
+                </button>
                 <button id="Add Training Project" class="button-red">Add Training Project</button>
                 <button id="Add Dataset" class="button">Add Dataset</button>
                 <button id="Import Dataset" class="button">Refresh Label-Studio</button>
@@ -234,7 +242,123 @@
         </div>
     </div>
 
+    <!-- Training Status Modal -->
+    <div id="training-status-modal" class="modal" style="display: none;">
+        <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+            <div class="modal-header">
+                <h2>Training Status</h2>
+                <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+            </div>
+            
+            <div class="modal-body">
+                <div class="settings-section" id="current-training-section" style="display: none;">
+                    <h3 style="color: #009eac;">Current Training</h3>
+                    <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                    </div>
+                </div>
+
+                <div class="settings-section" id="queue-section" style="display: none;">
+                    <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                    <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                    </div>
+                </div>
+
+                <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                    No trainings running or queued.
+                </div>
+            </div>
+        </div>
+    </div>
+
     <script src="js/settings.js"></script>
+    <script>
+      let trainingStatusPoller = null;
+
+      function toggleTrainingModal() {
+        const modal = document.getElementById('training-status-modal');
+        if (modal.style.display === 'none') {
+          modal.style.display = 'flex';
+          updateTrainingStatus();
+        } else {
+          modal.style.display = 'none';
+        }
+      }
+
+      function updateTrainingStatus() {
+        fetch('/api/training-status')
+          .then(res => res.json())
+          .then(data => {
+            const bell = document.getElementById('training-bell');
+            const badge = document.getElementById('bell-badge');
+            const currentSection = document.getElementById('current-training-section');
+            const queueSection = document.getElementById('queue-section');
+            const noTrainingsMsg = document.getElementById('no-trainings-msg');
+            
+            const totalCount = (data.current ? 1 : 0) + data.queue.length;
+            
+            if (totalCount > 0) {
+              bell.style.background = '#009eac';
+              badge.style.display = 'block';
+              badge.textContent = totalCount;
+            } else {
+              bell.style.background = '#999';
+              badge.style.display = 'none';
+            }
+            
+            if (data.current) {
+              currentSection.style.display = 'block';
+              noTrainingsMsg.style.display = 'none';
+              
+              const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+              document.getElementById('current-training-info').innerHTML = `
+                <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+                  <strong>${data.current.name || 'Training'}</strong>
+                  <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+                </div>
+                <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+                  <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+                </div>
+                <div style="font-size: 14px; color: #666;">
+                  Epoch ${data.current.iteration} / ${data.current.max_epoch}
+                </div>
+              `;
+            } else {
+              currentSection.style.display = 'none';
+            }
+            
+            if (data.queue.length > 0) {
+              queueSection.style.display = 'block';
+              noTrainingsMsg.style.display = 'none';
+              document.getElementById('queue-count').textContent = data.queue.length;
+              
+              document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+                <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+                  <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+                  <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                    ${t.max_epoch} epochs • Waiting...
+                  </div>
+                </div>
+              `).join('');
+            } else {
+              queueSection.style.display = 'none';
+            }
+            
+            if (totalCount === 0) {
+              noTrainingsMsg.style.display = 'block';
+            }
+          })
+          .catch(err => console.error('Failed to fetch training status:', err));
+      }
+
+      window.addEventListener('DOMContentLoaded', function() {
+        updateTrainingStatus();
+        trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+      });
+
+      window.addEventListener('beforeunload', function() {
+        if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+      });
+    </script>
 
 </body>
 

backend/0815/27/exp_infer.py

@@ -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

backend/1/6/exp.py

@@ -1,48 +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_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]

backend/1/6/exp_infer.py

@@ -1,48 +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_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]

backend/QUICKSTART.md

@@ -1,113 +0,0 @@
-# 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 → Flask
-2. **ORM**: Sequelize → SQLAlchemy
-3. **HTTP Client**: node-fetch → requests
-4. **Package Manager**: npm → pip
-5. **Dependencies**: package.json → requirements.txt
-6. **Startup**: `node server.js` → `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/
-├── server.js
-├── package.json
-├── routes/api.js
-├── models/*.js
-└── services/*.js
-```
-
-**After (Python):**
-```
-backend/
-├── app.py
-├── requirements.txt
-├── routes/api.py
-├── models/*.py
-└── services/*.py
-```

backend/asdf/5/exp_infer.py

@@ -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

backend/backend/1/1/exp_infer.py

@@ -1,84 +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"  # 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]

backend/backend/1/custom_exp_1/exp.py

@@ -1,84 +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"  # 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]

backend/database/database.js

@@ -1,10 +0,0 @@
-// database.js
-const { Sequelize } = require('sequelize');
-
-const sequelize = new Sequelize('myapp', 'root', 'root', {
-  host: 'localhost',
-  dialect: 'mysql',
-  logging: false,
-});
-
-module.exports = sequelize;

backend/database/migration_add_image_dimensions.sql

@@ -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`;

backend/database/migration_fix_image_dimensions.sql

@@ -1,12 +0,0 @@
--- Migration to change width and height from FLOAT to INT in image table
--- Run this after updating the Images model
-
--- First, backup the table (optional but recommended)
--- CREATE TABLE image_backup AS SELECT * FROM image;
-
--- Alter the columns to INT type
-ALTER TABLE image MODIFY COLUMN width INT;
-ALTER TABLE image MODIFY COLUMN height INT;
-
--- Verify the changes
-DESCRIBE image;

backend/models/Annotation.js

@@ -1,40 +0,0 @@
-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;

backend/models/Images.js

@@ -1,35 +0,0 @@
-
-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;
-
-

backend/models/LabelStudioProject.js

@@ -1,24 +0,0 @@
-
-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;
-
-

backend/models/TrainingProject.js

@@ -1,38 +0,0 @@
-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;
-
-

backend/models/TrainingProjectDetails.js

@@ -1,33 +0,0 @@
-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;

backend/models/index.js

@@ -1,30 +0,0 @@
-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 };

backend/models/training.js

@@ -1,140 +0,0 @@
-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;

backend/routes/api.js

@@ -1,496 +0,0 @@
-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;

backend/routes/api.py

@@ -73,7 +73,7 @@ def generate_yolox_json():
 
 @api_bp.route('/start-yolox-training', methods=['POST'])
 def start_yolox_training():
-    """Generate JSONs, exp.py, and start YOLOX training"""
+    """Generate JSONs, exp.py, and add training to queue"""
     try:
         data = request.get_json()
         project_id = data.get('project_id')
@@ -90,9 +90,11 @@ def start_yolox_training():
         details_id = training.project_details_id
         
         # Step 1: Generate COCO JSON files
+        # IMPORTANT: Pass training_id (not details_id) so JSON files are generated
+        # in the same location where exp.py expects them
         from services.generate_json_yolox import generate_training_json
         print(f'Generating COCO JSON for training {training_id}...')
-        generate_training_json(details_id)
+        generate_training_json(training_id)
         
         # Step 2: Generate exp.py
         from services.generate_yolox_exp import save_yolox_exp
@@ -113,8 +115,8 @@ def start_yolox_training():
         print(f'Generating exp.py at {exp_file_path}...')
         save_yolox_exp(training_id, exp_file_path)
         
-        # Step 3: Start training
+        # Step 3: Build training command
-        print(f'Starting YOLOX training for training {training_id}...')
+        print(f'Preparing training command for training {training_id}...')
         
         # Get YOLOX configuration from settings
         yolox_main_dir = get_setting('yolox_path', '/home/kitraining/Yolox/YOLOX-main')
@@ -130,11 +132,17 @@ def start_yolox_training():
         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'
+            # Use yolox_path setting to construct pretrained model path
+            model_path = os.path.join(yolox_main_dir, 'pretrained', f'{training.selected_model}.pth')
+            model_path = model_path.replace('\\', '/')  # Use forward slashes for command line
+            model_arg = f'-c {model_path}'
         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'
+            # Use yolox_path setting to construct pretrained model path
+            model_path = os.path.join(yolox_main_dir, 'pretrained', f'{training.selected_model}.pth')
+            model_path = model_path.replace('\\', '/')  # Use forward slashes for command line
+            model_arg = f'-c {model_path}'
         
         # Build base training arguments
         train_args = f'-f {exp_file_path} -d 1 -b 8 --fp16 --cache'
@@ -151,16 +159,18 @@ def start_yolox_training():
                 venv_activate = yolox_venv
             cmd = f'cmd /c ""{venv_activate}" && python tools\\train.py {train_args}"'
         else:
-            # Linux: Use bash with source
+            # Linux: Use bash with source to activate the venv
-            cmd = f'bash -c "source {yolox_venv} && python tools/train.py {train_args}"'
+            venv_activate = os.path.join(yolox_venv, 'bin', 'activate')
+            cmd = f'bash -c "source {venv_activate} && python tools/train.py {train_args}"'
         
         print(f'Training command: {cmd}')
         
-        # Start training in background
+        # Step 4: Add to training queue
-        subprocess.Popen(cmd, shell=True, cwd=yolox_main_dir)
+        from services.training_queue import training_queue
+        training_queue.add_to_queue(training_id, cmd, yolox_main_dir)
         
         return jsonify({
-            'message': f'JSONs and exp.py generated, training started for training {training_id}',
+            'message': f'Training {training_id} added to queue',
             'exp_path': exp_file_path
         })
     
@@ -170,6 +180,18 @@ def start_yolox_training():
         traceback.print_exc()
         return jsonify({'message': 'Failed to start training', 'error': str(err)}), 500
 
+@api_bp.route('/training-status', methods=['GET'])
+def get_training_status():
+    """Get current training queue status"""
+    try:
+        from services.training_queue import training_queue
+        status = training_queue.get_status()
+        return jsonify(status)
+    
+    except Exception as err:
+        print(f'Error getting training status: {err}')
+        return jsonify({'current': None, 'queue': []}), 500
+
 @api_bp.route('/training-log', methods=['GET'])
 def training_log():
     """Get YOLOX training log"""
@@ -477,17 +499,26 @@ def yolox_settings():
             settings['activation'] = settings['act']
             del settings['act']
         
-        # Type conversions
+        # Type conversions - Integer fields
-        numeric_fields = [
+        integer_fields = [
-            'max_epoch', 'depth', 'width', 'warmup_epochs', 'warmup_lr', 
+            'max_epoch', 'warmup_epochs', 'no_aug_epochs', 'print_interval', 
-            'no_aug_epochs', 'min_lr_ratio', 'weight_decay', 'momentum',
+            'eval_interval', 'multiscale_range', 'data_num_workers', 'num_classes'
-            'print_interval', 'eval_interval', 'test_conf', 'nmsthre',
-            'multiscale_range', 'degrees', 'translate', 'shear',
-            'train', 'valid', 'test'
         ]
         
-        for field in numeric_fields:
+        for field in integer_fields:
-            if field in settings:
+            if field in settings and settings[field] not in [None, '']:
+                settings[field] = int(float(settings[field]))  # Convert via float to handle "10.0" strings
+        
+        # Type conversions - Float fields
+        float_fields = [
+            'depth', 'width', 'warmup_lr', 'min_lr_ratio', 'weight_decay', 
+            'momentum', 'test_conf', 'nmsthre', 'degrees', 'translate', 
+            'shear', 'mosaic_prob', 'mixup_prob', 'hsv_prob', 'flip_prob',
+            'basic_lr_per_img', 'train', 'valid', 'test'
+        ]
+        
+        for field in float_fields:
+            if field in settings and settings[field] not in [None, '']:
                 settings[field] = float(settings[field])
         
         # Boolean conversions
@@ -617,6 +648,19 @@ def get_trainings():
     except Exception as error:
         return jsonify({'message': 'Failed to fetch trainings', 'error': str(error)}), 500
 
+@api_bp.route('/trainings/<int:id>', methods=['GET'])
+def get_training(id):
+    """Get a single training by id"""
+    try:
+        training = Training.query.get(id)
+        if training:
+            return jsonify(training.to_dict())
+        else:
+            return jsonify({'message': 'Training not found'}), 404
+    
+    except Exception as error:
+        return jsonify({'message': 'Failed to fetch training', 'error': str(error)}), 500
+
 @api_bp.route('/trainings/<int:id>', methods=['DELETE'])
 def delete_training(id):
     """Delete a training by id"""

backend/services/fetch-labelstudio.js

@@ -1,92 +0,0 @@
-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()

backend/services/generate-json-yolox.js

@@ -1,176 +0,0 @@
-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};

backend/services/generate-yolox-exp.js

@@ -1,135 +0,0 @@
-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 };

backend/services/generate_json_yolox.py

@@ -7,12 +7,30 @@ 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"""
+    """Generate COCO JSON for training, validation, and test sets
-    # training_id is now project_details_id
+    
-    training_project_details = TrainingProjectDetails.query.get(training_id)
+    Args:
+        training_id: Can be either a Training.id or TrainingProjectDetails.id
+                     Function will automatically detect which one and find the correct details_id
+    """
+    from models.training import Training
+    
+    # First, try to get as a Training record
+    training_record = Training.query.get(training_id)
+    
+    if training_record:
+        # It's a Training.id - use its project_details_id
+        details_id = training_record.project_details_id
+        print(f'[generate_training_json] Using training_id={training_id}, mapped to project_details_id={details_id}')
+    else:
+        # Try as TrainingProjectDetails.id directly
+        details_id = training_id
+        print(f'[generate_training_json] Using training_id={training_id} as project_details_id directly')
+    
+    training_project_details = TrainingProjectDetails.query.get(details_id)
     
     if not training_project_details:
-        raise Exception(f'No TrainingProjectDetails found for project_details_id {training_id}')
+        raise Exception(f'No TrainingProjectDetails found for id {training_id} (details_id: {details_id})')
     
     details_obj = training_project_details.to_dict()
     
@@ -110,22 +128,35 @@ def generate_training_json(training_id):
                     break
             
             # Construct ABSOLUTE path using data_dir
-            # Normalize data_dir - ensure it uses backslashes for Windows
+            # Detect platform for proper path handling
-            normalized_data_dir = data_dir.rstrip('/\\').replace('/', '\\')
+            import platform
+            is_windows = platform.system() == 'Windows'
+            
+            # Normalize data_dir and file_name based on platform
+            if is_windows:
+                # Windows: use backslashes
+                normalized_data_dir = data_dir.rstrip('/\\').replace('/', '\\')
+                file_name = file_name.replace('/', '\\')
+            else:
+                # Linux/Mac: use forward slashes
+                normalized_data_dir = data_dir.rstrip('/\\').replace('\\', '/')
+                file_name = file_name.replace('\\', '/')
             
             # Check if already absolute path
-            if not (file_name.startswith('\\\\') or (len(file_name) > 1 and file_name[1] == ':')):
+            is_absolute = False
-                # It's a relative path, combine with data_dir
+            if is_windows:
-                # For UNC paths, we need to manually concatenate to preserve \\
+                is_absolute = file_name.startswith('\\\\') or (len(file_name) > 1 and file_name[1] == ':')
-                if normalized_data_dir.startswith('\\\\'):
-                    # UNC path
-                    file_name = normalized_data_dir + '\\' + file_name.replace('/', '\\')
-                else:
-                    # Regular path
-                    file_name = os.path.join(normalized_data_dir, file_name.replace('/', '\\'))
             else:
-                # Already absolute, just normalize separators
+                is_absolute = file_name.startswith('/')
-                file_name = file_name.replace('/', '\\')
+            
+            if not is_absolute:
+                # It's a relative path, combine with data_dir
+                if is_windows and normalized_data_dir.startswith('\\\\'):
+                    # Windows UNC path
+                    file_name = normalized_data_dir + '\\' + file_name
+                else:
+                    # Regular path (Windows or Linux)
+                    file_name = os.path.join(normalized_data_dir, file_name)
             
             # Get annotations for this image
             annotations = Annotation.query.filter_by(image_id=image.image_id).all()
@@ -218,13 +249,19 @@ def generate_training_json(training_id):
     
     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
+    # Get training record to use its name and ID for folder and file names
-    training_record = Training.query.filter_by(project_details_id=training_id).first()
+    # Use the same training_id that was passed in (if it was a Training.id)
-    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)
+    # or find the first training for this details_id
-    training_folder_name = training_folder_name.replace(' ', '_')
+    if not training_record:
+        training_record = Training.query.filter_by(project_details_id=details_id).first()
     
-    # Use training_record.id for file names to match what generate_yolox_exp expects
+    if training_record:
-    training_file_id = training_record.id if training_record else training_id
+        training_folder_name = f"{training_record.exp_name or training_record.training_name or 'training'}_{training_record.id}"
+        training_folder_name = training_folder_name.replace(' ', '_')
+        training_file_id = training_record.id
+    else:
+        training_folder_name = str(details_id)
+        training_file_id = details_id
     
     # Save annotations to the configured output folder
     annotations_dir = os.path.join(output_base_path, project_name, training_folder_name, 'annotations')
@@ -242,7 +279,7 @@ def generate_training_json(training_id):
     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}')
+    print(f'COCO JSON splits written to {annotations_dir} for training_id={training_file_id} (details_id={details_id})')
     
     # Also generate inference exp.py
     from services.generate_yolox_exp import generate_yolox_inference_exp

backend/services/generate_yolox_exp.py

@@ -220,6 +220,10 @@ def generate_yolox_inference_exp(training_id, options=None, use_base_config=Fals
     annotations_parent_dir = os.path.join(output_base_path, project_name, training_folder_name)
     annotations_parent_escaped = annotations_parent_dir.replace('\\', '\\\\')
     
+    # Set output directory for checkpoints - models subdirectory
+    models_dir = os.path.join(annotations_parent_dir, 'models')
+    models_dir_escaped = models_dir.replace('\\', '\\\\')
+    
     # Build exp content
     exp_content = f'''#!/usr/bin/env python3
 # -*- coding:utf-8 -*-
@@ -235,6 +239,7 @@ class Exp(MyExp):
         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.output_dir = "{models_dir_escaped}"  # Where checkpoints will be saved
         self.train_ann = "{train_ann}"
         self.val_ann = "{val_ann}"
         self.test_ann = "{test_ann}"
@@ -252,21 +257,46 @@ class Exp(MyExp):
         if selected_model:
             exp_content += f"        self.pretrained_ckpt = r'{yolox_base_dir}/pretrained/{selected_model}.pth'\n"
     
-    # Format arrays
+    # Format arrays and values for Python code generation
-    def format_value(val):
+    # Integer-only parameters (sizes, epochs, intervals)
+    integer_params = {
+        'input_size', 'test_size', 'random_size', 'max_epoch', 'warmup_epochs',
+        'no_aug_epochs', 'print_interval', 'eval_interval', 'multiscale_range',
+        'data_num_workers', 'num_classes'
+    }
+    
+    def format_value(val, param_name=''):
         if isinstance(val, (list, tuple)):
-            return '(' + ', '.join(map(str, val)) + ')'
+            # Check if this parameter should have integer values
+            if param_name in integer_params:
+                # Convert all values to integers
+                formatted_items = [str(int(float(item))) if isinstance(item, (int, float)) else str(item) for item in val]
+            else:
+                # Keep as floats or original type
+                formatted_items = []
+                for item in val:
+                    if isinstance(item, float):
+                        formatted_items.append(str(item))
+                    elif isinstance(item, int):
+                        formatted_items.append(str(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, int):
+            return str(val)
+        elif isinstance(val, float):
+            return str(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"
+            exp_content += f"        self.{key} = {format_value(value, key)}\n"
     
     # Add get_dataset override using name parameter for image directory
     exp_content += '''
@@ -289,7 +319,7 @@ class Exp(MyExp):
     
     def get_eval_dataset(self, **kwargs):
         """Override eval dataset using name parameter"""
-        from yolox.data import COCODataset
+        from yolox.data import COCODataset, ValTransform
         
         testdev = kwargs.get("testdev", False)
         legacy = kwargs.get("legacy", False)
@@ -299,8 +329,34 @@ class Exp(MyExp):
             json_file=self.val_ann if not testdev else self.test_ann,
             name="",
             img_size=self.test_size,
-            preproc=None,  # No preprocessing for evaluation
+            preproc=ValTransform(legacy=legacy),  # Use proper validation transform
         )
+    
+    def get_eval_loader(self, batch_size, is_distributed, **kwargs):
+        """Standard YOLOX eval loader - matches official implementation"""
+        import torch
+        import torch.distributed as dist
+        from torch.utils.data import DataLoader
+        
+        valdataset = self.get_eval_dataset(**kwargs)
+
+        if is_distributed:
+            batch_size = batch_size // dist.get_world_size()
+            sampler = torch.utils.data.distributed.DistributedSampler(
+                valdataset, shuffle=False
+            )
+        else:
+            sampler = torch.utils.data.SequentialSampler(valdataset)
+
+        dataloader_kwargs = {
+            "num_workers": self.data_num_workers,
+            "pin_memory": True,
+            "sampler": sampler,
+        }
+        dataloader_kwargs["batch_size"] = batch_size
+        val_loader = DataLoader(valdataset, **dataloader_kwargs)
+
+        return val_loader
 '''
     
     # Add exp_name at the end (uses dynamic path)

backend/services/push-yolox-exp.js

@@ -1,48 +0,0 @@
-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 };

backend/services/seed-label-studio.js

@@ -1,120 +0,0 @@
-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 };

backend/services/training_queue.py

@@ -0,0 +1,206 @@
+"""
+Training Queue Manager
+Manages a queue of training jobs and tracks their progress
+"""
+import threading
+import queue
+import subprocess
+import re
+import os
+from services.settings_service import get_setting
+from models.training import Training
+
+class TrainingQueueManager:
+    _instance = None
+    _lock = threading.Lock()
+    
+    def __new__(cls):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:
+                    cls._instance = super().__new__(cls)
+                    cls._instance._initialized = False
+        return cls._instance
+    
+    def __init__(self):
+        if self._initialized:
+            return
+        
+        self.queue = queue.Queue()
+        self.current_training = None
+        self.current_process = None
+        self.worker_thread = None
+        self.running = False
+        self._initialized = True
+        
+        # Start the worker thread
+        self.start_worker()
+    
+    def start_worker(self):
+        """Start the background worker thread"""
+        if self.worker_thread is None or not self.worker_thread.is_alive():
+            self.running = True
+            self.worker_thread = threading.Thread(target=self._process_queue, daemon=True)
+            self.worker_thread.start()
+    
+    def add_to_queue(self, training_id, command, cwd):
+        """Add a training job to the queue"""
+        job = {
+            'training_id': training_id,
+            'command': command,
+            'cwd': cwd,
+            'iteration': 0,
+            'max_epoch': 300  # Will be updated from training record
+        }
+        
+        # Get max_epoch from training record
+        try:
+            training = Training.query.get(training_id)
+            if training:
+                job['max_epoch'] = training.max_epoch or 300
+                job['name'] = training.exp_name or f'Training {training_id}'
+        except:
+            pass
+        
+        self.queue.put(job)
+        print(f'Added training {training_id} to queue. Queue size: {self.queue.qsize()}')
+    
+    def _process_queue(self):
+        """Worker thread that processes the queue"""
+        while self.running:
+            try:
+                # Wait for a job (blocking with timeout)
+                job = self.queue.get(timeout=1)
+                
+                print(f'Starting training {job["training_id"]} from queue')
+                self.current_training = job
+                
+                # Execute the training command
+                self._run_training(job)
+                
+                # Mark as done
+                self.queue.task_done()
+                self.current_training = None
+                self.current_process = None
+                
+            except queue.Empty:
+                continue
+            except Exception as e:
+                print(f'Error processing training job: {e}')
+                self.current_training = None
+                self.current_process = None
+    
+    def _run_training(self, job):
+        """Run a training command and monitor its output"""
+        try:
+            import platform
+            is_windows = platform.system() == 'Windows'
+            
+            # Start process
+            self.current_process = subprocess.Popen(
+                job['command'],
+                shell=True,
+                cwd=job['cwd'],
+                stdout=subprocess.PIPE,
+                stderr=subprocess.STDOUT,
+                universal_newlines=True,
+                bufsize=1
+            )
+            
+            # Monitor output for progress
+            for line in iter(self.current_process.stdout.readline, ''):
+                if line:
+                    print(line.strip())
+                    
+                    # Parse epoch and iteration from YOLOX output
+                    # Example: "epoch: 3/300, iter: 90/101"
+                    epoch_match = re.search(r'epoch:\s*(\d+)/(\d+)', line, re.IGNORECASE)
+                    iter_match = re.search(r'iter:\s*(\d+)/(\d+)', line, re.IGNORECASE)
+                    
+                    if epoch_match:
+                        current_epoch = int(epoch_match.group(1))
+                        total_epochs = int(epoch_match.group(2))
+                        if self.current_training:
+                            self.current_training['current_epoch'] = current_epoch
+                            self.current_training['max_epoch'] = total_epochs
+                            # Debug log
+                            print(f'[PROGRESS] Parsed epoch: {current_epoch}/{total_epochs}')
+                    
+                    if iter_match:
+                        current_iter = int(iter_match.group(1))
+                        total_iters = int(iter_match.group(2))
+                        if self.current_training:
+                            self.current_training['current_iter'] = current_iter
+                            self.current_training['total_iters'] = total_iters
+                            
+                            # Calculate overall progress percentage
+                            if 'current_epoch' in self.current_training and 'max_epoch' in self.current_training:
+                                epoch_progress = (self.current_training['current_epoch'] - 1) / self.current_training['max_epoch']
+                                iter_progress = current_iter / total_iters / self.current_training['max_epoch']
+                                total_progress = (epoch_progress + iter_progress) * 100
+                                self.current_training['progress'] = round(total_progress, 2)
+                                # Debug log
+                                print(f'[PROGRESS] Epoch {self.current_training["current_epoch"]}/{self.current_training["max_epoch"]}, Iter {current_iter}/{total_iters}, Progress: {self.current_training["progress"]}%')
+            
+            # Wait for completion
+            self.current_process.wait()
+            print(f'Training {job["training_id"]} completed with exit code {self.current_process.returncode}')
+            
+        except Exception as e:
+            print(f'Error running training: {e}')
+    
+    def get_status(self):
+        """Get current status of training queue"""
+        queue_items = []
+        
+        # Get items from queue without removing them
+        temp_items = []
+        while not self.queue.empty():
+            try:
+                item = self.queue.get_nowait()
+                temp_items.append(item)
+                queue_items.append({
+                    'training_id': item['training_id'],
+                    'name': item.get('name', f'Training {item["training_id"]}'),
+                    'max_epoch': item.get('max_epoch', 300)
+                })
+            except queue.Empty:
+                break
+        
+        # Put items back
+        for item in temp_items:
+            self.queue.put(item)
+        
+        result = {
+            'current': None,
+            'queue': queue_items
+        }
+        
+        if self.current_training:
+            current_epoch = self.current_training.get('current_epoch', 0)
+            max_epoch = self.current_training.get('max_epoch', 300)
+            result['current'] = {
+                'training_id': self.current_training['training_id'],
+                'name': self.current_training.get('name', f'Training {self.current_training["training_id"]}'),
+                'epoch': current_epoch,  # For backward compatibility
+                'current_epoch': current_epoch,
+                'max_epoch': max_epoch,
+                'current_iter': self.current_training.get('current_iter', 0),
+                'total_iters': self.current_training.get('total_iters', 0),
+                'progress': self.current_training.get('progress', 0.0),
+                'iteration': current_epoch  # For backward compatibility
+            }
+        
+        return result
+    
+    def stop(self):
+        """Stop the worker thread"""
+        self.running = False
+        if self.current_process:
+            try:
+                self.current_process.terminate()
+            except:
+                pass
+
+# Global instance
+training_queue = TrainingQueueManager()

backend/services/validate_dataset.py

@@ -0,0 +1,244 @@
+"""
+Validate dataset for training - check for problematic images and annotations
+"""
+import os
+import json
+from PIL import Image
+import cv2
+
+def validate_coco_json(json_path, data_dir):
+    """
+    Validate a COCO JSON file and check all images
+    
+    Args:
+        json_path: Path to COCO JSON file
+        data_dir: Directory where images are located
+    
+    Returns:
+        dict with validation results
+    """
+    print(f"\n{'='*60}")
+    print(f"Validating: {json_path}")
+    print(f"{'='*60}\n")
+    
+    issues = {
+        'missing_images': [],
+        'corrupted_images': [],
+        'zero_dimension_images': [],
+        'invalid_annotations': [],
+        'zero_area_boxes': []
+    }
+    
+    try:
+        with open(json_path, 'r') as f:
+            coco_data = json.load(f)
+    except Exception as e:
+        print(f"❌ Failed to load JSON: {e}")
+        return issues
+    
+    images = coco_data.get('images', [])
+    annotations = coco_data.get('annotations', [])
+    
+    print(f"📊 Dataset Stats:")
+    print(f"   Images: {len(images)}")
+    print(f"   Annotations: {len(annotations)}")
+    print(f"   Categories: {len(coco_data.get('categories', []))}")
+    print()
+    
+    # Validate images
+    print("🔍 Validating images...")
+    for idx, img_info in enumerate(images):
+        img_id = img_info.get('id')
+        file_name = img_info.get('file_name', '')
+        width = img_info.get('width', 0)
+        height = img_info.get('height', 0)
+        
+        # Check if image file exists
+        # Try to construct the full path
+        if os.path.isabs(file_name):
+            img_path = file_name
+        else:
+            img_path = os.path.join(data_dir, file_name)
+        
+        if not os.path.exists(img_path):
+            issues['missing_images'].append({
+                'id': img_id,
+                'file_name': file_name,
+                'expected_path': img_path
+            })
+            continue
+        
+        # Check if image can be loaded
+        try:
+            # Try with PIL
+            with Image.open(img_path) as pil_img:
+                pil_width, pil_height = pil_img.size
+                
+                # Check if dimensions match JSON
+                if pil_width != width or pil_height != height:
+                    print(f"⚠️  Image {img_id}: Dimension mismatch - JSON: {width}x{height}, Actual: {pil_width}x{pil_height}")
+                
+                # Check for zero dimensions
+                if pil_width == 0 or pil_height == 0:
+                    issues['zero_dimension_images'].append({
+                        'id': img_id,
+                        'file_name': file_name,
+                        'dimensions': f"{pil_width}x{pil_height}"
+                    })
+        except Exception as e:
+            issues['corrupted_images'].append({
+                'id': img_id,
+                'file_name': file_name,
+                'error': str(e)
+            })
+        
+        # Progress indicator
+        if (idx + 1) % 100 == 0:
+            print(f"   Checked {idx + 1}/{len(images)} images...")
+    
+    print(f"✅ Image validation complete\n")
+    
+    # Validate annotations
+    print("🔍 Validating annotations...")
+    for idx, ann in enumerate(annotations):
+        ann_id = ann.get('id')
+        img_id = ann.get('image_id')
+        bbox = ann.get('bbox', [])
+        
+        if len(bbox) != 4:
+            issues['invalid_annotations'].append({
+                'id': ann_id,
+                'image_id': img_id,
+                'reason': f'Invalid bbox length: {len(bbox)}'
+            })
+            continue
+        
+        x, y, w, h = bbox
+        
+        # Check for zero or negative dimensions
+        if w <= 0 or h <= 0:
+            issues['zero_area_boxes'].append({
+                'id': ann_id,
+                'image_id': img_id,
+                'bbox': bbox,
+                'reason': f'Zero or negative dimensions: w={w}, h={h}'
+            })
+        
+        # Check for extremely small boxes (potential issue with mixup)
+        if w < 1 or h < 1:
+            issues['zero_area_boxes'].append({
+                'id': ann_id,
+                'image_id': img_id,
+                'bbox': bbox,
+                'reason': f'Extremely small box: w={w}, h={h}'
+            })
+        
+        # Progress indicator
+        if (idx + 1) % 1000 == 0:
+            print(f"   Checked {idx + 1}/{len(annotations)} annotations...")
+    
+    print(f"✅ Annotation validation complete\n")
+    
+    # Print summary
+    print(f"\n{'='*60}")
+    print("VALIDATION SUMMARY")
+    print(f"{'='*60}\n")
+    
+    total_issues = sum(len(v) for v in issues.values())
+    
+    if total_issues == 0:
+        print("✅ No issues found! Dataset is ready for training.")
+    else:
+        print(f"⚠️  Found {total_issues} total issues:\n")
+        
+        if issues['missing_images']:
+            print(f"   ❌ Missing images: {len(issues['missing_images'])}")
+            for item in issues['missing_images'][:5]:  # Show first 5
+                print(f"      - {item['file_name']}")
+            if len(issues['missing_images']) > 5:
+                print(f"      ... and {len(issues['missing_images']) - 5} more")
+        
+        if issues['corrupted_images']:
+            print(f"   ❌ Corrupted images: {len(issues['corrupted_images'])}")
+            for item in issues['corrupted_images'][:5]:
+                print(f"      - {item['file_name']}: {item['error']}")
+            if len(issues['corrupted_images']) > 5:
+                print(f"      ... and {len(issues['corrupted_images']) - 5} more")
+        
+        if issues['zero_dimension_images']:
+            print(f"   ❌ Zero dimension images: {len(issues['zero_dimension_images'])}")
+            for item in issues['zero_dimension_images'][:5]:
+                print(f"      - {item['file_name']}: {item['dimensions']}")
+            if len(issues['zero_dimension_images']) > 5:
+                print(f"      ... and {len(issues['zero_dimension_images']) - 5} more")
+        
+        if issues['invalid_annotations']:
+            print(f"   ❌ Invalid annotations: {len(issues['invalid_annotations'])}")
+            for item in issues['invalid_annotations'][:5]:
+                print(f"      - Ann ID {item['id']}: {item['reason']}")
+            if len(issues['invalid_annotations']) > 5:
+                print(f"      ... and {len(issues['invalid_annotations']) - 5} more")
+        
+        if issues['zero_area_boxes']:
+            print(f"   ⚠️  Zero/tiny area boxes: {len(issues['zero_area_boxes'])}")
+            print(f"      These may cause issues with mixup augmentation!")
+            for item in issues['zero_area_boxes'][:5]:
+                print(f"      - Ann ID {item['id']}, bbox: {item['bbox']}")
+            if len(issues['zero_area_boxes']) > 5:
+                print(f"      ... and {len(issues['zero_area_boxes']) - 5} more")
+    
+    print()
+    return issues
+
+
+def validate_training_dataset(training_id):
+    """
+    Validate all COCO JSON files for a training
+    
+    Args:
+        training_id: The training ID to validate
+    """
+    from models.training import Training
+    from models.TrainingProject import TrainingProject
+    from services.settings_service import get_setting
+    
+    training = Training.query.get(training_id)
+    if not training:
+        print(f"❌ Training {training_id} not found")
+        return
+    
+    # Get paths
+    from models.TrainingProjectDetails import TrainingProjectDetails
+    details = TrainingProjectDetails.query.get(training.project_details_id)
+    training_project = TrainingProject.query.get(details.project_id)
+    project_name = training_project.title.replace(' ', '_') if training_project else f'project_{details.project_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')
+    data_dir = get_setting('yolox_data_dir', '/home/kitraining/To_Annotate/')
+    
+    annotations_dir = os.path.join(output_base_path, project_name, training_folder_name, 'annotations')
+    
+    # Validate each split
+    splits = ['train', 'valid', 'test']
+    all_issues = {}
+    
+    for split in splits:
+        json_file = os.path.join(annotations_dir, f'coco_project_{training_id}_{split}.json')
+        if os.path.exists(json_file):
+            all_issues[split] = validate_coco_json(json_file, data_dir)
+        else:
+            print(f"⚠️  JSON file not found: {json_file}")
+    
+    return all_issues
+
+
+if __name__ == '__main__':
+    import sys
+    if len(sys.argv) > 1:
+        training_id = int(sys.argv[1])
+        validate_training_dataset(training_id)
+    else:
+        print("Usage: python validate_dataset.py <training_id>")

edit-training.html

@@ -202,6 +202,14 @@
             <label id="project-title-label"
                 style="display: block; text-align: left; font-weight: bold; font-size: x-large;">title</label>
             <div class="button-row">
+                <!-- Training Notification Bell -->
+                <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+                  style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+                  🔔
+                  <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+                    color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+                    text-align: center; font-weight: bold;">0</span>
+                </button>
                 <button id="Add Training Project" onclick="window.location.href='/add-project.html'"
                     class="button-red">Add Training Project</button>
                 <button id="seed-db-btn" class="button">
@@ -553,7 +561,7 @@ document.getElementById('parameters-form').addEventListener('submit', async func
     }
     // Add project id if available
     const urlParams = new URLSearchParams(window.location.search);
-    const projectId = urlParams.get('id');
+    const projectId = urlParams.get('project_id') || urlParams.get('id'); // Support both parameter names
     if (projectId) formData.append('project_id', projectId);
     // Send to backend
     try {
@@ -640,4 +648,186 @@ document.getElementById('parameters-form').addEventListener('submit', async func
 </div>
 
 <script src="js/settings.js"></script>
+<script>
+// Handle readonly mode and load training data
+window.addEventListener('DOMContentLoaded', function() {
+    const urlParams = new URLSearchParams(window.location.search);
+    const trainingId = urlParams.get('training_id');
+    const isReadonly = urlParams.get('readonly') === 'true';
+    
+    if (isReadonly) {
+        // Update page title
+        const titleLabel = document.querySelector('#project-title-label');
+        if (titleLabel) {
+            titleLabel.textContent = 'View Training Details (Read-Only)';
+        }
+        
+        // Disable all form inputs
+        document.querySelectorAll('input, select, textarea, button[type="submit"]').forEach(el => {
+            el.disabled = true;
+            el.style.opacity = '0.6';
+            el.style.cursor = 'not-allowed';
+        });
+        
+        // Hide submit buttons
+        document.querySelectorAll('button[type="submit"]').forEach(btn => {
+            btn.style.display = 'none';
+        });
+        
+        // Re-enable navigation buttons (back, etc.)
+        document.querySelectorAll('button:not([type="submit"])').forEach(btn => {
+            if (btn.textContent.includes('Back') || btn.onclick) {
+                btn.disabled = false;
+                btn.style.opacity = '1';
+                btn.style.cursor = 'pointer';
+            }
+        });
+    }
+    
+    // Load training data if training_id is present
+    if (trainingId) {
+        fetch(`/api/trainings/${trainingId}`)
+            .then(res => res.json())
+            .then(training => {
+                // Populate form fields with training data
+                Object.keys(training).forEach(key => {
+                    const input = document.querySelector(`[name="${key}"]`);
+                    if (input) {
+                        if (input.type === 'checkbox') {
+                            input.checked = training[key];
+                        } else {
+                            input.value = training[key] || '';
+                        }
+                    }
+                });
+                
+                // Handle special fields
+                if (training.train) document.getElementById('train-slider').value = training.train;
+                if (training.valid) document.getElementById('valid-slider').value = training.valid;
+                if (training.test) document.getElementById('test-slider').value = training.test;
+                syncSplitSliders('train');
+            })
+            .catch(err => {
+                console.error('Failed to load training data:', err);
+            });
+    }
+});
+</script>
+
+<!-- Training Status Modal -->
+<div id="training-status-modal" class="modal" style="display: none;">
+    <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+        <div class="modal-header">
+            <h2>Training Status</h2>
+            <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+        </div>
+        
+        <div class="modal-body">
+            <div class="settings-section" id="current-training-section" style="display: none;">
+                <h3 style="color: #009eac;">Current Training</h3>
+                <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                </div>
+            </div>
+
+            <div class="settings-section" id="queue-section" style="display: none;">
+                <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                </div>
+            </div>
+
+            <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                No trainings running or queued.
+            </div>
+        </div>
+    </div>
+</div>
+
+<script>
+  let trainingStatusPoller = null;
+
+  function toggleTrainingModal() {
+    const modal = document.getElementById('training-status-modal');
+    if (modal.style.display === 'none') {
+      modal.style.display = 'flex';
+      updateTrainingStatus();
+    } else {
+      modal.style.display = 'none';
+    }
+  }
+
+  function updateTrainingStatus() {
+    fetch('/api/training-status')
+      .then(res => res.json())
+      .then(data => {
+        const bell = document.getElementById('training-bell');
+        const badge = document.getElementById('bell-badge');
+        const currentSection = document.getElementById('current-training-section');
+        const queueSection = document.getElementById('queue-section');
+        const noTrainingsMsg = document.getElementById('no-trainings-msg');
+        
+        const totalCount = (data.current ? 1 : 0) + data.queue.length;
+        
+        if (totalCount > 0) {
+          bell.style.background = '#009eac';
+          badge.style.display = 'block';
+          badge.textContent = totalCount;
+        } else {
+          bell.style.background = '#999';
+          badge.style.display = 'none';
+        }
+        
+        if (data.current) {
+          currentSection.style.display = 'block';
+          noTrainingsMsg.style.display = 'none';
+          
+          const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+          document.getElementById('current-training-info').innerHTML = `
+            <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+              <strong>${data.current.name || 'Training'}</strong>
+              <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+            </div>
+            <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+              <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+            </div>
+            <div style="font-size: 14px; color: #666;">
+              Epoch ${data.current.iteration} / ${data.current.max_epoch}
+            </div>
+          `;
+        } else {
+          currentSection.style.display = 'none';
+        }
+        
+        if (data.queue.length > 0) {
+          queueSection.style.display = 'block';
+          noTrainingsMsg.style.display = 'none';
+          document.getElementById('queue-count').textContent = data.queue.length;
+          
+          document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+            <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+              <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+              <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                ${t.max_epoch} epochs • Waiting...
+              </div>
+            </div>
+          `).join('');
+        } else {
+          queueSection.style.display = 'none';
+        }
+        
+        if (totalCount === 0) {
+          noTrainingsMsg.style.display = 'block';
+        }
+      })
+      .catch(err => console.error('Failed to fetch training status:', err));
+  }
+
+  window.addEventListener('DOMContentLoaded', function() {
+    updateTrainingStatus();
+    trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+  });
+
+  window.addEventListener('beforeunload', function() {
+    if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+  });
+</script>
 </body></html>

index.html

@@ -28,6 +28,14 @@
       <icon class="header-icon" onclick="window.location.href='/index.html'" , onmouseover="" style="cursor: pointer;"
         src="./media/logo.png" alt="Logo"></icon>
       <div class="button-row">
+        <!-- Training Notification Bell -->
+        <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+          style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+          🔔
+          <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+            color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+            text-align: center; font-weight: bold;">0</span>
+        </button>
         <button id="Add Training Project" onclick="window.location.href='/add-project.html'" class="button-red">Add
           Training Project</button>
         <button id="seed-db-btn" class="button">
@@ -159,7 +167,133 @@
     </div>
   </div>
 
+  <!-- Training Status Modal -->
+  <div id="training-status-modal" class="modal" style="display: none;">
+      <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+          <div class="modal-header">
+              <h2>Training Status</h2>
+              <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+          </div>
+          
+          <div class="modal-body">
+              <!-- Current Training -->
+              <div class="settings-section" id="current-training-section" style="display: none;">
+                  <h3 style="color: #009eac;">Current Training</h3>
+                  <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- Queued Trainings -->
+              <div class="settings-section" id="queue-section" style="display: none;">
+                  <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                  <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- No trainings message -->
+              <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                  No trainings running or queued.
+              </div>
+          </div>
+      </div>
+  </div>
+
   <script src="js/settings.js"></script>
+  <script>
+    // Training status polling
+    let trainingStatusPoller = null;
+
+    function toggleTrainingModal() {
+      const modal = document.getElementById('training-status-modal');
+      if (modal.style.display === 'none') {
+        modal.style.display = 'flex';
+        updateTrainingStatus(); // Immediate update
+      } else {
+        modal.style.display = 'none';
+      }
+    }
+
+    function updateTrainingStatus() {
+      fetch('/api/training-status')
+        .then(res => res.json())
+        .then(data => {
+          const bell = document.getElementById('training-bell');
+          const badge = document.getElementById('bell-badge');
+          const currentSection = document.getElementById('current-training-section');
+          const queueSection = document.getElementById('queue-section');
+          const noTrainingsMsg = document.getElementById('no-trainings-msg');
+          
+          const totalCount = (data.current ? 1 : 0) + data.queue.length;
+          
+          // Update bell appearance
+          if (totalCount > 0) {
+            bell.style.background = '#009eac';
+            badge.style.display = 'block';
+            badge.textContent = totalCount;
+          } else {
+            bell.style.background = '#999';
+            badge.style.display = 'none';
+          }
+          
+          // Update modal content
+          if (data.current) {
+            currentSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            
+            const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+            document.getElementById('current-training-info').innerHTML = `
+              <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+                <strong>${data.current.name || 'Training'}</strong>
+                <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+              </div>
+              <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+                <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+              </div>
+              <div style="font-size: 14px; color: #666;">
+                Epoch ${data.current.iteration} / ${data.current.max_epoch}
+              </div>
+            `;
+          } else {
+            currentSection.style.display = 'none';
+          }
+          
+          if (data.queue.length > 0) {
+            queueSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            document.getElementById('queue-count').textContent = data.queue.length;
+            
+            document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+              <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+                <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+                <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                  ${t.max_epoch} epochs • Waiting...
+                </div>
+              </div>
+            `).join('');
+          } else {
+            queueSection.style.display = 'none';
+          }
+          
+          if (totalCount === 0) {
+            noTrainingsMsg.style.display = 'block';
+          }
+        })
+        .catch(err => console.error('Failed to fetch training status:', err));
+    }
+
+    // Poll every 5 seconds
+    window.addEventListener('DOMContentLoaded', function() {
+      updateTrainingStatus();
+      trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+    });
+
+    // Stop polling when page unloads
+    window.addEventListener('beforeunload', function() {
+      if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+    });
+  </script>
 </body>
 
 </html>

overview-training.html

@@ -30,6 +30,14 @@
       <label id="project-title-label"
         style="display: block; text-align: left; font-weight: bold; font-size: x-large;">Project</label>
       <div class="button-row">
+        <!-- Training Notification Bell -->
+        <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+          style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+          🔔
+          <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+            color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+            text-align: center; font-weight: bold;">0</span>
+        </button>
         <button id="Add Training Project" onclick="window.location.href='/add-project.html'" class="button-red">Add
           Training Project</button>
         <button id="seed-db-btn" class="button">
@@ -44,10 +52,7 @@
     </div>
       </button>
 
-      </button>
+
-        <button id="setup-details" class="button">
-          Show Details
-        </button>
 
     <script>
       document.getElementById('seed-db-btn').addEventListener('click', function () {
@@ -156,14 +161,15 @@
           };
           btnDiv.appendChild(startBtn);
 
-          // View Log button
+          // View Training Details button
-          const logBtn = document.createElement('button');
+          const detailsBtn = document.createElement('button');
-          logBtn.textContent = 'View Training Log';
+          detailsBtn.textContent = 'View Training Details';
-          logBtn.style = 'background:#666;color:white;border:none;border-radius:6px;padding:6px 12px;cursor:pointer;';
+          detailsBtn.style = 'background:#666;color:white;border:none;border-radius:6px;padding:6px 12px;cursor:pointer;';
-          logBtn.onclick = function() {
+          detailsBtn.onclick = function() {
-            showLogModal(training.id);
+            // Navigate to edit-training page in read-only mode
+            window.location.href = `/edit-training.html?training_id=${training.id}&readonly=true`;
           };
-          btnDiv.appendChild(logBtn);
+          btnDiv.appendChild(detailsBtn);
 
           // Remove button
           const removeBtn = document.createElement('button');
@@ -319,7 +325,133 @@
       </div>
   </div>
 
+  <!-- Training Status Modal -->
+  <div id="training-status-modal" class="modal" style="display: none;">
+      <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+          <div class="modal-header">
+              <h2>Training Status</h2>
+              <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+          </div>
+          
+          <div class="modal-body">
+              <!-- Current Training -->
+              <div class="settings-section" id="current-training-section" style="display: none;">
+                  <h3 style="color: #009eac;">Current Training</h3>
+                  <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- Queued Trainings -->
+              <div class="settings-section" id="queue-section" style="display: none;">
+                  <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                  <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- No trainings message -->
+              <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                  No trainings running or queued.
+              </div>
+          </div>
+      </div>
+  </div>
+
   <script src="js/settings.js"></script>
+  <script>
+    // Training status polling
+    let trainingStatusPoller = null;
+
+    function toggleTrainingModal() {
+      const modal = document.getElementById('training-status-modal');
+      if (modal.style.display === 'none') {
+        modal.style.display = 'flex';
+        updateTrainingStatus(); // Immediate update
+      } else {
+        modal.style.display = 'none';
+      }
+    }
+
+    function updateTrainingStatus() {
+      fetch('/api/training-status')
+        .then(res => res.json())
+        .then(data => {
+          const bell = document.getElementById('training-bell');
+          const badge = document.getElementById('bell-badge');
+          const currentSection = document.getElementById('current-training-section');
+          const queueSection = document.getElementById('queue-section');
+          const noTrainingsMsg = document.getElementById('no-trainings-msg');
+          
+          const totalCount = (data.current ? 1 : 0) + data.queue.length;
+          
+          // Update bell appearance
+          if (totalCount > 0) {
+            bell.style.background = '#009eac';
+            badge.style.display = 'block';
+            badge.textContent = totalCount;
+          } else {
+            bell.style.background = '#999';
+            badge.style.display = 'none';
+          }
+          
+          // Update modal content
+          if (data.current) {
+            currentSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            
+            const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+            document.getElementById('current-training-info').innerHTML = `
+              <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+                <strong>${data.current.name || 'Training'}</strong>
+                <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+              </div>
+              <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+                <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+              </div>
+              <div style="font-size: 14px; color: #666;">
+                Epoch ${data.current.iteration} / ${data.current.max_epoch}
+              </div>
+            `;
+          } else {
+            currentSection.style.display = 'none';
+          }
+          
+          if (data.queue.length > 0) {
+            queueSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            document.getElementById('queue-count').textContent = data.queue.length;
+            
+            document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+              <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+                <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+                <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                  ${t.max_epoch} epochs • Waiting...
+                </div>
+              </div>
+            `).join('');
+          } else {
+            queueSection.style.display = 'none';
+          }
+          
+          if (totalCount === 0) {
+            noTrainingsMsg.style.display = 'block';
+          }
+        })
+        .catch(err => console.error('Failed to fetch training status:', err));
+    }
+
+    // Poll every 5 seconds
+    window.addEventListener('DOMContentLoaded', function() {
+      updateTrainingStatus();
+      trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+    });
+
+    // Stop polling when page unloads
+    window.addEventListener('beforeunload', function() {
+      if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+    });
+  </script>
 </body>
 
 </html>

project-details.html

@@ -32,6 +32,14 @@
                 style="cursor: pointer;" src="./media/logo.png" alt="Logo"></icon>
             <label id="project-title-label" style="display: block; text-align: left; font-weight: bold; font-size: x-large;">title</label>
             <div class="button-row">
+                <!-- Training Notification Bell -->
+                <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+                  style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+                  🔔
+                  <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+                    color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+                    text-align: center; font-weight: bold;">0</span>
+                </button>
                 <button id="Add Training Project" onclick="window.location.href='/add-project.html'"
                     class="button-red">Add Training Project</button>
                 <button id="seed-db-btn" class="button">
@@ -177,7 +185,123 @@
         </div>
     </div>
 
+    <!-- Training Status Modal -->
+    <div id="training-status-modal" class="modal" style="display: none;">
+        <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+            <div class="modal-header">
+                <h2>Training Status</h2>
+                <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+            </div>
+            
+            <div class="modal-body">
+                <div class="settings-section" id="current-training-section" style="display: none;">
+                    <h3 style="color: #009eac;">Current Training</h3>
+                    <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                    </div>
+                </div>
+
+                <div class="settings-section" id="queue-section" style="display: none;">
+                    <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                    <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                    </div>
+                </div>
+
+                <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                    No trainings running or queued.
+                </div>
+            </div>
+        </div>
+    </div>
+
     <script src="js/settings.js"></script>
+    <script>
+      let trainingStatusPoller = null;
+
+      function toggleTrainingModal() {
+        const modal = document.getElementById('training-status-modal');
+        if (modal.style.display === 'none') {
+          modal.style.display = 'flex';
+          updateTrainingStatus();
+        } else {
+          modal.style.display = 'none';
+        }
+      }
+
+      function updateTrainingStatus() {
+        fetch('/api/training-status')
+          .then(res => res.json())
+          .then(data => {
+            const bell = document.getElementById('training-bell');
+            const badge = document.getElementById('bell-badge');
+            const currentSection = document.getElementById('current-training-section');
+            const queueSection = document.getElementById('queue-section');
+            const noTrainingsMsg = document.getElementById('no-trainings-msg');
+            
+            const totalCount = (data.current ? 1 : 0) + data.queue.length;
+            
+            if (totalCount > 0) {
+              bell.style.background = '#009eac';
+              badge.style.display = 'block';
+              badge.textContent = totalCount;
+            } else {
+              bell.style.background = '#999';
+              badge.style.display = 'none';
+            }
+            
+            if (data.current) {
+              currentSection.style.display = 'block';
+              noTrainingsMsg.style.display = 'none';
+              
+              const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+              document.getElementById('current-training-info').innerHTML = `
+                <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+                  <strong>${data.current.name || 'Training'}</strong>
+                  <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+                </div>
+                <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+                  <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+                </div>
+                <div style="font-size: 14px; color: #666;">
+                  Epoch ${data.current.iteration} / ${data.current.max_epoch}
+                </div>
+              `;
+            } else {
+              currentSection.style.display = 'none';
+            }
+            
+            if (data.queue.length > 0) {
+              queueSection.style.display = 'block';
+              noTrainingsMsg.style.display = 'none';
+              document.getElementById('queue-count').textContent = data.queue.length;
+              
+              document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+                <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+                  <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+                  <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                    ${t.max_epoch} epochs • Waiting...
+                  </div>
+                </div>
+              `).join('');
+            } else {
+              queueSection.style.display = 'none';
+            }
+            
+            if (totalCount === 0) {
+              noTrainingsMsg.style.display = 'block';
+            }
+          })
+          .catch(err => console.error('Failed to fetch training status:', err));
+      }
+
+      window.addEventListener('DOMContentLoaded', function() {
+        updateTrainingStatus();
+        trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+      });
+
+      window.addEventListener('beforeunload', function() {
+        if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+      });
+    </script>
 </body>
 
 </html>

setup-training-project.html

@@ -29,6 +29,14 @@
         src="./media/logo.png" alt="Logo"></icon>
         <label id="project-title-label" style="display: block; text-align: left; font-weight: bold; font-size: x-large;">title</label>
       <div class="button-row">
+        <!-- Training Notification Bell -->
+        <button id="training-bell" onclick="toggleTrainingModal()" class="button" title="Training Status" 
+          style="padding: 8px 16px; margin-right: 10px; position: relative; background: #999;">
+          🔔
+          <span id="bell-badge" style="display: none; position: absolute; top: -5px; right: -5px; background: #ff4d4f; 
+            color: white; border-radius: 50%; width: 20px; height: 20px; font-size: 12px; line-height: 20px; 
+            text-align: center; font-weight: bold;">0</span>
+        </button>
         <button id="Add Training Project" onclick="window.location.href='/add-project.html'" class="button-red">Add
           Training Project</button>
         <button id="seed-db-btn" class="button">
@@ -170,7 +178,129 @@
       </div>
   </div>
 
+  <!-- Training Status Modal -->
+  <div id="training-status-modal" class="modal" style="display: none;">
+      <div class="modal-content" style="max-width: 700px; max-height: 90vh; overflow-y: auto;">
+          <div class="modal-header">
+              <h2>Training Status</h2>
+              <button class="close-btn" onclick="toggleTrainingModal()">&times;</button>
+          </div>
+          
+          <div class="modal-body">
+              <!-- Current Training -->
+              <div class="settings-section" id="current-training-section" style="display: none;">
+                  <h3 style="color: #009eac;">Current Training</h3>
+                  <div id="current-training-info" style="background: #eaf7fa; padding: 16px; border-radius: 8px; margin-bottom: 16px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- Queued Trainings -->
+              <div class="settings-section" id="queue-section" style="display: none;">
+                  <h3 style="color: #666;">Queue (<span id="queue-count">0</span>)</h3>
+                  <div id="queue-list" style="display: flex; flex-direction: column; gap: 12px;">
+                      <!-- Populated by JS -->
+                  </div>
+              </div>
+
+              <!-- No trainings message -->
+              <div id="no-trainings-msg" style="text-align: center; padding: 32px; color: #666;">
+                  No trainings running or queued.
+              </div>
+          </div>
+      </div>
+  </div>
+
   <script src="js/settings.js"></script>
+  <script>
+    // Training status polling
+    let trainingStatusPoller = null;
+
+    function toggleTrainingModal() {
+      const modal = document.getElementById('training-status-modal');
+      if (modal.style.display === 'none') {
+        modal.style.display = 'flex';
+        updateTrainingStatus();
+      } else {
+        modal.style.display = 'none';
+      }
+    }
+
+    function updateTrainingStatus() {
+      fetch('/api/training-status')
+        .then(res => res.json())
+        .then(data => {
+          const bell = document.getElementById('training-bell');
+          const badge = document.getElementById('bell-badge');
+          const currentSection = document.getElementById('current-training-section');
+          const queueSection = document.getElementById('queue-section');
+          const noTrainingsMsg = document.getElementById('no-trainings-msg');
+          
+          const totalCount = (data.current ? 1 : 0) + data.queue.length;
+          
+          if (totalCount > 0) {
+            bell.style.background = '#009eac';
+            badge.style.display = 'block';
+            badge.textContent = totalCount;
+          } else {
+            bell.style.background = '#999';
+            badge.style.display = 'none';
+          }
+          
+          if (data.current) {
+            currentSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            
+            const percentage = Math.round((data.current.iteration / data.current.max_epoch) * 100);
+            document.getElementById('current-training-info').innerHTML = `
+              <div style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+                <strong>${data.current.name || 'Training'}</strong>
+                <span style="font-weight: bold; color: #009eac;">${percentage}%</span>
+              </div>
+              <div style="background: #ddd; border-radius: 4px; height: 24px; overflow: hidden; margin-bottom: 8px;">
+                <div style="background: #009eac; height: 100%; width: ${percentage}%; transition: width 0.3s;"></div>
+              </div>
+              <div style="font-size: 14px; color: #666;">
+                Epoch ${data.current.iteration} / ${data.current.max_epoch}
+              </div>
+            `;
+          } else {
+            currentSection.style.display = 'none';
+          }
+          
+          if (data.queue.length > 0) {
+            queueSection.style.display = 'block';
+            noTrainingsMsg.style.display = 'none';
+            document.getElementById('queue-count').textContent = data.queue.length;
+            
+            document.getElementById('queue-list').innerHTML = data.queue.map((t, idx) => `
+              <div style="background: #f5f5f5; padding: 12px; border-radius: 8px; border-left: 4px solid #009eac;">
+                <strong>#${idx + 1}: ${t.name || 'Training'}</strong>
+                <div style="font-size: 13px; color: #666; margin-top: 4px;">
+                  ${t.max_epoch} epochs • Waiting...
+                </div>
+              </div>
+            `).join('');
+          } else {
+            queueSection.style.display = 'none';
+          }
+          
+          if (totalCount === 0) {
+            noTrainingsMsg.style.display = 'block';
+          }
+        })
+        .catch(err => console.error('Failed to fetch training status:', err));
+    }
+
+    window.addEventListener('DOMContentLoaded', function() {
+      updateTrainingStatus();
+      trainingStatusPoller = setInterval(updateTrainingStatus, 5000);
+    });
+
+    window.addEventListener('beforeunload', function() {
+      if (trainingStatusPoller) clearInterval(trainingStatusPoller);
+    });
+  </script>
 </body>
 
 </html>

venv/bin/Activate.ps1

@@ -0,0 +1,247 @@
+<#
+.Synopsis
+Activate a Python virtual environment for the current PowerShell session.
+
+.Description
+Pushes the python executable for a virtual environment to the front of the
+$Env:PATH environment variable and sets the prompt to signify that you are
+in a Python virtual environment. Makes use of the command line switches as
+well as the `pyvenv.cfg` file values present in the virtual environment.
+
+.Parameter VenvDir
+Path to the directory that contains the virtual environment to activate. The
+default value for this is the parent of the directory that the Activate.ps1
+script is located within.
+
+.Parameter Prompt
+The prompt prefix to display when this virtual environment is activated. By
+default, this prompt is the name of the virtual environment folder (VenvDir)
+surrounded by parentheses and followed by a single space (ie. '(.venv) ').
+
+.Example
+Activate.ps1
+Activates the Python virtual environment that contains the Activate.ps1 script.
+
+.Example
+Activate.ps1 -Verbose
+Activates the Python virtual environment that contains the Activate.ps1 script,
+and shows extra information about the activation as it executes.
+
+.Example
+Activate.ps1 -VenvDir C:\Users\MyUser\Common\.venv
+Activates the Python virtual environment located in the specified location.
+
+.Example
+Activate.ps1 -Prompt "MyPython"
+Activates the Python virtual environment that contains the Activate.ps1 script,
+and prefixes the current prompt with the specified string (surrounded in
+parentheses) while the virtual environment is active.
+
+.Notes
+On Windows, it may be required to enable this Activate.ps1 script by setting the
+execution policy for the user. You can do this by issuing the following PowerShell
+command:
+
+PS C:\> Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser
+
+For more information on Execution Policies: 
+https://go.microsoft.com/fwlink/?LinkID=135170
+
+#>
+Param(
+    [Parameter(Mandatory = $false)]
+    [String]
+    $VenvDir,
+    [Parameter(Mandatory = $false)]
+    [String]
+    $Prompt
+)
+
+<# Function declarations --------------------------------------------------- #>
+
+<#
+.Synopsis
+Remove all shell session elements added by the Activate script, including the
+addition of the virtual environment's Python executable from the beginning of
+the PATH variable.
+
+.Parameter NonDestructive
+If present, do not remove this function from the global namespace for the
+session.
+
+#>
+function global:deactivate ([switch]$NonDestructive) {
+    # Revert to original values
+
+    # The prior prompt:
+    if (Test-Path -Path Function:_OLD_VIRTUAL_PROMPT) {
+        Copy-Item -Path Function:_OLD_VIRTUAL_PROMPT -Destination Function:prompt
+        Remove-Item -Path Function:_OLD_VIRTUAL_PROMPT
+    }
+
+    # The prior PYTHONHOME:
+    if (Test-Path -Path Env:_OLD_VIRTUAL_PYTHONHOME) {
+        Copy-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME -Destination Env:PYTHONHOME
+        Remove-Item -Path Env:_OLD_VIRTUAL_PYTHONHOME
+    }
+
+    # The prior PATH:
+    if (Test-Path -Path Env:_OLD_VIRTUAL_PATH) {
+        Copy-Item -Path Env:_OLD_VIRTUAL_PATH -Destination Env:PATH
+        Remove-Item -Path Env:_OLD_VIRTUAL_PATH
+    }
+
+    # Just remove the VIRTUAL_ENV altogether:
+    if (Test-Path -Path Env:VIRTUAL_ENV) {
+        Remove-Item -Path env:VIRTUAL_ENV
+    }
+
+    # Just remove VIRTUAL_ENV_PROMPT altogether.
+    if (Test-Path -Path Env:VIRTUAL_ENV_PROMPT) {
+        Remove-Item -Path env:VIRTUAL_ENV_PROMPT
+    }
+
+    # Just remove the _PYTHON_VENV_PROMPT_PREFIX altogether:
+    if (Get-Variable -Name "_PYTHON_VENV_PROMPT_PREFIX" -ErrorAction SilentlyContinue) {
+        Remove-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Scope Global -Force
+    }
+
+    # Leave deactivate function in the global namespace if requested:
+    if (-not $NonDestructive) {
+        Remove-Item -Path function:deactivate
+    }
+}
+
+<#
+.Description
+Get-PyVenvConfig parses the values from the pyvenv.cfg file located in the
+given folder, and returns them in a map.
+
+For each line in the pyvenv.cfg file, if that line can be parsed into exactly
+two strings separated by `=` (with any amount of whitespace surrounding the =)
+then it is considered a `key = value` line. The left hand string is the key,
+the right hand is the value.
+
+If the value starts with a `'` or a `"` then the first and last character is
+stripped from the value before being captured.
+
+.Parameter ConfigDir
+Path to the directory that contains the `pyvenv.cfg` file.
+#>
+function Get-PyVenvConfig(
+    [String]
+    $ConfigDir
+) {
+    Write-Verbose "Given ConfigDir=$ConfigDir, obtain values in pyvenv.cfg"
+
+    # Ensure the file exists, and issue a warning if it doesn't (but still allow the function to continue).
+    $pyvenvConfigPath = Join-Path -Resolve -Path $ConfigDir -ChildPath 'pyvenv.cfg' -ErrorAction Continue
+
+    # An empty map will be returned if no config file is found.
+    $pyvenvConfig = @{ }
+
+    if ($pyvenvConfigPath) {
+
+        Write-Verbose "File exists, parse `key = value` lines"
+        $pyvenvConfigContent = Get-Content -Path $pyvenvConfigPath
+
+        $pyvenvConfigContent | ForEach-Object {
+            $keyval = $PSItem -split "\s*=\s*", 2
+            if ($keyval[0] -and $keyval[1]) {
+                $val = $keyval[1]
+
+                # Remove extraneous quotations around a string value.
+                if ("'""".Contains($val.Substring(0, 1))) {
+                    $val = $val.Substring(1, $val.Length - 2)
+                }
+
+                $pyvenvConfig[$keyval[0]] = $val
+                Write-Verbose "Adding Key: '$($keyval[0])'='$val'"
+            }
+        }
+    }
+    return $pyvenvConfig
+}
+
+
+<# Begin Activate script --------------------------------------------------- #>
+
+# Determine the containing directory of this script
+$VenvExecPath = Split-Path -Parent $MyInvocation.MyCommand.Definition
+$VenvExecDir = Get-Item -Path $VenvExecPath
+
+Write-Verbose "Activation script is located in path: '$VenvExecPath'"
+Write-Verbose "VenvExecDir Fullname: '$($VenvExecDir.FullName)"
+Write-Verbose "VenvExecDir Name: '$($VenvExecDir.Name)"
+
+# Set values required in priority: CmdLine, ConfigFile, Default
+# First, get the location of the virtual environment, it might not be
+# VenvExecDir if specified on the command line.
+if ($VenvDir) {
+    Write-Verbose "VenvDir given as parameter, using '$VenvDir' to determine values"
+}
+else {
+    Write-Verbose "VenvDir not given as a parameter, using parent directory name as VenvDir."
+    $VenvDir = $VenvExecDir.Parent.FullName.TrimEnd("\\/")
+    Write-Verbose "VenvDir=$VenvDir"
+}
+
+# Next, read the `pyvenv.cfg` file to determine any required value such
+# as `prompt`.
+$pyvenvCfg = Get-PyVenvConfig -ConfigDir $VenvDir
+
+# Next, set the prompt from the command line, or the config file, or
+# just use the name of the virtual environment folder.
+if ($Prompt) {
+    Write-Verbose "Prompt specified as argument, using '$Prompt'"
+}
+else {
+    Write-Verbose "Prompt not specified as argument to script, checking pyvenv.cfg value"
+    if ($pyvenvCfg -and $pyvenvCfg['prompt']) {
+        Write-Verbose "  Setting based on value in pyvenv.cfg='$($pyvenvCfg['prompt'])'"
+        $Prompt = $pyvenvCfg['prompt'];
+    }
+    else {
+        Write-Verbose "  Setting prompt based on parent's directory's name. (Is the directory name passed to venv module when creating the virtual environment)"
+        Write-Verbose "  Got leaf-name of $VenvDir='$(Split-Path -Path $venvDir -Leaf)'"
+        $Prompt = Split-Path -Path $venvDir -Leaf
+    }
+}
+
+Write-Verbose "Prompt = '$Prompt'"
+Write-Verbose "VenvDir='$VenvDir'"
+
+# Deactivate any currently active virtual environment, but leave the
+# deactivate function in place.
+deactivate -nondestructive
+
+# Now set the environment variable VIRTUAL_ENV, used by many tools to determine
+# that there is an activated venv.
+$env:VIRTUAL_ENV = $VenvDir
+
+if (-not $Env:VIRTUAL_ENV_DISABLE_PROMPT) {
+
+    Write-Verbose "Setting prompt to '$Prompt'"
+
+    # Set the prompt to include the env name
+    # Make sure _OLD_VIRTUAL_PROMPT is global
+    function global:_OLD_VIRTUAL_PROMPT { "" }
+    Copy-Item -Path function:prompt -Destination function:_OLD_VIRTUAL_PROMPT
+    New-Variable -Name _PYTHON_VENV_PROMPT_PREFIX -Description "Python virtual environment prompt prefix" -Scope Global -Option ReadOnly -Visibility Public -Value $Prompt
+
+    function global:prompt {
+        Write-Host -NoNewline -ForegroundColor Green "($_PYTHON_VENV_PROMPT_PREFIX) "
+        _OLD_VIRTUAL_PROMPT
+    }
+    $env:VIRTUAL_ENV_PROMPT = $Prompt
+}
+
+# Clear PYTHONHOME
+if (Test-Path -Path Env:PYTHONHOME) {
+    Copy-Item -Path Env:PYTHONHOME -Destination Env:_OLD_VIRTUAL_PYTHONHOME
+    Remove-Item -Path Env:PYTHONHOME
+}
+
+# Add the venv to the PATH
+Copy-Item -Path Env:PATH -Destination Env:_OLD_VIRTUAL_PATH
+$Env:PATH = "$VenvExecDir$([System.IO.Path]::PathSeparator)$Env:PATH"

venv/bin/activate

@@ -0,0 +1,69 @@
+# This file must be used with "source bin/activate" *from bash*
+# you cannot run it directly
+
+deactivate () {
+    # reset old environment variables
+    if [ -n "${_OLD_VIRTUAL_PATH:-}" ] ; then
+        PATH="${_OLD_VIRTUAL_PATH:-}"
+        export PATH
+        unset _OLD_VIRTUAL_PATH
+    fi
+    if [ -n "${_OLD_VIRTUAL_PYTHONHOME:-}" ] ; then
+        PYTHONHOME="${_OLD_VIRTUAL_PYTHONHOME:-}"
+        export PYTHONHOME
+        unset _OLD_VIRTUAL_PYTHONHOME
+    fi
+
+    # This should detect bash and zsh, which have a hash command that must
+    # be called to get it to forget past commands.  Without forgetting
+    # past commands the $PATH changes we made may not be respected
+    if [ -n "${BASH:-}" -o -n "${ZSH_VERSION:-}" ] ; then
+        hash -r 2> /dev/null
+    fi
+
+    if [ -n "${_OLD_VIRTUAL_PS1:-}" ] ; then
+        PS1="${_OLD_VIRTUAL_PS1:-}"
+        export PS1
+        unset _OLD_VIRTUAL_PS1
+    fi
+
+    unset VIRTUAL_ENV
+    unset VIRTUAL_ENV_PROMPT
+    if [ ! "${1:-}" = "nondestructive" ] ; then
+    # Self destruct!
+        unset -f deactivate
+    fi
+}
+
+# unset irrelevant variables
+deactivate nondestructive
+
+VIRTUAL_ENV=/home/kitraining/coco-tool/Abschluss-Projekt/venv
+export VIRTUAL_ENV
+
+_OLD_VIRTUAL_PATH="$PATH"
+PATH="$VIRTUAL_ENV/"bin":$PATH"
+export PATH
+
+# unset PYTHONHOME if set
+# this will fail if PYTHONHOME is set to the empty string (which is bad anyway)
+# could use `if (set -u; : $PYTHONHOME) ;` in bash
+if [ -n "${PYTHONHOME:-}" ] ; then
+    _OLD_VIRTUAL_PYTHONHOME="${PYTHONHOME:-}"
+    unset PYTHONHOME
+fi
+
+if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT:-}" ] ; then
+    _OLD_VIRTUAL_PS1="${PS1:-}"
+    PS1='(venv) '"${PS1:-}"
+    export PS1
+    VIRTUAL_ENV_PROMPT='(venv) '
+    export VIRTUAL_ENV_PROMPT
+fi
+
+# This should detect bash and zsh, which have a hash command that must
+# be called to get it to forget past commands.  Without forgetting
+# past commands the $PATH changes we made may not be respected
+if [ -n "${BASH:-}" -o -n "${ZSH_VERSION:-}" ] ; then
+    hash -r 2> /dev/null
+fi

venv/bin/activate.csh

@@ -0,0 +1,26 @@
+# This file must be used with "source bin/activate.csh" *from csh*.
+# You cannot run it directly.
+# Created by Davide Di Blasi <davidedb@gmail.com>.
+# Ported to Python 3.3 venv by Andrew Svetlov <andrew.svetlov@gmail.com>
+
+alias deactivate 'test $?_OLD_VIRTUAL_PATH != 0 && setenv PATH "$_OLD_VIRTUAL_PATH" && unset _OLD_VIRTUAL_PATH; rehash; test $?_OLD_VIRTUAL_PROMPT != 0 && set prompt="$_OLD_VIRTUAL_PROMPT" && unset _OLD_VIRTUAL_PROMPT; unsetenv VIRTUAL_ENV; unsetenv VIRTUAL_ENV_PROMPT; test "\!:*" != "nondestructive" && unalias deactivate'
+
+# Unset irrelevant variables.
+deactivate nondestructive
+
+setenv VIRTUAL_ENV /home/kitraining/coco-tool/Abschluss-Projekt/venv
+
+set _OLD_VIRTUAL_PATH="$PATH"
+setenv PATH "$VIRTUAL_ENV/"bin":$PATH"
+
+
+set _OLD_VIRTUAL_PROMPT="$prompt"
+
+if (! "$?VIRTUAL_ENV_DISABLE_PROMPT") then
+    set prompt = '(venv) '"$prompt"
+    setenv VIRTUAL_ENV_PROMPT '(venv) '
+endif
+
+alias pydoc python -m pydoc
+
+rehash

venv/bin/activate.fish

@@ -0,0 +1,69 @@
+# This file must be used with "source <venv>/bin/activate.fish" *from fish*
+# (https://fishshell.com/); you cannot run it directly.
+
+function deactivate  -d "Exit virtual environment and return to normal shell environment"
+    # reset old environment variables
+    if test -n "$_OLD_VIRTUAL_PATH"
+        set -gx PATH $_OLD_VIRTUAL_PATH
+        set -e _OLD_VIRTUAL_PATH
+    end
+    if test -n "$_OLD_VIRTUAL_PYTHONHOME"
+        set -gx PYTHONHOME $_OLD_VIRTUAL_PYTHONHOME
+        set -e _OLD_VIRTUAL_PYTHONHOME
+    end
+
+    if test -n "$_OLD_FISH_PROMPT_OVERRIDE"
+        set -e _OLD_FISH_PROMPT_OVERRIDE
+        # prevents error when using nested fish instances (Issue #93858)
+        if functions -q _old_fish_prompt
+            functions -e fish_prompt
+            functions -c _old_fish_prompt fish_prompt
+            functions -e _old_fish_prompt
+        end
+    end
+
+    set -e VIRTUAL_ENV
+    set -e VIRTUAL_ENV_PROMPT
+    if test "$argv[1]" != "nondestructive"
+        # Self-destruct!
+        functions -e deactivate
+    end
+end
+
+# Unset irrelevant variables.
+deactivate nondestructive
+
+set -gx VIRTUAL_ENV /home/kitraining/coco-tool/Abschluss-Projekt/venv
+
+set -gx _OLD_VIRTUAL_PATH $PATH
+set -gx PATH "$VIRTUAL_ENV/"bin $PATH
+
+# Unset PYTHONHOME if set.
+if set -q PYTHONHOME
+    set -gx _OLD_VIRTUAL_PYTHONHOME $PYTHONHOME
+    set -e PYTHONHOME
+end
+
+if test -z "$VIRTUAL_ENV_DISABLE_PROMPT"
+    # fish uses a function instead of an env var to generate the prompt.
+
+    # Save the current fish_prompt function as the function _old_fish_prompt.
+    functions -c fish_prompt _old_fish_prompt
+
+    # With the original prompt function renamed, we can override with our own.
+    function fish_prompt
+        # Save the return status of the last command.
+        set -l old_status $status
+
+        # Output the venv prompt; color taken from the blue of the Python logo.
+        printf "%s%s%s" (set_color 4B8BBE) '(venv) ' (set_color normal)
+
+        # Restore the return status of the previous command.
+        echo "exit $old_status" | .
+        # Output the original/"old" prompt.
+        _old_fish_prompt
+    end
+
+    set -gx _OLD_FISH_PROMPT_OVERRIDE "$VIRTUAL_ENV"
+    set -gx VIRTUAL_ENV_PROMPT '(venv) '
+end