Integrated Gradients
This is the pytorch implementation of "Axiomatic Attribution for Deep Networks". The original tensorflow version could be found here.
Acknowledgement
Requirements
- python-3.5.2
- pytorch-0.4.1
- opencv-python
TODO List
- add more functions as the original code.
- finetune the results, make them close to the original paper.
Instructions
Highly recommend to use GPU to accelerate the computation. If you use CPU, I will recommend to select some small networks, such as resnet18. You also need to put your images under examples/.
Lists of networks that support (of course, you can add any networks by yourself)
- inception
- resnet18
- resnet152
- vgg19
Run the code
python main.py --cuda --model-type='inception' --img='01.jpg'
Results
Results are slightly different from the original paper, it may have some bugs or need to do some adjustments. I will keep updating it, any contributions are welcome!
Inception-v3
ResNet-18
ResNet-152
VGG-19
