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chainer-grad-cam

Chainer implementation of Grad-CAM [1]. Grad-CAM can localize and highlight important region in the image for predicting the concept without changing the model architecture. Currently, this implementation supports AlexNet, VGGNet and ResNet.

Summary

Grad-CAM Guided Backpropagation Guided Grad-CAM
Boxer (242)
Tiger Cat (282)

Requirements

  • Chainer
  • Cupy (for GPU support)
  • OpenCV

Usage

python run.py --input images/dog_cat.png --label 242 --layer conv5_3 --gpu 0
python run.py --input images/dog_cat.png --label 282 --layer conv5_3 --gpu 0

References

  • [1] Ramprasaath R. Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra, "Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization", https://arxiv.org/abs/1610.02391