security_vision/Towards-Realtime-MOT
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update pretrained model

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Zhongdao 2019-10-02 22:47:39 +08:00
parent 357a747491
commit 2bf6876c0f
2 changed files with 15 additions and 13 deletions
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2
README.md
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@ -28,7 +28,7 @@ Will be released later.
## Pretrained model and baseline models
Darknet-53 ImageNet pretrained: [[DarkNet Official]](https://pjreddie.com/media/files/darknet53.conv.74)
JDE uncertainty-weighted: [[Google Drive]]()(Coming soon) [[Baidu NetDisk]](https://pan.baidu.com/s/1Ifgn0Y_JZE65_qSrQM2l-Q)
JDE-1088x608-uncertainty: [[Google Drive]]()(Coming soon) [[Baidu NetDisk]](https://pan.baidu.com/s/1Ifgn0Y_JZE65_qSrQM2l-Q)
## Test on MOT-16 Challenge
## Training

24
track.py
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@ -74,7 +74,7 @@ def eval_seq(opt, dataloader, data_type, result_filename, save_dir=None, show_im
frame_id += 1
# save results
write_results(result_filename, results, data_type)
return frame_id
return frame_id, timer.average_time, timer.calls
def main(opt, data_root='/data/MOT16/train', det_root=None, seqs=('MOT16-05',), exp_name='demo',
@ -85,10 +85,9 @@ def main(opt, data_root='/data/MOT16/train', det_root=None, seqs=('MOT16-05',),
data_type = 'mot'
# run tracking
timer = Timer()
accs = []
n_frame = 0
timer.tic()
timer_avgs, timer_calls = [], []
for seq in seqs:
output_dir = os.path.join(data_root, '..','outputs', exp_name, seq) if save_images or save_videos else None
@ -97,8 +96,11 @@ def main(opt, data_root='/data/MOT16/train', det_root=None, seqs=('MOT16-05',),
result_filename = os.path.join(result_root, '{}.txt'.format(seq))
meta_info = open(os.path.join(data_root, seq, 'seqinfo.ini')).read()
frame_rate = int(meta_info[meta_info.find('frameRate')+10:meta_info.find('\nseqLength')])
n_frame += eval_seq(opt, dataloader, data_type, result_filename,
nf, ta, tc = eval_seq(opt, dataloader, data_type, result_filename,
save_dir=output_dir, show_image=show_image, frame_rate=frame_rate)
n_frame += nf
timer_avgs.append(ta)
timer_calls.append(tc)
# eval
logger.info('Evaluate seq: {}'.format(seq))
@ -108,11 +110,13 @@ def main(opt, data_root='/data/MOT16/train', det_root=None, seqs=('MOT16-05',),
output_video_path = osp.join(output_dir, '{}.mp4'.format(seq))
cmd_str = 'ffmpeg -f image2 -i {}/%05d.jpg -c:v copy {}'.format(output_dir, output_video_path)
os.system(cmd_str)
timer.toc()
logger.info('Time elapsed: {}, FPS {}'.format(timer.average_time, n_frame / timer.average_time))
timer_avgs = np.asarray(timer_avgs)
timer_calls = np.asarray(timer_calls)
all_time = np.dot(timer_avgs, timer_calls)
avg_time = all_time / np.sum(timer_calls)
logger.info('Time elapsed: {:.2f} seconds, FPS: {:.2f}'.format(all_time, 1.0 / avg_time))
# get summary
# metrics = ['mota', 'num_switches', 'idp', 'idr', 'idf1', 'precision', 'recall']
metrics = mm.metrics.motchallenge_metrics
mh = mm.metrics.create()
summary = Evaluator.get_summary(accs, seqs, metrics)
@ -143,10 +147,6 @@ if __name__ == '__main__':
print(opt, end='\n\n')
if not opt.test_mot16:
seqs_str = '''CVPR19-01
CVPR19-02
CVPR19-03
CVPR19-05'''
seqs_str = '''KITTI-13
KITTI-17
ADL-Rundle-6
@ -162,6 +162,8 @@ if __name__ == '__main__':
MOT16-08
MOT16-12
MOT16-14'''
seqs_str = '''MOT16-01
MOT16-07'''
data_root = '/home/wangzd/datasets/MOT/MOT16/test'
seqs = [seq.strip() for seq in seqs_str.split()]