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# Copyright (c) OpenMMLab. All rights reserved.
import logging
import os
from argparse import ArgumentParser
from mmengine.logging import print_log
from mmdet3d.apis import MultiModalityDet3DInferencer
def parse_args():
parser = ArgumentParser()
parser.add_argument('pcd', help='Point cloud file')
parser.add_argument('img', help='Image file')
parser.add_argument('infos', help='Infos file with annotations')
parser.add_argument('model', help='Config file')
parser.add_argument('weights', help='Checkpoint file')
parser.add_argument(
'--device', default='cuda:0', help='Device used for inference')
parser.add_argument(
'--cam-type',
type=str,
default='CAM_FRONT',
help='choose camera type to inference')
parser.add_argument(
'--pred-score-thr',
type=float,
default=0.3,
help='bbox score threshold')
parser.add_argument(
'--out-dir',
type=str,
default='outputs',
help='Output directory of prediction and visualization results.')
parser.add_argument(
'--show',
action='store_true',
help='Show online visualization results')
parser.add_argument(
'--wait-time',
type=float,
default=-1,
help='The interval of show (s). Demo will be blocked in showing'
'results, if wait_time is -1. Defaults to -1.')
parser.add_argument(
'--no-save-vis',
action='store_true',
help='Do not save detection visualization results')
parser.add_argument(
'--no-save-pred',
action='store_true',
help='Do not save detection prediction results')
parser.add_argument(
'--print-result',
action='store_true',
help='Whether to print the results.')
call_args = vars(parser.parse_args())
call_args['inputs'] = dict(
points=call_args.pop('pcd'),
img=call_args.pop('img'),
infos=call_args.pop('infos'))
call_args.pop('cam_type')
if call_args['no_save_vis'] and call_args['no_save_pred']:
call_args['out_dir'] = ''
init_kws = ['model', 'weights', 'device']
init_args = {}
for init_kw in init_kws:
init_args[init_kw] = call_args.pop(init_kw)
# NOTE: If your operating environment does not have a display device,
# (e.g. a remote server), you can save the predictions and visualize
# them in local devices.
if os.environ.get('DISPLAY') is None and call_args['show']:
print_log(
'Display device not found. `--show` is forced to False',
logger='current',
level=logging.WARNING)
call_args['show'] = False
return init_args, call_args
def main():
# TODO: Support inference of point cloud numpy file.
init_args, call_args = parse_args()
inferencer = MultiModalityDet3DInferencer(**init_args)
inferencer(**call_args)
if call_args['out_dir'] != '' and not (call_args['no_save_vis']
and call_args['no_save_pred']):
print_log(
f'results have been saved at {call_args["out_dir"]}',
logger='current')
if __name__ == '__main__':
main()
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