philipp/Abschluss-Projekt
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

training fix.add global settings

Browse Source
This commit is contained in:
Philipp
2025-12-02 09:55:50 +01:00
parent c3c7e042bb
commit 0e31237b79
7 changed files with 96 additions and 65 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
backend/0815/27/exp_infer.py Normal file
View File

@@ -0,0 +1,28 @@
#!/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

25
backend/asdf/5/exp_infer.py Normal file
View File

@@ -0,0 +1,25 @@
#!/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

12
backend/database/migration_add_image_dimensions.sql Normal file
View File

@@ -0,0 +1,12 @@
-- 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`;

12
backend/database/migration_fix_image_dimensions.sql Normal file
View File

@@ -0,0 +1,12 @@
-- 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;

7
backend/routes/api.py
View File

@@ -152,12 +152,7 @@ def start_yolox_training():
cmd = f'cmd /c ""{venv_activate}" && python tools\\train.py {train_args}"'
else:
# Linux: Use bash with source
# If venv path doesn't end with 'activate', assume it needs bin/activate
if not yolox_venv.endswith('activate'):
venv_activate = os.path.join(yolox_venv, 'bin', 'activate')
else:
venv_activate = yolox_venv
cmd = f'bash -c "source {venv_activate} && python tools/train.py {train_args}"'
cmd = f'bash -c "source {yolox_venv} && python tools/train.py {train_args}"'
print(f'Training command: {cmd}')

57
backend/services/generate_json_yolox.py
View File

@@ -110,60 +110,31 @@ def generate_training_json(training_id):
break
# Construct ABSOLUTE path using data_dir
# Detect platform for proper path handling
import platform
is_windows = platform.system() == 'Windows'
# Normalize data_dir - ensure it uses backslashes for Windows
normalized_data_dir = data_dir.rstrip('/\\').replace('/', '\\')
# Normalize path separators in file_name to forward slashes first (OS-agnostic)
file_name = file_name.replace('\\', '/')
# Normalize data_dir to use forward slashes
normalized_data_dir = data_dir.rstrip('/\\').replace('\\', '/')
# Check if file_name is already an absolute path
is_absolute = False
if is_windows:
# Windows: Check for drive letter (C:/) or UNC path (//server/)
is_absolute = (len(file_name) > 1 and file_name[1] == ':') or file_name.startswith('//')
else:
# Linux/Mac: Check for leading /
is_absolute = file_name.startswith('/')
if not is_absolute:
# Check if already absolute path
if not (file_name.startswith('\\\\') or (len(file_name) > 1 and file_name[1] == ':')):
# It's a relative path, combine with data_dir
if normalized_data_dir.startswith('//'):
# UNC path on Windows
file_name = normalized_data_dir + '/' + file_name
# For UNC paths, we need to manually concatenate to preserve \\
if normalized_data_dir.startswith('\\\\'):
# UNC path
file_name = normalized_data_dir + '\\' + file_name.replace('/', '\\')
else:
# Regular path - use os.path.join but with forward slashes
file_name = os.path.join(normalized_data_dir, file_name).replace('\\', '/')
# Final OS-specific normalization
if is_windows:
# Convert to Windows-style backslashes
# Regular path
file_name = os.path.join(normalized_data_dir, file_name.replace('/', '\\'))
else:
# Already absolute, just normalize separators
file_name = file_name.replace('/', '\\')
else:
# Keep as forward slashes for Linux/Mac
file_name = file_name.replace('\\', '/')
# Get annotations for this image
annotations = Annotation.query.filter_by(image_id=image.image_id).all()
# Ensure width and height are integers and valid
# If missing or invalid, skip this image or use default dimensions
img_width = int(image.width) if image.width else 0
img_height = int(image.height) if image.height else 0
# Skip images with invalid dimensions
if img_width <= 0 or img_height <= 0:
print(f'Warning: Skipping image {file_name} with invalid dimensions: {img_width}x{img_height}')
continue
coco_images.append({
'id': image_id,
'file_name': file_name, # Use absolute path
'width': img_width,
'height': img_height
'width': image.width or 0,
'height': image.height or 0
})
for annotation in annotations:

20
backend/services/generate_yolox_exp.py
View File

@@ -174,10 +174,9 @@ def generate_yolox_inference_exp(training_id, options=None, use_base_config=Fals
'mixup_prob': training.mixup_prob,
'hsv_prob': training.hsv_prob,
'flip_prob': training.flip_prob,
# Convert single values to tuples for YOLOX augmentation parameters
'degrees': (training.degrees, training.degrees) if training.degrees is not None and not isinstance(training.degrees, (list, tuple)) else training.degrees,
'translate': (training.translate, training.translate) if training.translate is not None and not isinstance(training.translate, (list, tuple)) else training.translate,
'shear': (training.shear, training.shear) if training.shear is not None and not isinstance(training.shear, (list, tuple)) else training.shear,
'degrees': training.degrees,
'translate': training.translate,
'shear': training.shear,
'mixup_scale': mixup_scale,
'activation': training.activation,
}
@@ -256,22 +255,11 @@ class Exp(MyExp):
# Format arrays
def format_value(val):
if isinstance(val, (list, tuple)):
# Convert float values to int for size-related parameters
formatted_items = []
for item in val:
# Convert to int if it's a whole number float
if isinstance(item, float) and item.is_integer():
formatted_items.append(str(int(item)))
else:
formatted_items.append(str(item))
return '(' + ', '.join(formatted_items) + ')'
return '(' + ', '.join(map(str, val)) + ')'
elif isinstance(val, bool):
return str(val)
elif isinstance(val, str):
return f'"{val}"'
elif isinstance(val, float) and val.is_integer():
# Convert whole number floats to ints
return str(int(val))
else:
return str(val)