I am trying to train custom object classifier in Darknet YOLO v2 https://pjreddie.com/darknet/yolo/
I gathered a dataset for images most of them are 6000 x 4000 px and s
By default the darknet api changes the size of the images in both inference and training, but in theory any input size w, h = 32 x X where X belongs to a natural number should, W is the width, H the height. By default X = 13, so the input size is w, h = (416, 416). I use this rule with yolov3 in opencv, and it works better the bigger X is.