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An implementation of a Convolutional VAE on the SVHN dataset.

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Convolutional Variational Autoencoder on the SVHN Dataset

Data Description

  • 10 classes, 73257 train images
  • 3 x 32 x 32 tensors.

Install

python3 -m venv venv
source venv/bin/activate
pip install requirements.txt

Train

python train.py --gen_images_dir images --num_epochs=100 --batch_size=64

Images will be samples and generated at the end of each epoch in the --gen_images-dir directory.

Sample Generated Images (103 epochs)

Images

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An implementation of a Convolutional VAE on the SVHN dataset.

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