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README.md

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+---
+annotations_creators: []
+language: []
+language_creators: []
+license:
+- cc0-1.0
+multilinguality: []
+pretty_name: Anime Segmentation
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+tags: []
+task_categories:
+- image-segmentation
+task_ids:
+- semantic-segmentation
+---
+
+## Dataset Description
+
+A segmentation dataset for anime character
+
+My project: [anime-segmentation](https://github.com/SkyTNT/anime-segmentation)
+
+### Dataset Summary
+
+| Dir  | Description                               | Format | Images |
+| ---- | ----                                      | ----   | ----   |
+| bg   | background images                         | jpg    | 8057   |
+| fg   | foreground images, transparent background | png    | 11802  |
+| imgs | real images with background and foreground| jpg    | 1111   |
+| masks| labels for imgs                           | jpg    | 1111   |
+
+Total size: 18GB
+
+### Collection Method
+
+Collect background from [character_bg_seg_data](https://github.com/ShuhongChen/bizarre-pose-estimator#download)
+
+Collect foreground from danbooru website.
+
+Collect imgs and masks from [AniSeg](https://github.com/jerryli27/AniSeg#about-the-models) and danbooru website.
+
+I use [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN) to restore the background images.
+
+I clean the dataset using [DeepDanbooru](https://github.com/KichangKim/DeepDanbooru) first then manually, to make sue all foreground is anime character.
+
+### Contributions
+
+Thanks to [@SkyTNT](https://github.com/SkyTNT) for adding this dataset.
+
+Thanks to [@ShuhongChen](https://github.com/ShuhongChen) for [character_bg_seg_data](https://github.com/ShuhongChen/bizarre-pose-estimator#download)
+
+Thanks to [@jerryli27](https://github.com/jerryli27) for [AniSeg](https://github.com/jerryli27/AniSeg#about-the-models)

anime-segmentation.py

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+import os
+import datasets
+from datasets import DownloadManager, DatasetInfo
+
+_DESCRIPTION = """\
+A segmentation dataset for anime character
+"""
+_HOMEPAGE = "https://huggingface.co/datasets/skytnt/anime-segmentation"
+_URL_BASE = "https://huggingface.co/datasets/skytnt/anime-segmentation/resolve/main/data/"
+_EXTENSION = [".png", ".jpg"]
+
+
+class AnimeSegmentationConfig(datasets.BuilderConfig):
+
+    def __init__(self, features, data_files, **kwargs):
+        super(AnimeSegmentationConfig, self).__init__(**kwargs)
+        self.features = features
+        self.data_files = data_files
+
+
+class AnimeSegmentation(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        AnimeSegmentationConfig(
+            name="bg",
+            description="background",
+            features=["image"],
+            data_files=["bg-00.zip", "bg-01.zip", "bg-02.zip", "bg-03.zip", "bg-04.zip"]
+        ),
+        AnimeSegmentationConfig(
+            name="fg",
+            description="foreground",
+            features=["image"],
+            data_files=["fg-00.zip", "fg-01.zip", "fg-02.zip", "fg-03.zip", "fg-04.zip", "fg-05.zip"]
+        ),
+        AnimeSegmentationConfig(
+            name="imgs-masks",
+            description="real images and masks",
+            features=["image", "mask"],
+            data_files=["imgs-masks.zip"]
+        )
+    ]
+
+    def _info(self) -> DatasetInfo:
+
+        features = {feature: datasets.Image() for feature in self.config.features}
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(features),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation="",
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager):
+        urls = [_URL_BASE + data_file for data_file in self.config.data_files]
+        dirs = dl_manager.download_and_extract(urls)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"dirs": dirs})]
+
+    def _generate_examples(self, dirs):
+        if self.config.name != "imgs-masks":
+            for path in dirs:
+                all_fnames = {os.path.relpath(os.path.join(root, fname), start=path)
+                              for root, _dirs, files in os.walk(path) for fname in files}
+                image_fnames = sorted(fname for fname in all_fnames if os.path.splitext(fname)[1].lower() in _EXTENSION)
+                for image_fname in image_fnames:
+                    yield image_fname, {"image": os.path.join(path, image_fname)}
+        else:
+            path = dirs[0]
+            all_fnames = {os.path.relpath(os.path.join(root, fname), start=path)
+                          for root, _dirs, files in os.walk(os.path.join(path, "imgs")) for fname in files}
+            image_fnames = sorted(fname for fname in all_fnames if os.path.splitext(fname)[1].lower() in _EXTENSION)
+            for image_fname in image_fnames:
+                yield image_fname, {"image": os.path.join(path, image_fname),
+                                    "mask": os.path.join(path, image_fname.replace("imgs", "masks"))}

data/bg-00.zip

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+size 2131302329

data/bg-01.zip

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data/imgs-masks.zip

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