Scripts to run anti-spoofing experiments
This package is part of the signal-processing and machine learning toolbox
Bob.
This package is the base of the bob.pad family of packages, which allow to
run comparable and reproducible presentation attack detection (PAD) experiments
on publicly available databases.
This package contains basic functionality to run PAD experiments. It provides a generic API for PAD including:
- A database and its evaluation protocol
- A data preprocessing algorithm
- A feature extraction algorithm
- A PAD algorithm
All these steps of the PAD system are given as configuration files. All the algorithms are standardized on top of scikit-learn estimators.
In this base package, only a core functionality is implemented. The specialized
algorithms should be provided by other packages, which are usually in the
bob.pad namespace, like
bob.pad.face.
Installation
Complete Bob's installation instructions. Then, to install this package, run:
conda install bob.pad.base
Contact
For questions or reporting issues to this software package, contact our development mailing list.
1 maintainer
Release files for bob.pad.base 6.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| bob_pad_base-6.0.1.tar.gz | 505.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| bob.pad.base-6.0.1-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 542.3 kB
Release files / bob_pad_base-6.0.1.tar.gz
| Download URL | bob_pad_base-6.0.1.tar.gz |
|---|---|
| Size | 505.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
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Release files / bob.pad.base-6.0.1-py2.py3-none-any.whl
| Download URL | bob.pad.base-6.0.1-py2.py3-none-any.whl |
|---|---|
| Size | 36.6 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.14
|
