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chainer-grad-cam's Introduction

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. You can choose AlexNet, VGGNet or ResNet as the model to generate CAM images.

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

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