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This project focused on the Image Reconstruction using a Variational Autoencoder (VAE).

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Image-Generation-by-Variational-Autoencoder

This project focused on the Image Reconstruction using a Variational Autoencoder (VAE).

Dataset

All images in this project comes from Anime Face Dataset
Download the images from 👉 https://www.kaggle.com/splcher/animefacedataset

Execution & Overall Structure of system

  1. Image Preprocessing :

    • Resize Images to [32,32] pixels (Cubic interpolation)
    • Reshape 2D image to 1D array [1024 set of RGB] = [3072]
      image
    python3 Img_Preprocess.py
    
  2. Training a VAE network with Torch package
    image

    python3 VAE.py
    
  3. Reconstruct the trained model with random latent variable Z

    python3 Reconstruct_Img.py
    
    • Reconstruction Results
      image

    • Visualization fo VAE's Transitivity
      image

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This project focused on the Image Reconstruction using a Variational Autoencoder (VAE).

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