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OpenCV血管骨架化与距离阈值异常点过滤 — measured AI agent skill | DecimalAI

ecnu-icalk/OpenCV血管骨架化与距离阈值异常点过滤

NewSkillScoreMaintained

使用OpenCV对图像进行骨架化处理，并去除游离孤点及基于距离阈值过滤连接时的异常点。

codingby ecnu-icalk

Links this skill to your agents and keeps it current with the author’s updates.

Automatic

Coding pack

1 · One-time — install the CLI (docs ↗)

pip install decimalai

2 · Get the skill — writes .claude/skills/ecnu-icalk-opencv/SKILL.md

decimalai skills pull ecnu-icalk-opencv --out .claude/skills/

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/ecnu-icalk-opencv/SKILL.md https://app.decimal.ai/s/ecnu-icalk-opencv/SKILL.md

Raw file: /s/ecnu-icalk-opencv/SKILL.md ↗ · machine-readable summary at /s/ecnu-icalk-opencv.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

No production data for this skill yet — usage numbers appear here once agents start running it.

Anonymized aggregate across every org using this skill — proof from real production use, not a demo.

Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 3h ago

Yes — +14% lift+11% tokens0% turns100% of whole cases pass with skill (22/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-19	✗→✓	▲ Improved	17%	0%
case-07	✗→✓	▲ Improved	-17%	0%
case-14	✗→✓	▲ Improved	46%	0%
case-16	✓→✓	＝ Same ✓	15%	0%
case-17	✓→✓	＝ Same ✓	63%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

ecnu-icalk / autoskill

SkillBank/ConvSkill/chinese_gpt3.5_8/opencv%E8%A1%80%E7%AE%A1%E9%AA%A8%E6%9E%B6%E5%8C%96%E4%B8%8E%E8%B7%9D%E7%A6%BB%E9%98%88%E5%80%BC%E5%BC%82%E5%B8%B8%E7%82%B9%E8%BF%87%E6%BB%A4/SKILL.md

View on GitHub ↗

Imported 8/3/2026Version v1

Skill contents

SKILL.md

OpenCV血管骨架化与距离阈值异常点过滤

使用OpenCV对图像进行骨架化处理，并去除游离孤点及基于距离阈值过滤连接时的异常点。

Prompt

Role & Objective

扮演一个OpenCV图像处理专家。你的任务是对血管等管状结构图像进行骨架化处理，并清理骨架线中的噪声和异常点。

Operational Rules & Constraints

使用OpenCV库和C++语言编写代码。
实现图像骨架化（Skeletonization）功能。
在骨架化后，去除游离的孤点（Isolated Points）。
在连接骨架点生成曲线时，必须应用距离阈值过滤逻辑：如果一个点与其他点之间的距离超过设定的阈值，则将该点视为异常点并抛弃。
确保代码能够处理二值化后的图像输入。

Anti-Patterns

不要使用会破坏主骨架线的形态学操作（如过度的开运算）。不要忽略用户关于“连接点时基于距离抛弃点”的具体逻辑要求。

Triggers

血管骨架化代码
去除骨架游离孤点
骨架线异常点过滤
OpenCV skeletonization outlier removal

Want to see if ecnu-icalk/OpenCV血管骨架化与距离阈值异常点过滤 would activate on your phrasing? Try it before you install — no LLM call, no signup.

Other measured skills in the registry, with their headline benchmark lift.