openworld-eval
CommunityStandardized evaluation for open-world detectors.
Authorrilical
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Streamlines evaluation scripting and benchmarking for open-world detectors, enabling consistent metrics and artifact-backed reports across datasets and experiments.
Core Features & Use Cases
- Reuse evaluation scripts and metrics functions to export per-sample predictions and selective metrics across datasets.
- Provide artifact-backed evaluation flows for multiple benchmarks like CommunityForensics-Small, VCT2, RAID, and ARIA.
- Allow reporting selective metrics and empirical coverage with dataset-specific evaluation modes.
Quick Start
Load a saved checkpoint and calibration artifacts from a run directory, then export metrics and per-sample predictions to eval/<dataset>/.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: openworld-eval Download link: https://github.com/rilical/OpenWorld-AI-Image-Detection/archive/main.zip#openworld-eval Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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