Hi, I am using TensorRT python API. I was able to import a Caffe model of SSD network using the built-in TensorRT plugin layers and following user instructions. Unfortunately, when inferring the outputs are incorrect compared to the original Caffe implementation using the OpenCV DNN libraries: Prio…

Hi, Just to confirm that this issue is fixed with TensorRT 8.0.1 delivered in JetPack 4.6. Thank you for your support.

Wrong SSD inference results using TensorRT python API

Robotics & Edge Computing Jetson Systems Jetson Nano

AastaLLL April 22, 2021, 9:35am 7

Hi,

It seems that you load a prebuilt TensorRT engine in the python example.
Could you try to create the TensorRT engine from caffemodel parser?

Since we do have a issue related to PriorBox accuracy and the root cause is from the serializer.
This issue is fixed internally and you won’t meet it in our next JetPack release.

Thanks.

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Wrong SSD inference results using TensorRT python API

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