70 lines
1.9 KiB
Python
70 lines
1.9 KiB
Python
import argparse
|
|
|
|
import torch
|
|
from mmcv import Config
|
|
|
|
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')
|
|
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)
|
|
# import modules from string list.
|
|
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()
|