| """Validate YOLO dataset layout and labels against `data.yaml`.""" |
| import os |
| import sys |
| import yaml |
| from glob import glob |
|
|
|
|
| def load_data_yaml(p='data.yaml'): |
| if not os.path.exists(p): |
| print(f'Missing {p}') |
| sys.exit(1) |
| with open(p,'r') as f: |
| return yaml.safe_load(f) |
|
|
|
|
| def find_missing_labels(img_files, label_dir): |
| missing = [] |
| for img in img_files: |
| stem = os.path.splitext(os.path.basename(img))[0] |
| lbl = os.path.join(label_dir, stem + '.txt') |
| if not os.path.exists(lbl): |
| missing.append((img, lbl)) |
| return missing |
|
|
|
|
| def main(): |
| data = load_data_yaml('data.yaml') |
| train_p = data.get('train') |
| val_p = data.get('val') |
| print('Train:', train_p) |
| print('Val: ', val_p) |
|
|
| for name, path in [('train', train_p), ('val', val_p)]: |
| img_dir = path |
| if not os.path.isdir(img_dir): |
| print(f'ERROR: {name} images path not found: {img_dir}') |
| continue |
| imgs = glob(os.path.join(img_dir, '*.*')) |
| imgs = [p for p in imgs if p.lower().endswith(('.jpg','.jpeg','.png','bmp','tif','tiff','webp'))] |
| print(f'{name} images found: {len(imgs)}') |
| lbl_dir = img_dir.replace('images', 'labels') |
| if not os.path.isdir(lbl_dir): |
| print(f'WARNING: labels dir not found for {name}: {lbl_dir}') |
| else: |
| missing = find_missing_labels(imgs, lbl_dir) |
| if missing: |
| print(f'Missing {len(missing)} label files in {lbl_dir}. Example:') |
| for m in missing[:5]: |
| print(' ', m) |
| else: |
| print('All images have corresponding label files.') |
|
|
| print('\nIf there are zero images, add images to the dataset/images/* folders or run the sample generator script:') |
| print(' python scripts/create_sample_dataset.py') |
|
|
| if __name__ == '__main__': |
| main() |
|
|
