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# This script for Hugging Face's datasets library was written by Théo Gigant
import os
import datasets
from PIL import Image
_CITATION = """\
@inproceedings{CycleGAN2017,
title={Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks},
author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A},
booktitle={Computer Vision (ICCV), 2017 IEEE International Conference on},
year={2017}
}
"""
_DESCRIPTION = """\
Two unpaired sets of photos of respectively horses and zebras, designed for unpaired image-to-image translation, as seen in the paper introducing CycleGAN
"""
_HOMEPAGE = "https://people.eecs.berkeley.edu/~taesung_park/CycleGAN/datasets/"
_LICENSE = ""
_URL = "http://efrosgans.eecs.berkeley.edu/cyclegan/datasets/horse2zebra.zip"
class Horse2Zebra(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="horse", version=VERSION, description="Images of horses"),
datasets.BuilderConfig(name="zebra", version=VERSION, description="Images of zebras"),
]
def _info(self):
features = datasets.Features(
{
"image": datasets.Image()
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
urls = _URL
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"datapath": os.path.join(data_dir, "horse2zebra"),
"split":"train"
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"datapath": os.path.join(data_dir, "horse2zebra"),
"split":"test"
},
),
]
def _generate_examples(self, datapath, split):
if split=="train":
dir = "trainA" if self.config.name == "horse" else "trainB"
elif split=="test":
dir = "testA" if self.config.name == "horse" else "testB"
image_dir = os.path.join(datapath, dir)
for idx, image_file in enumerate(os.listdir(image_dir)):
image_id = image_file.split(".")[0]
with Image.open(os.path.join(image_dir, image_file)) as img :
yield idx, {
"image": img.convert("RGB"),
}
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