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VisualBackprop

This is the Pytorch version of the VisualBack prop algorithm on the VGG16 model. Theoretical description of the algorithm can be found found here: https://arxiv.org/abs/1611.05418.

Getting Started

These instructions will get you a copy of the project up and running on your local machine.

Prerequisites

Pytorch 1.0
tqdm {for pretty progress bars}

Run

The input data should be arranged in standard pytorch data loading format i.e

root/dog/xxx.png
root/dog/xxy.png
root/dog/xxz.png

root/cat/123.png
root/cat/nsdf3.png
root/cat/asd932_.png
python main.py --cp='trained model' --bs='Batch Size' --ms='Manual Seed' --dir='Data Directory'

Results

The results are saved in the results directory. Here are sample results for VGG16 model pretrained on ImageNet.

n02169497_1092_img n02169497_1092_outputseg n02169497_1092_over n02169497_1122_img n02169497_1122_outputseg n02169497_1122_over n02169497_1307_img n02169497_1307_outputseg n02169497_1307_over n02169497_1309_img n02169497_1309_outputseg n02169497_1309_over

Acknowledgments

We thank Dr. Marius Bojarski @mbojarski NVIDIA Corporation for useful feedbacks.

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This is the Pytorch version of the VisualBack prop algorithm on the VGG16 model. Theoretical description of the algorithm can be found found here: https://arxiv.org/abs/1611.05418.

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