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pythonpytorchobject-detectionyolo

[FIXED, Roboflow exported CoCo Dataset mistake]YoloV5 cropping image into tiles with overlap (image + bbox)


I have images that are 4928x3280 and I'd like to crop them into tiles of 640x640 with a certain percentage of overlap. The issue is that I have no idea how to deal with the bounding boxes of these files in my dataset as I've found this paper,(http://openaccess.thecvf.com/content_CVPRW_2019/papers/UAVision/Unel_The_Power_of_Tiling_for_Small_Object_Detection_CVPRW_2019_paper.pdf), but not code or so referring to how they did this. There are some examples on the internet that actually have the yoloV5 tiling but without overlap like this(https://github.com/slanj/yolo-tiling) one.

Does anyone know how I could make this myself or if someone has an example of this for me?


Solution

  • If you want a ready to go library to make possible tiling and inference for yolov5, there is SAHI:

    <https://github.com/obss/sahi

    You can use it to create tiles with related annotations, to make inferences and evaluate model performance.