Datasets:
Size:
10K<n<100K
License:
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, | |
}, | |
} | |