About Vision Analysis
Credible and deep analysis of computer vision models.
Mission
Vision Analysis provides credible benchmarks for object detection models. All benchmarks are run using vision-analysis-benchmark on top of LibreYOLO.
Submission Flow
Community contributors run the harness locally, produce a submission JSON, and open a pull request adding that file under submissions/.
CI validates each submission against the schema and the current support matrix, then rebuilds the canonical benchmark dataset consumed by the website.
The site renders only from the generated canonical dataset. Raw submission files stay in the repo for review and provenance, but the public UI reads the rebuilt verified snapshot.
Methodology
All models are evaluated on COCO val2017 (5,000 images, 80 classes) using the standard pycocotools evaluation protocol.
We measure end-to-end latency including preprocessing, inference, and postprocessing when the runtime exposes those phases.
Every published result should include the benchmark config, actual input size, hardware identity, runtime/provider, and the supporting LibreYOLO commit so the number is reproducible.