I attended the webinar and downloaded the TensorRT package. It works on my TX2. I wanted to compare the TensorRT classification scores with those of the Tensorflow model.
I am working with inception_v3 model which was provided and used by the convert_plan.py.
The results of classifying the image data/images/lifeboat.jpg
with Tensorflow are:
0 9.46784 626 lifeboat
1 5.38329 815 speedboat
2 5.22412 555 fireboat
3 5.22268 511 container ship, containership, container vessel
4 3.76027 409 amphibian, amphibious vehicle
with the TensorRT are:
0 10.371737 626 lifeboat
1 3.901006 415 backpack, back pack, knapsack, packsack, rucksack, haversack
2 2.526643 815 speedboat
3 2.167920 736 poncho
4 2.089388 601 hook, claw
This seems like more than just a rounding error.
If the Tensorflow results were not as good as the TensorRT results I would be looking at the scripts I used to run Tensorflow, but since they appear better I felt impelled to ask.
I reformatted the outputs from classify_image.cu and included the scores to enable easy comparison with the Python script used to run Tensorflow.
Any thoughts. Any one.