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
- Python 3.6
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md
├── datasets <- All datasets are stored here
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├── saved_models <- Checkpointed models and tensorboard summaries
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├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
└── src <- Source code for use in this project
├── __init__.py <- Makes src a Python module
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├── train.py <- Run this to train
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├── test.py <- Run this to test
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├── data <- Code for downloading or loading data
│ ├── data.py <- Dataset class
│ └── download_data.py
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├── models <- Code for defining the network structure and loss functions
│ ├── __init__.py
│ ├── network.py
│ ├── cyclegan.py <- CycleGAN model class
│ └── losses.py
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└── utils <- Utility files
├── options.py <- Class for command line options
└── image_history_buffer.py
Project based on the cookiecutter data science project template. #cookiecutterdatascience