Pytorch implementation of different saliency methods.
- Pytorch 4.0
git clone https://github.com/Ema93sh/pytorch-saliency
cd pytorch-saliency
python setup.py install
For more detailed example checkout main.py
from torchvision import models
from saliency import SaliencyMethod, MapType, generate_saliency
# Load your image
input_image = ...
# Load your model
model = models.vgg16(pretrained=True)
# Choose your saliency method
saliency_method = SaliencyMethod.GUIDED
# Choose your targets for saliency
targets = [2]
saliency_maps = generate_saliency(model, input_image, targets, saliency_method)
# Select the type that you want to display
saliency = saliency_maps[MapType.POSITIVE]
- Vanilla backprop
- Guided backprop
- DeConv
- Positive (MapType.POSITIVE)
- Negative (MapType.NEGATIVE)
- Absolute (MapType.ABSOLUTE)
- Original (MapType.ORIGINAL)
To test your saliency method run main.py. It will pick a random image from images folder and display the saliency.
python main.py --type guided
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