| import argparse | |
| from mmcv import Config | |
| from mmcv.cnn import get_model_complexity_info | |
| from mmseg.models import build_segmentor | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description='Train a segmentor') | |
| parser.add_argument('config', help='train config file path') | |
| parser.add_argument( | |
| '--shape', | |
| type=int, | |
| nargs='+', | |
| default=[2048, 1024], | |
| help='input image size') | |
| args = parser.parse_args() | |
| return args | |
| def main(): | |
| args = parse_args() | |
| if len(args.shape) == 1: | |
| input_shape = (3, args.shape[0], args.shape[0]) | |
| elif len(args.shape) == 2: | |
| input_shape = (3, ) + tuple(args.shape) | |
| else: | |
| raise ValueError('invalid input shape') | |
| cfg = Config.fromfile(args.config) | |
| cfg.model.pretrained = None | |
| model = build_segmentor( | |
| cfg.model, | |
| train_cfg=cfg.get('train_cfg'), | |
| test_cfg=cfg.get('test_cfg')).cuda() | |
| model.eval() | |
| if hasattr(model, 'forward_dummy'): | |
| model.forward = model.forward_dummy | |
| else: | |
| raise NotImplementedError( | |
| 'FLOPs counter is currently not currently supported with {}'. | |
| format(model.__class__.__name__)) | |
| flops, params = get_model_complexity_info(model, input_shape) | |
| split_line = '=' * 30 | |
| print('{0}\nInput shape: {1}\nFlops: {2}\nParams: {3}\n{0}'.format( | |
| split_line, input_shape, flops, params)) | |
| print('!!!Please be cautious if you use the results in papers. ' | |
| 'You may need to check if all ops are supported and verify that the ' | |
| 'flops computation is correct.') | |
| if __name__ == '__main__': | |
| main() | |