What are the trigger terms for this skill?

Common triggers include phrases like 'analyze image', 'object detection', 'computer vision', and 'image segmentation'.

Can it identify specific objects like cars or people?

Yes, the skill can detect specific objects and return labels along with bounding box coordinates for their location.

How does Claude return the results of the vision analysis?

Claude generates Python code to process the image and provides the results directly in the chat, including labels, confidence scores, or lists of detected items.

Does this skill require external plugins?

Yes, it is designed to work specifically with the computer-vision-processor plugin to execute the /process-vision command.

What types of image analysis can this skill perform?

This skill supports object detection (finding items), image classification (categorizing images), and image segmentation (mapping specific regions).

Computer Vision Adapter

Name: Computer Vision Adapter
Author: BbgnsurfTech

byBbgnsurfTech

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Ciencia de Datos y ML

Processes and analyzes images using advanced computer vision techniques to identify objects, classify scenes, and segment visual data.

Acerca de

The Computer Vision Adapter skill bridges the gap between Claude's text reasoning and visual analysis by leveraging the computer-vision-processor plugin. It automates complex image processing workflows such as object detection, image classification, and segmentation, allowing Claude to extract meaningful insights from visual inputs. By generating and executing optimized Python code via the /process-vision command, this skill enables developers to integrate sophisticated visual intelligence into their AI-driven workflows.

Características Principales

Detailed image segmentation to identify specific regions
Seamless integration with the /process-vision plugin command
3 GitHub stars
Robust data validation and error handling for image inputs
Automated object detection and bounding box generation
High-accuracy image classification with confidence scoring

Casos de Uso

Identifying specific components or pedestrians in technical photography
Extracting spatial information and object counts from environment photos
Categorizing visual assets for digital asset management systems

Acerca de

Características Principales

Detailed image segmentation to identify specific regions
Seamless integration with the /process-vision plugin command
3 GitHub stars
Robust data validation and error handling for image inputs
Automated object detection and bounding box generation
High-accuracy image classification with confidence scoring

Casos de Uso

Identifying specific components or pedestrians in technical photography
Extracting spatial information and object counts from environment photos
Categorizing visual assets for digital asset management systems