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TAO deploy docker eval accuracy lower vs TAO tf1 docker

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I used PeopleNet, and retrained it using the sample notebook and the reworked detectnet sample spec file. I was able to achieve around 82% percent mAP, but get around 60% using the pre/post processing from the tao deploy backend. I had changed these scripts to run inference on the .onnx exported model, and achieved these numbers with the .onnx model. Let me know what additional info I should provide, thank you.

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