---

name: performance-and-visualization description: "Benchmark LightGlue latency and throughput, and create or save match, keypoint, pruning, and benchmark plots." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Performance and Visualization

Use this sub-skill when the task is about measuring LightGlue speed or making match visualizations.

Primary entry points

• scripts/benchmark_lightglue.py: benchmark matcher latency or throughput with safe defaults, optional compile and FlashAttention toggles, pruning-threshold overrides, a synthetic fallback image pair, and --save / --no-show support.
• references/benchmarking.md: benchmark workflow, measurement semantics, speed knobs, and weight-download caveats.
• references/visualization.md: viz2d plotting helpers for matches, keypoints, pruning colors, labels, and saved plots.
• references/troubleshooting.md: common device, backend, compile, pruning, and headless display fixes.

Boundaries

• For matcher constructor choices, confidence settings, and routing around LightGlue configuration, use ../matcher-configuration/SKILL.md.
• For extractor selection and feature-specific setup, use ../extractors-and-features/SKILL.md.
• For a one-off image-pair matching workflow rather than benchmarking or plotting, use ../image-pair-matching/SKILL.md.

Notes

• The benchmark script times matcher forward passes after feature extraction.
• First-use runs may download pretrained extractor or matcher weights.
• Runtime dependencies assumed here are torch, torchvision, numpy, opencv-python, matplotlib, and kornia.