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--- |
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license: cc |
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task_categories: |
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- image-to-image |
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task_ids: [] |
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pretty_name: Horse2Zebra |
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tags: |
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- GAN |
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- unpaired-image-to-image-translation |
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--- |
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## Dataset Description |
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- **Homepage:** https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/ |
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- **Paper:** https://arxiv.org/abs/1703.10593 |
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### Dataset Summary |
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This dataset was obtained from the original CycleGAN Datasets directory available on [Berkeley's website](https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/). |
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For more details about the dataset you can refer to the [original CycleGAN publication](https://arxiv.org/abs/1703.10593). |
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### How to use |
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You can easily load the dataset with the following lines : |
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```python |
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from datasets import load_dataset |
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data_horses = load_dataset("gigant/horse2zebra", name="horse", split="train") |
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data_zebras = load_dataset("gigant/horse2zebra", name="zebra", split="train") |
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``` |
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Two splits are available, `"train"` and `"test"` |
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### Citation Information |
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``` |
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@inproceedings{CycleGAN2017, |
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title={Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks}, |
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author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A}, |
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booktitle={Computer Vision (ICCV), 2017 IEEE International Conference on}, |
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year={2017} |
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} |
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``` |
