I am using a custom dataset to train BEVFusion. Exactly as you mentioned previously, I implemented a custom data preprocessor class that essentially generates custom_infos.pkl in NuScenes annotation style. I'm able to train and test with that.
However, I won't be able to create a NuScenes object as it is not compatible. But I do want to render or visualize results (both BEV on lidar as well as 3D Boxes on camera frames). My results are currently super wonky and I wanted to better understand the following:
1) BEVFusion camera only model for object detection - what is the coordinate frame of the predictions and what is that of the ground truth ?
2) Outputs are size, translation and rotation but with reference to what? Is that represented in Birds eye View? Is there a script to visualize not in BEV but in perspective view of each camera ?
Adding support for a custom dataset is beyond the scope of this codebase, and unfortunately, we don't have the capacity to accommodate such customized requests.
Hello @kentang-mit,
I am using a custom dataset to train BEVFusion. Exactly as you mentioned previously, I implemented a custom data preprocessor class that essentially generates custom_infos.pkl in NuScenes annotation style. I'm able to train and test with that.
However, I won't be able to create a NuScenes object as it is not compatible. But I do want to render or visualize results (both BEV on lidar as well as 3D Boxes on camera frames). My results are currently super wonky and I wanted to better understand the following:
1) BEVFusion camera only model for object detection - what is the coordinate frame of the predictions and what is that of the ground truth ?
2) Outputs are size, translation and rotation but with reference to what? Is that represented in Birds eye View? Is there a script to visualize not in BEV but in perspective view of each camera ?