Hard coded calibration parameters & using a custom dataset

[jacoblambert]

Hi,
I've had some success using a custom dataset converted to KITTI format for training. Your repo is generally easy to use so thanks for that.

However I noticed that some of the hard-coded KITTI calibration matrices are being used in augmentation. The dataset loader seems to load calibration files properly(?), but some functions use the "average KITTI value" defined here https://github.com/maudzung/Complex-YOLOv4-Pytorch/blob/master/src/config/kitti_config.py . I could change those matrices but that wouldn't scale well, so I modified the code to make sure the proper calibration values were being passed to the augmentation function.

In the end, that had a small, negative impact on my results; do you have any idea why that is? Why were things even working with the hard coded KITTI params, when I'm using a dataset completely unlike KITTI? Can you explain how the hard-coded values were used and how it would impact a custom dataset?

I'm worried I somehow broke some augmentation code in the process; do you have any suggestions with debugging this repo? (making sure the boxes are TF'd properly, data augmentation is working properly, and so on..)?