I am about to start training with DeepLabCut on a dataset of cattle passing through a race, the goal is to identify key points on the cattle which will be used in conjunction with depth cameras to calculate biometric measurments.
I have a question regarding the training process, because my dataset involves cattle passing through a race, the animal is partially occluded by this static race. See this image as an example:
Because this is a static environment, i.e the cameras, race will never move, i had an idea to use a image mask to remove some of the race and external environment from the image leaving just the animal inside the race, see the following as an example:
Would this typically yield better results using DeepLabCut, or should i simply train on the full images?
Any advice is much appreciated.