Comments (4)
weiyangdaren
commented on July 19, 2024
2
我遇到了和你类似的问题。我使用的是pytorch0.4.1和作者提供的模型finetune_300.tar。
然后我改成pytorch0.4.0，但是发生了错误“num_batches_tracked”。于是我将psmnet/sunmission.py里的
model.load_state_dict(state_dict['state_dict'])
改成
model.load_state_dict({k.replace('.num_batches_tracked', ''):v for k,v in state_dict['state_dict'].items()})
它成功了
希望能帮到你
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Zong-Ming-Jing
commented on July 19, 2024
Do you fix the problem ? I have the same problem too !
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mileyan
commented on July 19, 2024
Hi @pengweiweiwei @Zong-Ming-Jing
Could you please send a point cloud sample (the .bin file) to [email protected]? I can help you address this question.
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vkorotkine
commented on July 19, 2024
I actually had a similar issue. The approach ends up working perfectly fine, but the point cloud results are different. LIDAR (red), Your provided pseudo-lidar point cloud (green), and the one computed from a disparity map generated by psmnet (blue). This is the top view for image 000003 from the object training dataset.
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Related Issues (20)
- Evaluation with pre-trained frustum pointnet HOT 1
- AVOD pre-trained weights for mono pseudo-lidar HOT 1
- have trouble in Train the stereo model
- pseudo lidar HOT 1
- pseudo lidar gives wrong converted point cloud HOT 1
- Can not install pytorch with Python 2.7 HOT 2
- Training for my own custom data HOT 3
- If you need PSMNet but only want to go with python 3, check this repo then HOT 1
- question about dataloader
- About the calibration problem between the true location and the Pseudo-LiDAR HOT 1
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- Why does the nan value appear in loss when training the stereo model?
- Confusion about paper table 5
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- Visualising Pseudo and Real LiDAR HOT 1
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