Delete onlyclothe.py

onlyclothe.py

@@ -1,104 +0,0 @@
-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",
-# )
-IMAGES_URL = https://huggingface.co/datasets/chengzhiyuan/onlyclothe/blob/main/images.zip
-CONDITIONING_IMAGES_URL = https://huggingface.co/datasets/chengzhiyuan/onlyclothe/blob/main/conditioning_images.zip
-
-
-_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"]
- print("test")
- image_path = row["image"]
- image_path = os.path.join(images_dir, image_path)
- image = open(image_path, "rb").read()
- print("image")
- 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()
- print("conditioning")
- yield row["image"], {
- "text": text,
- "image": {
- "path": image_path,
- "bytes": image,
- },
- "conditioning_image": {
- "path": conditioning_image_path,
- "bytes": conditioning_image,
- },
- }