from os import path, replace, remove, listdir, makedirs from os.path import abspath import shutil from datetime import datetime from pathlib import Path from ultralytics import YOLOv10 from constants import current_images_dir, current_labels_dir, annotation_classes, prefix, date_format latest_model = f'models/{prefix}latest.pt' today_folder = f'{prefix}{datetime.now():{date_format}}' train_set = 70 valid_set = 20 test_set = 10 def form_dataset(): makedirs(path.join('datasets', today_folder), exist_ok=True) images = listdir(current_images_dir) train_size = int(len(images) * train_set / 100.0) valid_size = int(len(images) * valid_set / 100.0) move_annotations(images[:train_size], 'train') move_annotations(images[train_size:train_size + valid_size], 'valid') move_annotations(images[train_size + valid_size:], 'test') create_yaml() def move_annotations(images, folder): today_dataset = path.join('datasets', today_folder) destination_images = path.join(today_dataset, folder, 'images') makedirs(destination_images, exist_ok=True) destination_labels = path.join(today_dataset, folder, 'labels') makedirs(destination_labels, exist_ok=True) for image_name in images: image_path = path.join(current_images_dir, image_name) label_name = f'{Path(image_name).stem}.txt' label_path = path.join(current_labels_dir, label_name) if not check_label(label_path): remove(image_path) else: replace(image_path, path.join(destination_images, image_name)) replace(label_path, path.join(destination_labels, label_name)) def check_label(label_path): lines_edited = False if not path.exists(label_path): return False with open(label_path, 'r') as f: lines = f.readlines() for line in lines: for val in line.split(' ')[1:]: if float(val) > 1: lines.remove(line) lines_edited = True if len(lines) == 0: return False if not lines_edited: return True with open(label_path, 'w') as label_write: label_write.writelines(lines) label_write.close() return True def create_yaml(): lines = ['names:'] for c in annotation_classes: lines.append(f'- {annotation_classes[c].name}') lines.append(f'nc: {len(annotation_classes)}') lines.append(f'test: test/images') lines.append(f'train: train/images') lines.append(f'val: valid/images') lines.append('') today_yaml = abspath(path.join('datasets', today_folder, 'data.yaml')) with open(today_yaml, 'w', encoding='utf-8') as f: f.writelines([f'{line}\n' for line in lines]) def revert_to_current(date): def revert_dir(src_dir, dest_dir): for file in listdir(src_dir): s = path.join(src_dir, file) d = path.join(dest_dir, file) replace(s, d) date_dataset = path.join('datasets', f'{prefix}{date}') current_dataset = path.join('datasets', f'{prefix}current') for subset in ['test', 'train', 'valid']: revert_dir(path.join(date_dataset, subset, 'images'), path.join(current_dataset, 'images')) revert_dir(path.join(date_dataset, subset, 'labels'), path.join(current_dataset, 'labels')) shutil.rmtree(date_dataset) if __name__ == '__main__': # form_dataset() # create_yaml() m = latest_model or 'yolov10x.yaml' print(f'Initial model: {m}') model = YOLOv10(latest_model or 'yolov10x.yaml') folder = f'{prefix}2024-06-18' yaml = abspath(path.join('datasets', folder, 'data.yaml')) results = model.train(data=yaml, epochs=100, batch=10, imgsz=640, save_period=1) shutil.copy(f'{results.save_dir}/weights/best.pt', latest_model) shutil.copytree(results.save_dir, f'models/{folder}') shutil.rmtree('runs') shutil.rmtree('models/zombobase-latest')