File size: 1,905 Bytes
a3a407d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | """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()
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