Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  fs: fsspec.AbstractFileSystem = fsspec.filesystem("memory")
                                                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 302, in filesystem
                  cls = get_filesystem_class(protocol)
                File "/usr/local/lib/python3.14/site-packages/fsspec/registry.py", line 239, in get_filesystem_class
                  raise ValueError(f"Protocol not known: {protocol}")
              ValueError: Protocol not known: memory
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 71, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Summary

This is the dataset proposed in our paper Scaling Laws for Deepfake Detection.

ScaleDF is the largest dataset in the deepfake detection domain to date. It contains over 5.8 million real images from 51 different datasets (domains) and more than 8.8 million fake images generated by 102 deepfake methods.

Using ScaleDF, we observe power-law scaling similar to that shown in large language models (LLMs). Specifically, the average detection error follows a predictable power-law decay as either the number of real domains or the number of deepfake methods increases.

Directory

*DATA_PATH
    *ScaleDF
        *train
            000000AFAD.tar # The tar files starting with 000000 contain real faces.
            000000AVA.tar 
            ...
            AMatrix_faces.tar # The tar files starting without 000000 contain fake faces.
            AniPortrait_faces.tar
            ...
        *val
            000000300VW.tar # The tar files starting with 000000 contain real faces.
            000000GENKI-4K.tar
            ...
            3dSwap_faces.tar # The tar files starting without 000000 contain fake faces.
            DiffFace_faces.tar
            ...
    *Established_benchmarks
        *CDFv2.tar
        *DF40.tar
        *DeepFakeDetection.tar
        *DeepFakeFace.tar
        *ForgeryNet.tar
        *Wild_Deepfake.tar
        *ScaleDF.tar # We also adapt the ScaleDF validation set format to other established benchmarks and provide the adapted version here.

Download

Automatic

from huggingface_hub import snapshot_download

local_dir = snapshot_download(
    repo_id="scaledf/ScaleDF",
    repo_type="dataset"
)

Manually

wget https://huggingface.co/datasets/scaledf/ScaleDF/resolve/main/ScaleDF/train/000000AFAD.tar # This is an example.

Compared to existing datasets

Observed scaling laws

Included real datasets

We

Included deepfake methods

License

Our ScaleDF is released under the CC BY-NC-SA 4.0 license.

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