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| import cv2 | |
| import shutil | |
| from tqdm import tqdm | |
| from pathlib import Path | |
| max_size = 2048 | |
| input_dataset_path = r'.\iHarmony4\HAdobe5k' | |
| output_path = f'{input_dataset_path}_resized{max_size}_{max_size}' | |
| input_dataset_path = Path(input_dataset_path) | |
| output_path = Path(output_path) | |
| assert not output_path.exists() | |
| output_path.mkdir() | |
| for subfolder in ['composite_images', 'masks', 'real_images']: | |
| (output_path / subfolder).mkdir() | |
| for annotation_path in input_dataset_path.glob('*.txt'): | |
| shutil.copy(annotation_path, output_path / annotation_path.name) | |
| images_list = sorted(input_dataset_path.rglob('*.jpg')) | |
| images_list.extend(sorted(input_dataset_path.rglob('*.png'))) | |
| for x in tqdm(images_list): | |
| image = cv2.imread(str(x), cv2.IMREAD_UNCHANGED) | |
| new_path = output_path / x.relative_to(input_dataset_path) | |
| new_width = max_size | |
| new_height = max_size | |
| image = cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_LANCZOS4) | |
| if x.suffix == '.jpg': | |
| cv2.imwrite(str(new_path), image, [cv2.IMWRITE_JPEG_QUALITY, 90]) | |
| else: | |
| cv2.imwrite(str(new_path), image) |