How to get a good result

Parametres

There are several parameters you need to modify when you are about to train. However, usually these parameters won't change too much as long as you are using the same camera and the same dataset making tool.

Camera Intrinsics

The dataset making tool which we are using can output the intrinsics. Strictly speaking, it is important for you to change the intrinsics everytime you start to train a new dataset. However since you are using exactly the same camera, the intrinsics won't vary too much to affect the result.

Diametre

Diametre is the maximum distance among the corners of the 3D bounding box. Obviously this parametre changes a lot between different objects. While you are using the dataset making tool, you should have noticed that the tool provides a way to generate the diametre of the current object. However, the valid.py itself can calculate the diametre, so commonly there's no need to modify this parameter manually.

batch_size

Batch is a common parametre in CNN. As we all know (if you don't, try to train on your own laptop and you will find out🙃), batch_size is limited by the memory of your GPU. Try to cut down on the batch_size when facing error CUDA out of memory or something else. Meanwhile, it is said that the bigger the batch_size is, the better the result will be. So make sure that you have a appropriate batch_size. Notice: we are using 8 on Aliyun servers.

anchor

See also. I have never changed this one yet.