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
- 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
-Convolutional Autoencoder
- python3 main_cnn.py
