A Simple pytorch implementation of GradCAM[1], and GradCAM++[2]
Installation
pip install pytorch-gradcam
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.
Use your own model and layer:
model = MyModel()
target_layer = model.my_submodule
gradcam = GradCAM(model, target_layer)
References:
[1] Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization, Selvaraju et al, ICCV, 2017
[2] Grad-CAM++: Generalized Gradient-based Visual Explanations for Deep Convolutional Networks, Chattopadhyay et al, WACV, 2018
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Release files for pytorch-gradcam 0.2.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| pytorch-gradcam-0.2.1.tar.gz | 6.0 MB | Details |
Release files / pytorch-gradcam-0.2.1.tar.gz
| Download URL | pytorch-gradcam-0.2.1.tar.gz |
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