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Temporal Misalignment lack of results["cam_sweeps"] #11
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Thank you very much for addressing the question. To generate the info = {
'lidar_path': lidar_path,
'token': sample['token'],
'sweeps': [],
'sweeps_back': [],
'cams': dict(),
'cam_sweeps': [],
'lidar2ego_translation': cs_record['translation'],
'lidar2ego_rotation': cs_record['rotation'],
'ego2global_translation': pose_record['translation'],
'ego2global_rotation': pose_record['rotation'],
'timestamp': sample['timestamp'],
} cam_sweep = []
for cam in camera_types:
# print(cam)
camk = []
while len(camk) < max_sweeps:
cam_rec = nusc.get('sample_data', sample['data']['%s'%cam])
if not cam_rec['prev'] == '':
cam_re = nusc.get('sample_data', cam_rec['prev'])
camk.append(cam_re)
else:
break
cam_sweep.append(camk)
info['cam_sweeps'] = cam_sweep |
OK! I know what to do. thanks. |
The code you provided has a problem, you second, The paper describes it this way:
Your code replaces the current frame of both Lidar and Camera with the previous |
How is the results['cam_sweeps'] in nuscenes Dataset generated?
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