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# Copyright (c) OpenMMLab. All rights reserved.
from argparse import ArgumentParser
from mmaction.apis.inferencers import MMAction2Inferencer
def parse_args():
parser = ArgumentParser()
parser.add_argument(
'inputs', type=str, help='Input video file or rawframes folder path.')
parser.add_argument(
'--vid-out-dir',
type=str,
default='',
help='Output directory of videos.')
parser.add_argument(
'--rec',
type=str,
default=None,
help='Pretrained action recognition algorithm. It\'s the path to the '
'config file or the model name defined in metafile.')
parser.add_argument(
'--rec-weights',
type=str,
default=None,
help='Path to the custom checkpoint file of the selected recog model. '
'If it is not specified and "rec" is a model name of metafile, the '
'weights will be loaded from metafile.')
parser.add_argument(
'--label-file', type=str, default=None, help='label file for dataset.')
parser.add_argument(
'--device',
type=str,
default=None,
help='Device used for inference. '
'If not specified, the available device will be automatically used.')
parser.add_argument(
'--batch-size', type=int, default=1, help='Inference batch size.')
parser.add_argument(
'--show',
action='store_true',
help='Display the video in a popup window.')
parser.add_argument(
'--print-result',
action='store_true',
help='Whether to print the results.')
parser.add_argument(
'--pred-out-file',
type=str,
default='',
help='File to save the inference results.')
call_args = vars(parser.parse_args())
init_kws = ['rec', 'rec_weights', 'device', 'label_file']
init_args = {}
for init_kw in init_kws:
init_args[init_kw] = call_args.pop(init_kw)
return init_args, call_args
def main():
init_args, call_args = parse_args()
mmaction2 = MMAction2Inferencer(**init_args)
mmaction2(**call_args)
if __name__ == '__main__':
main()
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