A Tensorflow implementation of Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks using Eager Execution, tf.keras.layers, and tf.data.
Requirements:
- Tensorflow 1.11
Thanks to the original authors PyTorch implementation for inspiration: https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix
βββ README.md
βββ requirements.txt <- Use `pip install -r requirements.txt`
βββ setup.py <- makes project pip installable (pip install -e .) so src can be imported
βββ LICENSE
βββ src <- Source code for use in this project
Β Β βββ __init__.py <- Makes src a Python module
β
βββ train.py <- Run this to train
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βββ test.py <- Run this to test
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Β Β βββ data <- Code for downloading or loading data
Β Β βΒ Β βββ data.py <- Dataset class
Β Β βΒ Β βββ download_data.py
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Β Β βββ models <- Code for defining the network structure and loss functions
βΒ Β βββ cyclegan.py <- CycleGAN model class
βΒ Β βββ networks.py
Β Β βΒ Β βββ losses.py
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Β Β βββ utils <- Utility files
Β Β βββ options.py <- Class for command line options
Β Β Β Β βββ image_history_buffer.py
Project organisation based on the cookiecutter data science project template. #cookiecutterdatascience