I have a tensorflow trained model and tested at tensorflow with accuracy achieved 95%.
Tensorflow model is converted to ONNX and converted to TensorRT.
TensorRT engine runs with 16-bit precision.
In TensorRT, accuracy drops to 75%.
Tested same images for both tests and same input size.
Where should I look at for this accuracy drop? The only difference is I do batch inference in TensorRT, but not in Tensorflow.
This link also has the same issue. But he said because of image reading.
For me, images are read using OpenCV for both Tensorflow and TensorRT.