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Image creation through Generative Adversarial Network

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GAN

How to Run

  • Place the training dataset in the "train_set" folder and run the "train.py" file to train the model.
  • "gooddescriminator.h5" and "goodgenerator.h5" files are generated which contains the trained weights.
  • Run the "generate.py" to create new new samples.

Requirements

  • Python 3.6.x
  • Tensorflow
    • CUDA toolkit
    • CuDNN
  • Pillow
  • Keras
  • H5py

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