opencv-template-matching SKILL.md skillA
opencv-template-matching from cxcscmu/skilllearnbench is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add cxcscmu/skilllearnbench/opencv-template-matching@git:20260424.d50cf5aPins git:20260424.d50cf5a in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- cxcscmu/skilllearnbench
- Path
skills/b1-one-shot-claude-opus-4-6/video-object-counting/opencv-template-matching/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260424.d50cf5a, committed Apr 24, 2026
- Size
- 2,947 bytes
- Repository stars
- 91
- License
- MIT
Count occurrences of a template object in an image using OpenCV template matching with non-maximum suppression.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# OpenCV Template Matching for Object Counting
## Overview
Use `cv2.matchTemplate` to find all occurrences of a small template image within a larger scene image. Apply thresholding and non-maximum suppression to count distinct objects.
## Code
```python
import cv2
import numpy as np
def count_objects(scene_path, template_path, threshold=0.8):
"""Count occurrences of template in scene using template matching."""
scene = cv2.imread(scene_path, cv2.IMREAD_GRAYSCALE)
template = cv2.imread(template_path, cv2.IMREAD_GRAYSCALE)
if scene is None or template is None:
return 0
th, tw = template.shape[:2]
# Multi-scale matching can help if objects vary in size
result = cv2.matchTemplate(scene, template, cv2.TM_CCOEFF_NORMED)
# Find locations above threshold
locations = np.where(result >= threshold)
points = list(zip(*locations[::-1])) # (x, y) pairs
if len(points) == 0:
return 0
# Non-maximum suppression to avoid double counting
boxes = [(x, y, x + tw, y + th) for x, y in points]
scores = [result[y, x] for x, y in points]
indices = cv2.dnn.NMSBoxes(
[(x, y, tw, th) for x, y, _, _ in boxes],
…Read the whole file at its exact version.
How to install
mdr add cxcscmu/skilllearnbench/opencv-template-matching@sha256:8e2cd9a1dfd242bcThe line at the top of this page pins the label git:20260424.d50cf5a, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_rlpac2dqk7ieytb4)
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Versions
The registry has recorded 1 version of this file, committed on Apr 24, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2947 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
cxcscmu/skilllearnbench · 91 stars · license MIT · pushed 2026-10-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_rlpac2dqk7ieytb4 GET https://markdownregistry.com/api/v1/resolve?ref=cxcscmu/skilllearnbench/opencv-template-matching GET https://markdownregistry.com/api/v1/blob/8e2cd9a1dfd242bce0ba1146c96c64038a5f321550df785e96f56a7479c783f0
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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