Improving_Unsupervised_Defect_Segmentation
This is Keras code from "Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders".
https://arxiv.org/abs/1807.02011
I tried for my computer vision research.
That's is amazing method for unsupervised defect segmentation using AutoEncoder with SSIM.
Usage
0. Install Library
keras >= 2.0
tensorflow >= 1.6
scikit-learn
PIL
matplotlib
1. Use AutoEncoder
You can use your images with AutoEncoder.ipynb.
Please set your Image Path and automatically be resized on this code 128×128×1.
minimum 10 images required
2. Use SSIM
Next time, you can compare Inpue Image and Decoded Image.
If you use SSIM method, you have to pip install SSIM-PIL.