Upload onlyclothe.py

onlyclothe.py

@@ -0,0 +1,104 @@
+import pandas as pd
+from huggingface_hub import hf_hub_url
+import datasets
+import os
+
+_VERSION = datasets.Version("0.0.2")
+
+_DESCRIPTION = "TODO"
+_HOMEPAGE = "TODO"
+_LICENSE = "TODO"
+_CITATION = "TODO"
+
+_FEATURES = datasets.Features(
+ {
+ "image": datasets.Image(),
+ "conditioning_image": datasets.Image(),
+ "text": datasets.Value("string"),
+ },
+)
+
+METADATA_URL = hf_hub_url(
+ "chengzhiyuan/onlyclothe",
+ filename="train.jsonl",
+ repo_type="dataset",
+)
+
+IMAGES_URL = hf_hub_url(
+ "chengzhiyuan/onlyclothe",
+ filename="images.zip",
+ repo_type="dataset",
+)
+
+CONDITIONING_IMAGES_URL = hf_hub_url(
+ "chengzhiyuan/onlyclothe",
+ filename="conditioning_images.zip",
+ repo_type="dataset",
+)
+print(METADATA_URL)
+print(IMAGES_URL)
+print(CONDITIONING_IMAGES_URL)
+
+_DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
+
+
+class Onlyclothe(datasets.GeneratorBasedBuilder):
+ BUILDER_CONFIGS = [_DEFAULT_CONFIG]
+ DEFAULT_CONFIG_NAME = "default"
+
+ def _info(self):
+ return datasets.DatasetInfo(
+ description=_DESCRIPTION,
+ features=_FEATURES,
+ supervised_keys=None,
+ homepage=_HOMEPAGE,
+ license=_LICENSE,
+ citation=_CITATION,
+ )
+
+ def _split_generators(self, dl_manager):
+ metadata_path = dl_manager.download(METADATA_URL)
+ images_dir = dl_manager.download_and_extract(IMAGES_URL)
+ conditioning_images_dir = dl_manager.download_and_extract(
+ CONDITIONING_IMAGES_URL
+ )
+
+ return [
+ datasets.SplitGenerator(
+ name=datasets.Split.TRAIN,
+ # These kwargs will be passed to _generate_examples
+ gen_kwargs={
+ "metadata_path": metadata_path,
+ "images_dir": images_dir,
+ "conditioning_images_dir": conditioning_images_dir,
+ },
+ ),
+ ]
+
+ def _generate_examples(self, metadata_path, images_dir, conditioning_images_dir):
+ metadata = pd.read_json(metadata_path, lines=True)
+
+ for _, row in metadata.iterrows():
+ text = row["text"]
+
+ image_path = row["image"]
+ image_path = os.path.join(images_dir, image_path)
+ image = open(image_path, "rb").read()
+
+ conditioning_image_path = row["conditioning_image"]
+ conditioning_image_path = os.path.join(
+ conditioning_images_dir, row["conditioning_image"]
+ )
+ conditioning_image = open(conditioning_image_path, "rb").read()
+
+ yield row["image"], {
+ "text": text,
+ "image": {
+ "path": image_path,
+ "bytes": image,
+ },
+ "conditioning_image": {
+ "path": conditioning_image_path,
+ "bytes": conditioning_image,
+ },
+ }