Wenwei Zhang

Hi @Kay1794 , I do not quite understand your question. Do you meet bugs or something else? The config should work, and you need to check the Tensorboard to see...

Hi @Kay1794 , This is because the code does not pass the results to the pymotmetrics for evaluation. After the refactoring, the code use the KITTI's evaluation metric rather than...

1. This is weird, I need to check it further. 2. The codebase has been modified to directly use the point cloud data and reduce it in data pre-processing [here[(https://github.com/ZwwWayne/mmMOT/blob/master/point_cloud/preprocess.py#L64),...

I do not know about it, maybe you need to download the data again.

Ops, my data is from 0000 to 0146, I do not have 147. But I met no bug.

Hi @SamGhK , Thanks for your feedback, this is unusual because the metrics except the MOTA seems to be normal. Can you provide more details about your running environment? Especially...

Hi @SamGhK , I evaluated the model again and got the same normal results as before. I thought the problem is the version of pyproj, because I met the problem...

It is possible to do that. You need to set `point_len: 512` to `point_len: 0` to avoid using LiDAR modules. And then you need to set `score_fusion_arch: ~`, `test_mode: 0`...

Hi @SamGhK , The eval results of pp_pv_40e_mul_C should be as the following:  You can check it with your evaluation results.

`=> no checkpoint found at '.data/pretrain_models/pp_pv_40e_mul_C-gpu.pth` in the log means the model is not loaded successfully. You might need to check whether the path of the pre-trained model is correct.