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Generative models

Autoencoder

How I learned Generative models

1:Basic autoencoder using MNIST dataset

  • Autoencoder.py: Baisc file for training autoencoder and saving checkpoints
  • Check points will be saved in Model folder
  • Results will be saved in Results folder
  • orignal image

Orignal image

  • Reconstructed image

Reconstructed image

2:Anti-Rotate Autoencoder Autoencoder uses fashion MNIST dataset where input is a randomly rotated image and output is upright image. Few autoencoder arhitectures are explored in doing the same task.

-Single layer Autoencoder

  • Inoder to run single layer Autoencoder uncomment line 8(import autoenocder class) and line 32(getEncodedImage)
  • Comment(line 9)
  • python3 main.py

-Multilayer autoencoder

  • python3 main.py Anti-Rotate-Autoencoder image

-Convolutional Autoencoder

  • python3 main_cnn.py Anti-Rotate-Autoencoder image

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How I learned Autoenocders models

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