DeepClip
CLIP for deepfakes
Dataset
preprocess/ builds the frame-level FaceForensics++ dataset and its forgery annotation
(face crops, 68 facial landmarks, forgery masks and forgery features) used to train DeepClip.
1 maintainer
Metadata
1 maintainer
Release files for deepclip 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| deepclip-0.1.0.tar.gz | 1.4 MB | With provenance | Details for deepclip-0.1.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| deepclip-0.1.0-py3-none-any.whl | Python 3 | none | any | Details for deepclip-0.1.0-py3-none-any.whl |
Total release size: 2.8 MB
Release files / deepclip-0.1.0.tar.gz
| Download URL | deepclip-0.1.0.tar.gz |
|---|---|
| Size | 1.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
299a4e8836475078ba7338d02a13972e5ae7ccf18fdcd081fb54def353f097e8
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Transparency logRelease files / deepclip-0.1.0-py3-none-any.whl
| Download URL | deepclip-0.1.0-py3-none-any.whl |
|---|---|
| Size | 1.4 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d04c90e1ee00727e9bebe1a199454aaa5c249bfe81bf5f09ce7ff368cad548b9
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BLAKE2b-256 checksum How to use checksums |
22fbaa31d7208df071d3a9f8aeff22f2739f8c8d3c41b6e9e38fcc6673c4ed69
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.16
|
Provenance
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Transparency logSecurity for deepclip 0.1.0
Provenance
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Attestation for deepclip-0.1.0.tar.gz
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PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 5, 2026.
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