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Custom model #56

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Kickjaw opened this issue May 19, 2022 · 1 comment
Open

Custom model #56

Kickjaw opened this issue May 19, 2022 · 1 comment

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@Kickjaw
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Kickjaw commented May 19, 2022

Hello,

I have a custom trained model that started with the yolov5m.yaml configuration. I am lost as to what changes i would need to make to the implementation of the yolomodel. I can provide what ever files anyone needs to help with this.

Thanks

@sstainba
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Once your model is in ONNX format, you can use Netron to inspect it and see the input/output. You use this info to set the values in your inherited model class.

For example, my model has an input that is a float32[1, 3, 640, 640].
That corresponds to the batch size, color depth (I think), height, width

My output is float32[1, 25200, 6]. For this, I am no sure what the '1' is for... but it seems the only number that matters is the last one (6) which is my value for "Dimensions" on the model. I left everything else as the base model and it worked for me.

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