import argparse
import os
from pathlib import Path
import mmcv
from mmcv import Config
from mmdet.datasets.builder import build_dataset
def parse_args():
parser = argparse.ArgumentParser(description='Browse a dataset')
parser.add_argument('config', help='train config file path')
parser.add_argument(
'--skip-type',
type=str,
nargs='+',
default=['DefaultFormatBundle', 'Normalize', 'Collect'],
help='skip some useless pipeline')
parser.add_argument(
'--output-dir',
default=None,
type=str,
help='If there is no display interface, you can save it')
parser.add_argument('--not-show', default=False, action='store_true')
parser.add_argument(
'--show-interval',
type=int,
default=999,
help='the interval of show (ms)')
args = parser.parse_args()
return args
def retrieve_data_cfg(config_path, skip_type):
cfg = Config.fromfile(config_path)
train_data_cfg = cfg.data.train
train_data_cfg['pipeline'] = [
x for x in train_data_cfg.pipeline if x['type'] not in skip_type
]
return cfg
def main():
args = parse_args()
cfg = retrieve_data_cfg(args.config, args.skip_type)
dataset = build_dataset(cfg.data.train)
progress_bar = mmcv.ProgressBar(len(dataset))
for item in dataset:
filename = os.path.join(args.output_dir,
Path(item['filename']).name
) if args.output_dir is not None else None
mmcv.imshow_det_bboxes(
item['img'],
item['gt_bboxes'],
item['gt_labels'] - 1,
class_names=dataset.CLASSES,
show=not args.not_show,
out_file=filename,
wait_time=args.show_interval)
progress_bar.update()
if __name__ == '__main__':
main()
