run2_matching-evaluation
Efficient greedy matching of cluster centroids to expert points with distance constraint.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 92
- Forks
- 7
01 前言 Front Matter
- name
- run2_matching-evaluation
- description
- Efficient greedy matching of cluster centroids to expert points with distance constraint.
03 SKILL.md 正文
Logic
- For each image, build a full distance matrix (N centroids x M experts).
- Sorting the entire matrix allows for optimal greedy matching without repeated searching.
- Ensure the distance constraint (max distance 100 pixels) is applied strictly.
04 同仓库更多 Skills
object_counter
Count occurrences of an object in the image using computer vision algorithm.
travel-planning-workflow
Invoke this skill when performing travel planning. It defines a structured workflow for generating itineraries. Following this workflow is essential to ensure the final plan satisfies user requirements.
bundled-dataset-search-tool
invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.