| | import argparse |
| |
|
| | import torch |
| | from mmcv import Config, DictAction |
| |
|
| | from mmdet.models import build_detector |
| |
|
| | try: |
| | from mmcv.cnn import get_model_complexity_info |
| | except ImportError: |
| | raise ImportError('Please upgrade mmcv to >0.6.2') |
| |
|
| |
|
| | def parse_args(): |
| | parser = argparse.ArgumentParser(description='Train a detector') |
| | parser.add_argument('config', help='train config file path') |
| | parser.add_argument( |
| | '--shape', |
| | type=int, |
| | nargs='+', |
| | default=[1280, 800], |
| | help='input image size') |
| | parser.add_argument( |
| | '--cfg-options', |
| | nargs='+', |
| | action=DictAction, |
| | help='override some settings in the used config, the key-value pair ' |
| | 'in xxx=yyy format will be merged into config file. If the value to ' |
| | 'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' |
| | 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' |
| | 'Note that the quotation marks are necessary and that no white space ' |
| | 'is allowed.') |
| | 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) |
| | if args.cfg_options is not None: |
| | cfg.merge_from_dict(args.cfg_options) |
| | |
| | if cfg.get('custom_imports', None): |
| | from mmcv.utils import import_modules_from_strings |
| | import_modules_from_strings(**cfg['custom_imports']) |
| |
|
| | model = build_detector( |
| | cfg.model, |
| | train_cfg=cfg.get('train_cfg'), |
| | test_cfg=cfg.get('test_cfg')) |
| | if torch.cuda.is_available(): |
| | model.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(f'{split_line}\nInput shape: {input_shape}\n' |
| | f'Flops: {flops}\nParams: {params}\n{split_line}') |
| | 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() |
| |
|
