Megvii-BaseDetection / Megvii-BaseDetection/BEVDepth
BEV grid resolution
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- Python
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Description
Hello dear blogger, thank you very much for your great work. I modified the corresponding parameters in the bev_stereo_lss_r50_256x704_128x128_24e_2key.py file according to this #146 for get 256x256 bev grid resolution. Specifically include
`backbone_conf:
1,x_bound: [-51.2, 51.2, 0.8]-->:[-51.2, 51.2, 0.4];
2, y_bound: [-51.2, 51.2, 0.8]-->:[-51.2, 51.2, 0.4];
bbox_coder:
1, out_size_factor=4 --> 2,
2, voxel_size=[0.2, 0.2, 8] --> [0.1, 0.1, 8];
train_cfg:
1, out_size_factor=4 --> 2,
2, voxel_size=[0.2, 0.2, 8] --> [0.1, 0.1, 8];
test_cfg:
1, out_size_factor=4 --> 2,
2, voxel_size=[0.2, 0.2, 8] --> [0.1, 0.1, 8];',Other than that there are no changes.
But there is no result at all, that is, mAP=0. In addition to this, do you need to modify the parameters? Or is there still something in the test code that needs to be modified?
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with configs/bev_stereo_lss_r50_256x704_128x128_24e_2key.py and compare the changed backbone_conf, bbox_coder, train_cfg, and test_cfg values with issue #146. Then trace the test configuration and evaluation path to determine which settings affect the zero mAP result. Done means identifying the additional required changes or confirming the correct configuration for a 256x256 BEV grid.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100