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object_counter

Count object instances in images using template matching with OpenCV.

4|Updated Feb 22, 2026
Search Tags:#opencv#image-processing#count#template-matching#object-counting#non-maximum-suppression
One-click install
npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill object-counter-generalreasoning
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: object_counter
Source: https://github.com/GeneralReasoning/env-skillsbench/tree/main/mario-coin-counting/environment/skills/object_counter
Command: npx skills add https://github.com/GeneralReasoning/env-skillsbench --skill object-counter-generalreasoning

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires opencv-python, numpy, and includes scripts (resource) components.

What problem does it solve?

Counting occurrences of a visual object in an image for automated analysis and quality control tasks.

Core Features & Use Cases

  • Template-based object counting using thresholding and non-maximum suppression to identify multiple instances.
  • Quick analyses for quality control, inventory checks, and scene understanding in datasets.
  • Scalable to single images or batches with simple command-line usage.

Quick Start

Run the object counting script on your input image and object template to get the total number of detected objects.

Frequently Asked Questions about object_counter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I count multiple instances of an object in an image using OpenCV?▼

Count multiple object instances in an image using OpenCV template matching with a threshold and dedup_min_dist parameter for non-maximum suppression, returning the total detected object count.

What is template matching with non-maximum suppression for object counting?▼

Template matching for object counting detects visual object instances by applying a threshold to match scores and using a dedup_min_dist parameter to perform non-maximum suppression, eliminating overlapping duplicate detections.

Can I use this OpenCV template matching approach for quality inspection and inventory counting?▼

Yes, OpenCV template matching supports automated quality inspection, inventory counting, and scene analysis by detecting and counting multiple visual object instances within a single input image.

Do I need Python and OpenCV to count objects in images with template matching?▼

Yes, counting objects in images with template matching requires Python with opencv-python and numpy dependencies installed to execute the script and process the visual data.

What are the limitations of using template matching for object counting in images?▼

Template matching for object counting relies on visual similarity, requiring a specific object template and threshold tuning, and may struggle with significant scale, rotation, or lighting variations in the input image.

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