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python script added

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  1. CVUSA_subset.py +101 -0
CVUSA_subset.py ADDED
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+ import pandas as pd
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+ from huggingface_hub import hf_hub_url
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+ import datasets
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+ import os
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+
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+ _VERSION = datasets.Version("0.0.2")
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+
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+ _DESCRIPTION = "TODO"
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+ _HOMEPAGE = "TODO"
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+ _LICENSE = "TODO"
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+ _CITATION = "TODO"
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+
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+ _FEATURES = datasets.Features(
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+ {
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+ "image": datasets.Image(),
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+ "conditioning_image": datasets.Image(),
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+ "text": datasets.Value("string"),
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+ },
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+ )
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+
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+ METADATA_URL = hf_hub_url(
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+ "Saail/CVUSA_subset",
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+ filename="random.jsonl",
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+ repo_type="dataset",
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+ )
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+
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+ IMAGES_URL = hf_hub_url(
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+ "Saail/CVUSA_subset",
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+ filename="street_view.zip",
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+ repo_type="dataset",
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+ )
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+
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+ CONDITIONING_IMAGES_URL = hf_hub_url(
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+ "Saail/CVUSA_subset",
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+ filename="sat.zip",
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+ repo_type="dataset",
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+ )
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+
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+ _DEFAULT_CONFIG = datasets.BuilderConfig(name="default", version=_VERSION)
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+
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+
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+ class Fill50k(datasets.GeneratorBasedBuilder):
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+ BUILDER_CONFIGS = [_DEFAULT_CONFIG]
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+ DEFAULT_CONFIG_NAME = "default"
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=_FEATURES,
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+ supervised_keys=None,
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+ homepage=_HOMEPAGE,
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+ license=_LICENSE,
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ metadata_path = dl_manager.download(METADATA_URL)
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+ images_dir = dl_manager.download_and_extract(IMAGES_URL)
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+ conditioning_images_dir = dl_manager.download_and_extract(
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+ CONDITIONING_IMAGES_URL
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+ )
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+
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+ return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.TRAIN,
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+ # These kwargs will be passed to _generate_examples
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+ gen_kwargs={
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+ "metadata_path": metadata_path,
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+ "images_dir": images_dir,
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+ "conditioning_images_dir": conditioning_images_dir,
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+ },
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+ ),
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+ ]
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+
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+ def _generate_examples(self, metadata_path, images_dir, conditioning_images_dir):
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+ metadata = pd.read_json(metadata_path, lines=True)
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+
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+ for _, row in metadata.iterrows():
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+ text = row["text"]
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+
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+ image_path = row["image"]
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+ image_path = os.path.join(images_dir, image_path)
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+ image = open(image_path, "rb").read()
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+
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+ conditioning_image_path = row["conditioning_image"]
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+ conditioning_image_path = os.path.join(
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+ conditioning_images_dir, row["conditioning_image"]
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+ )
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+ conditioning_image = open(conditioning_image_path, "rb").read()
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+
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+ yield row["image"], {
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+ "text": text,
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+ "image": {
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+ "path": image_path,
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+ "bytes": image,
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+ },
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+ "conditioning_image": {
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+ "path": conditioning_image_path,
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+ "bytes": conditioning_image,
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+ },
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+ }