infer_tensorrt_imagenet.py: Not Predicting The Correct Classes

[Hassan313]

Hi @rmccorm4 ,

I am using the infer_tensorrt_imagenet.py file to infer the images of imagenet with the int8 engine created by TensorRT.

Here is the way that I am using the code:

python3 infer_tensorrt_imagenet.py --engine resnet18.int8.engine
-d /home/hassan/Datasets/ImageNet/ -b 1 -n 5

Here are the results:

[TensorRT] WARNING: Current optimization profile is: 0. Please ensure there are no enqueued operations pending in this context prior to switching profiles
[TensorRT] WARNING: Explicit batch network detected and batch size specified, use execute without batch size instead.
Allocating buffers ...
Input image: /home/hassan/Datasets/ImageNet/ILSVRC2012_val_00000025.JPEG
Prediction: wall clock Probability: 0.09
Prediction: matchstick Probability: 0.06
Prediction: switch Probability: 0.03
Prediction: screw Probability: 0.03
Prediction: envelope Probability: 0.02

[TensorRT] WARNING: Current optimization profile is: 0. Please ensure there are no enqueued operations pending in this context prior to switching profiles
[TensorRT] WARNING: Explicit batch network detected and batch size specified, use execute without batch size instead.
Allocating buffers ...
Input image: /home/hassan/Datasets/ImageNet/ILSVRC2012_val_00000073.JPEG
Prediction: wall clock Probability: 0.06
Prediction: matchstick Probability: 0.06
Prediction: switch Probability: 0.04
Prediction: screw Probability: 0.03
Prediction: envelope Probability: 0.02

[TensorRT] WARNING: Current optimization profile is: 0. Please ensure there are no enqueued operations pending in this context prior to switching profiles
[TensorRT] WARNING: Explicit batch network detected and batch size specified, use execute without batch size instead.
Allocating buffers ...
Input image: /home/hassan/Datasets/ImageNet/ILSVRC2012_val_00000117.JPEG
Prediction: wing Probability: 0.07
Prediction: spotlight Probability: 0.02
Prediction: lampshade Probability: 0.02
Prediction: matchstick Probability: 0.02
Prediction: wall clock Probability: 0.02

[TensorRT] WARNING: Current optimization profile is: 0. Please ensure there are no enqueued operations pending in this context prior to switching profiles
[TensorRT] WARNING: Explicit batch network detected and batch size specified, use execute without batch size instead.
Allocating buffers ...
Input image: /home/hassan/Datasets/ImageNet/ILSVRC2012_val_00000113.JPEG
Prediction: wall clock Probability: 0.06
Prediction: envelope Probability: 0.06
Prediction: matchstick Probability: 0.04
Prediction: lampshade Probability: 0.03
Prediction: refrigerator Probability: 0.03

There are certain classes popping up (like wall clock). Can you kindly help?

Thank you.

[rmccorm4]

Hi @Hassan313 ,

Sorry for the delay.

Few questions come to mind:

1. Are the inference results correct on fp32/fp16 engines? If yes, then probably an int8 calibration issue. If not, then probably an issue with the model/conversion.

2. Was your int8 calibration data similar/representative of the data you're testing with inference?

3. Are the images already pre-processed?

4. Does using a different pre-processing function give better results?