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 def get_yaml_path(date_str): date_dataset = path.join('datasets', f'{prefix}{date_str}') date_yaml_path = abspath(path.join(date_dataset, 'data.yaml')) return date_dataset, date_yaml_path today_dataset, today_yaml = get_yaml_path(f'{datetime.now():%Y-%m-%d}') train_set = 70 valid_set = 20 test_set = 10 def form_dataset(): makedirs(today_dataset, 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): 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 path.exists(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 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('') 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() model = YOLOv10('datasets/zombobase-latest.pt' or 'yolov10x.yaml') _, yaml = get_yaml_path('2024-06-09') results = model.train(data=yaml, epochs=2, batch=10, imgsz=640) print(results) res_model = path.join(results['save_dir'], '/weights/best.pt') print(res_model) shutil.copy(res_model, 'datasets/zombobase-latest2.pt') pass