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| import os | |
| import glob | |
| from PIL import Image | |
| help_msg = """ | |
| The dataset can be downloaded from https://cityscapes-dataset.com. | |
| Please download the datasets [gtFine_trainvaltest.zip] and [leftImg8bit_trainvaltest.zip] and unzip them. | |
| gtFine contains the semantics segmentations. Use --gtFine_dir to specify the path to the unzipped gtFine_trainvaltest directory. | |
| leftImg8bit contains the dashcam photographs. Use --leftImg8bit_dir to specify the path to the unzipped leftImg8bit_trainvaltest directory. | |
| The processed images will be placed at --output_dir. | |
| Example usage: | |
| python prepare_cityscapes_dataset.py --gtFine_dir ./gtFine/ --leftImg8bit_dir ./leftImg8bit --output_dir ./datasets/cityscapes/ | |
| """ | |
| def load_resized_img(path): | |
| return Image.open(path).convert('RGB').resize((256, 256)) | |
| def check_matching_pair(segmap_path, photo_path): | |
| segmap_identifier = os.path.basename(segmap_path).replace('_gtFine_color', '') | |
| photo_identifier = os.path.basename(photo_path).replace('_leftImg8bit', '') | |
| assert segmap_identifier == photo_identifier, \ | |
| "[%s] and [%s] don't seem to be matching. Aborting." % (segmap_path, photo_path) | |
| def process_cityscapes(gtFine_dir, leftImg8bit_dir, output_dir, phase): | |
| save_phase = 'test' if phase == 'val' else 'train' | |
| savedir = os.path.join(output_dir, save_phase) | |
| os.makedirs(savedir, exist_ok=True) | |
| os.makedirs(savedir + 'A', exist_ok=True) | |
| os.makedirs(savedir + 'B', exist_ok=True) | |
| print("Directory structure prepared at %s" % output_dir) | |
| segmap_expr = os.path.join(gtFine_dir, phase) + "/*/*_color.png" | |
| segmap_paths = glob.glob(segmap_expr) | |
| segmap_paths = sorted(segmap_paths) | |
| photo_expr = os.path.join(leftImg8bit_dir, phase) + "/*/*_leftImg8bit.png" | |
| photo_paths = glob.glob(photo_expr) | |
| photo_paths = sorted(photo_paths) | |
| assert len(segmap_paths) == len(photo_paths), \ | |
| "%d images that match [%s], and %d images that match [%s]. Aborting." % (len(segmap_paths), segmap_expr, len(photo_paths), photo_expr) | |
| for i, (segmap_path, photo_path) in enumerate(zip(segmap_paths, photo_paths)): | |
| check_matching_pair(segmap_path, photo_path) | |
| segmap = load_resized_img(segmap_path) | |
| photo = load_resized_img(photo_path) | |
| # data for pix2pix where the two images are placed side-by-side | |
| sidebyside = Image.new('RGB', (512, 256)) | |
| sidebyside.paste(segmap, (256, 0)) | |
| sidebyside.paste(photo, (0, 0)) | |
| savepath = os.path.join(savedir, "%d.jpg" % i) | |
| sidebyside.save(savepath, format='JPEG', subsampling=0, quality=100) | |
| # data for cyclegan where the two images are stored at two distinct directories | |
| savepath = os.path.join(savedir + 'A', "%d_A.jpg" % i) | |
| photo.save(savepath, format='JPEG', subsampling=0, quality=100) | |
| savepath = os.path.join(savedir + 'B', "%d_B.jpg" % i) | |
| segmap.save(savepath, format='JPEG', subsampling=0, quality=100) | |
| if i % (len(segmap_paths) // 10) == 0: | |
| print("%d / %d: last image saved at %s, " % (i, len(segmap_paths), savepath)) | |
| if __name__ == '__main__': | |
| import argparse | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--gtFine_dir', type=str, required=True, | |
| help='Path to the Cityscapes gtFine directory.') | |
| parser.add_argument('--leftImg8bit_dir', type=str, required=True, | |
| help='Path to the Cityscapes leftImg8bit_trainvaltest directory.') | |
| parser.add_argument('--output_dir', type=str, required=True, | |
| default='./datasets/cityscapes', | |
| help='Directory the output images will be written to.') | |
| opt = parser.parse_args() | |
| print(help_msg) | |
| print('Preparing Cityscapes Dataset for val phase') | |
| process_cityscapes(opt.gtFine_dir, opt.leftImg8bit_dir, opt.output_dir, "val") | |
| print('Preparing Cityscapes Dataset for train phase') | |
| process_cityscapes(opt.gtFine_dir, opt.leftImg8bit_dir, opt.output_dir, "train") | |
| print('Done') | |