Comments (5)
Train from scratch shouldn't result terrible, there may be some bugs in my code.
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What's your result when train from scratch? The performance of pretrained model should be very easy to achieve.
I have trained 80k step and get 84/74/67 3D AP, there seems no serious bug in my code.
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I used the default car.config in the repo. Should I modify files in SparseConvNet as you mentioned in README, even if I did not use the pretrained model?
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I use a different version of SparseConvNet and Pytorch and it seems all right.
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Can we used pretrained model for poinpillar algoritm?
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Related Issues (20)
- KeyError: 'annotations' when using nuscenes dataset
- KeyError: 'annotations' when using nuscenes dataset HOT 3
- How to start training from interrupted step HOT 1
- About gt_sampling
- ModuleNotFoundError: No module named 'second' HOT 1
- Kitti web viewer backend issue HOT 1
- second.pytorch 1.6.0 Alpha and spconv 2.1 HOT 2
- Convert custom Lidar point cloud data to KITTI format HOT 1
- Summary name eval.kitti/official/Car/[email protected]/1 is illegal; using eval.kitti/official/Car/3d_0.70/1 instead.
- Issues while using Kitti viewer. HOT 1
- Need tips on improving performance on custom dataset
- Need suggestions on how to generate onnx files using this repo
- Source of torchplus package
- OSS License compatibility question
- About kitti viewer
- second.data HOT 2
- I would like to know how many samples should be used for validation if 3517 samples are used for training?
- Is the sparse library writed by the autuor?
- Input only the desired scene
- 有人试过把这个代码在windows上运行吗
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