How to get anchors for custom datasets?

[Fred199683]

❔Question

My datasets is completely about small objects, but the default number of anchors is 9, and the number of layers is 3. So for small objects datasets, what should i do, can anyone give me some advices? I think i may try 6 anchors and 2 layers(each layer have 3 anchors), or even 3 anchors and one layer?? My datasets is totally about small objects, I think the default anchors which size is too big for my datasets....But i am very confused about how to choose the number K in kmeans and also the number of layers(something about receptive field??) Hope anyone can give me some advice!!THX!!!! plus: anchor_t: 4.0 # anchor-multiple threshold should i change this hyper-param???

Additional context

[glenn-jocher]

@Fred199683 before you modify anything I would first train with the default settings to establish a performance baseline that you can compare to.

YOLOv5 use autoanchor. autoanchor verifies your anchors against your dataset and training settings and adjusts them as necessary if it sees a bad fit. It works well in most cases, though if it causes problems you can always disable it with

python train.py --noautoanchor

[Fred199683]

@glenn-jocher

Thanks for ur reply. I've already train for first time with default setting. It works well. And because my datasets is totally about small objects, there is no objects bigger than 60 pixels. So i am wondering if i should try to modified the anchors to fit my dataset? And in ur autoanchor, i think only 3 anchors fit for my datasets, so the bpr is 100%, but i think the large anchors is useless? Am i clear.....I just want try to get better results...should i modified this?

[glenn-jocher]

@Fred199683 ok, then sure, you can remove output layers by not passing them to the Detect() layer in your model.yaml file: https://github.com/ultralytics/yolov5/blob/25f8ab835ef82a5664f6434934c7f40088117f65/models/yolov5s.yaml#L47

And you can remove or adjust anchors also in your model.yaml file: https://github.com/ultralytics/yolov5/blob/25f8ab835ef82a5664f6434934c7f40088117f65/models/yolov5s.yaml#L6-L11

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