Skip to main content

Python port of EA's IRIS - Photosensitive epilepsy risk detection for video content

Project description

IRIS-PSE-Detection

PyPI version CI

Python port of IRIS - Electronic Arts' photosensitive epilepsy risk detection library.

IRIS analyzes video content to detect flash patterns that may trigger seizures in people with photosensitive epilepsy, based on guidelines from W3C WCAG and ISO 9241-391.

Installation

pip install iris-pse-detection

Or for development:

git clone https://github.com/tokoroten/iris-pse-detection
cd iris-pse-detection
uv sync

Usage

iris video.mp4

Or with Python:

from iris_pse_detection import VideoAnalyser, Configuration

config = Configuration()
analyser = VideoAnalyser(config)
result = analyser.analyse_video("video.mp4")
print(result.overall_result)

Features

  • Luminance flash detection
  • Red saturation flash detection
  • Transition tracking with 1-second sliding window
  • Extended failure detection (4+ seconds)
  • Pattern detection (optional)

Note on Accuracy

Due to floating-point precision differences between C++ and Python/NumPy, results may vary slightly from the original IRIS implementation. These differences are minimal and occur at boundary conditions where values are very close to detection thresholds.

Acknowledgments

This project is a Python port of IRIS by Electronic Arts Inc., originally released under the BSD 3-Clause License.

License

MIT License - see LICENSE for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iris_pse_detection-1.1.2.tar.gz (76.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iris_pse_detection-1.1.2-py3-none-any.whl (29.4 kB view details)

Uploaded Python 3

File details

Details for the file iris_pse_detection-1.1.2.tar.gz.

File metadata

  • Download URL: iris_pse_detection-1.1.2.tar.gz
  • Upload date:
  • Size: 76.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for iris_pse_detection-1.1.2.tar.gz
Algorithm Hash digest
SHA256 f8779deb7a7f78d825f00482379d9851f511bee9dda6a0a382852ce4a22cd28b
MD5 859d52d89f24c3ee17c2fd6644fe9d4e
BLAKE2b-256 a4f0a01597b20250cb61ddfe191d86df05b4624875209476c2d893fb9f0141ce

See more details on using hashes here.

Provenance

The following attestation bundles were made for iris_pse_detection-1.1.2.tar.gz:

Publisher: publish.yml on tokoroten/iris-pse-detection

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file iris_pse_detection-1.1.2-py3-none-any.whl.

File metadata

File hashes

Hashes for iris_pse_detection-1.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 633517f6a24dde5288bbdce59b7bed3eba3e9d9a115a7f9a9e7323f13e15fdef
MD5 19ea17f341ad2c70eced644cb7a466af
BLAKE2b-256 bbb48c2d5887bc9b59b043ebf826aca538147452526faf5f49a08cc321516a34

See more details on using hashes here.

Provenance

The following attestation bundles were made for iris_pse_detection-1.1.2-py3-none-any.whl:

Publisher: publish.yml on tokoroten/iris-pse-detection

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page