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Implement a simple GAN with Python and use it to generate Chinese character digitsDescription: I choose this project to get familiar with GAN. After training a self-collected Chinese characters numbers from 0 to 9, we expect to get a batch of fake numbers in the same style. I use deep convolutional GAN and self-collected training dataset. Dataset: Numbers in Chinese character : 0 to 9 1) In the beginning, I used two sets of hand-writing numbers, which seems too hard to get a better result because of thin strokes 2) Then I chose to use thick strokes numbers Use the augmentation.py to expand the training dataset to 10,000 pictures. Download train.zip Deep Convolutional GAN: Discriminator - With three convolutional layers and one fully-connected layer. Generator - With three convolutional layers and one fully-connected layer. Use Adam optimizer and fixed learning rate 0.0002 and momentum term of 0.8. Use batch normalization in both discriminator and generator and leaky ReLU. Download dcgan.py Output: Here is the result after training 20000 epochs. Conclusion: A high-quality training dataset is critical for GAN. |