Does it require external API calls for processing?

The skill utilizes the computer-vision-processor plugin to handle the analysis; processing may be local or cloud-based depending on your specific plugin configuration.

How do I trigger the vision processing capabilities?

You can trigger the skill by using natural language prompts such as 'analyze this image', 'detect objects', or 'perform image segmentation' while referencing an image file.

What types of images can this skill process?

This skill supports common image formats such as PNG and JPEG, provided they are accessible to the local environment where Claude Code is running.

What kind of output does the classification task provide?

It returns the most likely category for the image along with a confidence score to help you gauge the accuracy of the result.

Can it identify multiple different objects in one request?

Yes, the object detection feature is designed to identify and return coordinates for multiple distinct objects and categories within a single image.

Computer Vision Analysis

Name: Computer Vision Analysis
Author: jeremylongshore

byjeremylongshore

•

883

Data Science & ML

Processes and analyzes images using computer vision techniques to perform object detection, image classification, and segmentation.

About

The Computer Vision Analysis skill equips Claude with the ability to interpret visual data through the computer-vision-processor plugin. By automating complex workflows like object detection and image segmentation, this skill allows users to extract actionable insights from images directly within their development environment. Whether you are identifying specific features in a photograph, categorizing image datasets, or partitioning images into meaningful regions, this skill optimizes performance and provides detailed metadata including bounding boxes, labels, and confidence scores.

Key Features

Automated Python code generation for vision processing
883 GitHub stars
Real-time object detection with bounding box coordinates
Precise image segmentation for region-based analysis
Seamless integration with the /process-vision plugin command
Automated image classification into predefined categories

Use Cases

Identifying and counting specific objects like cars or pedestrians within a scene
Automating the labeling of large image datasets for machine learning projects
Analyzing screenshots to identify UI components or visual layout structures

About

Key Features

Automated Python code generation for vision processing
883 GitHub stars
Real-time object detection with bounding box coordinates
Precise image segmentation for region-based analysis
Seamless integration with the /process-vision plugin command
Automated image classification into predefined categories

Use Cases

Identifying and counting specific objects like cars or pedestrians within a scene
Automating the labeling of large image datasets for machine learning projects
Analyzing screenshots to identify UI components or visual layout structures