| |
| |
| |
| import numpy as np |
| import os |
| from pathlib import Path |
| import tqdm |
| from PIL import Image |
|
|
|
|
| def convert(input, output): |
| img = np.asarray(Image.open(input)) |
| assert img.dtype == np.uint8 |
| img = img - 1 |
| Image.fromarray(img).save(output) |
|
|
|
|
| if __name__ == "__main__": |
| dataset_dir = Path(os.getenv("DETECTRON2_DATASETS", "datasets")) / "ADEChallengeData2016" |
| for name in ["training", "validation"]: |
| annotation_dir = dataset_dir / "annotations" / name |
| output_dir = dataset_dir / "annotations_detectron2" / name |
| output_dir.mkdir(parents=True, exist_ok=True) |
| for file in tqdm.tqdm(list(annotation_dir.iterdir())): |
| output_file = output_dir / file.name |
| convert(file, output_file) |
|
|