Create princess-connect-images.py

princess-connect-images.py

@@ -0,0 +1,52 @@
+import os
+import datasets
+from huggingface_hub import HfApi
+from datasets import DownloadManager, DatasetInfo
+from datasets.data_files import DataFilesDict
+
+_EXTENSION = [".png", ".jpg", ".jpeg"]
+_DESCRIPTION = ""
+_NAME = "animelover/princess-connect-images"
+_REVISION = "main"
+
+
+class DanbooruDataset(datasets.GeneratorBasedBuilder):
+
+ def _info(self) -> DatasetInfo:
+ return datasets.DatasetInfo(
+ description=_DESCRIPTION,
+ features=datasets.Features(
+ {
+ "image": datasets.Image(),
+ "tags": datasets.Value("string")
+ }
+ ),
+ supervised_keys=None,
+ citation="",
+ )
+
+ def _split_generators(self, dl_manager: DownloadManager):
+ hfh_dataset_info = HfApi().dataset_info(_NAME, revision=_REVISION, timeout=100.0)
+ data_files = DataFilesDict.from_hf_repo(
+ {datasets.Split.TRAIN: ["**"]},
+ dataset_info=hfh_dataset_info,
+ allowed_extensions=["zip"],
+ )
+ gs = []
+ for split, files in data_files.items():
+ downloaded_files = dl_manager.download_and_extract(files)
+ gs.append(datasets.SplitGenerator(name=split, gen_kwargs={"filepath": downloaded_files}))
+ return gs
+
+ def _generate_examples(self, filepath):
+ for path in filepath:
+ 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:
+ image_path = os.path.join(path, image_fname)
+ tags_path = os.path.join(path, os.path.splitext(image_fname)[0] + ".txt")
+ with open(tags_path, "r", encoding="utf-8") as f:
+ tags = f.read()
+ yield image_fname, {"image": image_path, "tags": tags}