Description
My program contains two modules, one is object detection which is implemented by TensorRT and YOLOV5. I use the following github GitHub - wang-xinyu/tensorrtx: Implementation of popular deep learning networks with TensorRT network definition API. Aother is OCR recognition which is implemented by TensorflowLite. I found a serious problem that using costomized plug-in of TensorRT by REGISTER_TENSORRT_PLUGIN to register the plug-in would affect the TensorflowLite model accuracy by 20%. And the TensorflowLite is just using CPU to compute and no customized operator. I just comment the code REGISTER_TENSORRT_PLUGIN, then the accuracy of the TensorflowLite model will up to 98%(this is the right accuracy when ocr module Individual test), otherwise is 77%.
This problem has confused me for a long time, could you give me some advice?
Environment
TensorRT Version: 7.2.1
GPU Type: GTX1070
CUDA Version: 10.2
CUDNN Version: 8.0.4
Operating System + Version: Ubuntu 18.04
Program Language: C++
TensorFlowLite Version: 2.2.0