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104 lines
3.4 KiB
Python
104 lines
3.4 KiB
Python
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# Copyright (c) OpenMMLab. All rights reserved.
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import argparse
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import itertools
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import os.path as osp
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import sys
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import mmcv
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from mmcv import Config, DictAction
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from mmcls.datasets.builder import build_dataset
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from mmcls.registry import VISUALIZERS
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from mmcls.utils import register_all_modules
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def parse_args():
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parser = argparse.ArgumentParser(description='Browse a dataset')
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parser.add_argument('config', help='train config file path')
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parser.add_argument(
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'--output-dir',
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default='./outputs',
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type=str,
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help='If there is no display interface, you can save it')
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parser.add_argument('--not-show', default=False, action='store_true')
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parser.add_argument(
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'--phase',
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default='train',
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type=str,
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choices=['train', 'test', 'val'],
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help='phase of dataset to visualize, accept "train" "test" and "val".'
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' Default train.')
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parser.add_argument(
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'--show-number',
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type=int,
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default=sys.maxsize,
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help='number of images selected to visualize, must bigger than 0. if '
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'the number is bigger than length of dataset, show all the images in '
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'dataset; default "sys.maxsize", show all images in dataset')
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parser.add_argument(
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'--show-interval',
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type=float,
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default=2,
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help='the interval of show (s)')
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parser.add_argument(
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'--rescale-factor',
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type=float,
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help='image rescale factor, which is useful if the output is too '
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'large or too small.')
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parser.add_argument(
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'--cfg-options',
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nargs='+',
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action=DictAction,
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help='override some settings in the used config, the key-value pair '
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'in xxx=yyy format will be merged into config file. If the value to '
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'be overwritten is a list, it should be like key="[a,b]" or key=a,b '
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'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" '
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'Note that the quotation marks are necessary and that no white space '
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'is allowed.')
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args = parser.parse_args()
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return args
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def main():
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args = parse_args()
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cfg = Config.fromfile(args.config)
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if args.cfg_options is not None:
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cfg.merge_from_dict(args.cfg_options)
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# register all modules in mmdet into the registries
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register_all_modules()
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dataloader = cfg[f'{args.phase}_dataloader']
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dataset = build_dataset(dataloader.dataset)
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cfg.visualizer.save_dir = args.output_dir
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visualizer = VISUALIZERS.build(cfg.visualizer)
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visualizer.dataset_meta = dataset.metainfo
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display_number = min(args.show_number, len(dataset))
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progress_bar = mmcv.ProgressBar(display_number)
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for item in itertools.islice(dataset, display_number):
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img = item['inputs'].permute(1, 2, 0).numpy()
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data_sample = item['data_sample'].numpy()
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img_path = osp.basename(item['data_sample'].img_path)
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out_file = osp.join(
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args.output_dir,
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osp.basename(img_path)) if args.output_dir is not None else None
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img = img[..., [2, 1, 0]] # bgr to rgb
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visualizer.add_datasample(
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osp.basename(img_path),
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img,
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data_sample,
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rescale_factor=args.rescale_factor,
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show=not args.not_show,
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wait_time=args.show_interval,
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out_file=out_file)
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progress_bar.update()
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if __name__ == '__main__':
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main()
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