| 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() |
|
|
