Instructions to use keras-io/CycleGAN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/CycleGAN with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/CycleGAN") - Notebooks
- Google Colab
- Kaggle
Keras Implementation of CycleGAN model using Horse to Zebra dataset π΄ -> π¦
This repo contains the model and the notebook to this Keras example on CycleGAN.
Full credits to: Aakash Kumar Nain
Background Information
CycleGAN is a model that aims to solve the image-to-image translation problem. The goal of the image-to-image translation problem is to learn the mapping between an input image and an output image using a training set of aligned image pairs. However, obtaining paired examples isn't always feasible. CycleGAN tries to learn this mapping without requiring paired input-output images, using cycle-consistent adversarial networks.

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