Merge branch 'main' of https://huggingface.co/datasets/faridlab/deepaction_v1
Browse files- README.md +1 -2
- deepaction_v1.py +23 -9
README.md
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---
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license: openrail
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viewer: false
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tags:
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- deepfakes
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## Licensing
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<br>
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---
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viewer: false
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tags:
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- deepfakes
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## Licensing
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The AI-generated videos (folders BDAnimateDiffLightning, CogVideoX5B, RunwayML, StableDiffusion, Veo, and VideoPoet) are released under <a href='https://creativecommons.org/licenses/by/4.0/deed.en'>the CC BY 4.0 license</a>. The real videos (folder Pexels) are released under <a href='https://www.pexels.com/license/'>the Pexels license</a>.
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<br>
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deepaction_v1.py
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_LICENSE = "TBD"
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class DeepActionV1(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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description=_DESCRIPTION,
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features=datasets.Features({
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"video": datasets.Video(),
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"label": datasets.ClassLabel(names=
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}),
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supervised_keys=("video", "label"),
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homepage=_HOMEPAGE,
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)
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def _split_generators(self, dl_manager):
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return [
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datasets.SplitGenerator(
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]
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def _generate_examples(self, data_dir):
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subfolder_path = os.path.join(label_dir, subfolder)
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if os.path.isdir(subfolder_path):
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for video_file in os.listdir(subfolder_path):
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if video_file.endswith(".mp4"):
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_LICENSE = "TBD"
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SUPPORTED = ["VideoPoet", "BDAnimateDiffLightning", "CogVideoX5B", "Pexels", "RunwayML", "StableDiffusion"] # todo add veo
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class DeepActionV1(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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description=_DESCRIPTION,
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features=datasets.Features({
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"video": datasets.Video(),
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"label": datasets.ClassLabel(names=SUPPORTED), # Add all category names
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}),
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supervised_keys=("video", "label"),
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homepage=_HOMEPAGE,
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)
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def _split_generators(self, dl_manager):
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urls = []
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base_url = "https://huggingface.co/datasets/faridlab/deepaction_v1/resolve/main/"
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for engine in SUPPORTED:
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for i in list(range(95)) + list(range(99, 104)):
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if engine in ["Pexels", "Veo"]:
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urls.append(os.path.join(base_url, engine, "{}".format(i), "a.mp4"))
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elif engine in ["VideoPoet"]:
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for vid_file in ["a.mp4", "b.mp4", "c.mp4", "d.mp4"]:
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urls.append(os.path.join(base_url, engine, "{}".format(i), vid_file))
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else:
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for vid_file in ["a.mp4", "b.mp4", "c.mp4", "d.mp4", "e.mp4"]:
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urls.append(os.path.join(base_url, engine, "{}".format(i), vid_file))
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data_dir = dl_manager.download_and_extract(urls)
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return [
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datasets.SplitGenerator(
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]
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def _generate_examples(self, data_dir):
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for label in os.listdir(data_dir):
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label_path = os.path.join(data_dir, label)
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if os.path.isdir(label_path):
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for subfolder in os.listdir(label_path):
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subfolder_path = os.path.join(label_path, subfolder)
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if os.path.isdir(subfolder_path):
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for video_file in os.listdir(subfolder_path):
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if video_file.endswith(".mp4"):
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