Gradcam plus plus pytorch
A Simple pytorch implementation of GradCAM and GradCAM++
please refer to `example.ipynb` for general usage and refer to documentations of each layer-finding functions in `utils.py` if you want to know how to set `target_layer_name` properly. The project is written primarily in Jupyter Notebook, first published in 2018. Key topics include: cnn-visualization, gradcam, gradcam-plus-plus, interpretable-deep-learning.
A Simple pytorch implementation of GradCAM[1], and GradCAM++[2]
<br> <p align="center"> <img src=assets/readme.png> </p>Supported torchvision models
- alexnet
- vgg
- resnet
- densenet
- squeezenet
Usage
please refer to example.ipynb for general usage and refer to documentations of each layer-finding functions in utils.py if you want to know how to set target_layer_name properly.
References:
[1] Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization, Selvaraju et al, ICCV, 2017 <br>
[2] Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep Convolutional Networks, Chattopadhyay et al, WACV, 2018
Contributors
Showing top 1 contributor by commit count.
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