clip

Classifies images zero-shot and matches image-text pairs using CLIP.

Updated Mar 12, 2026
One-click install
npx skills add https://github.com/GarrettRoi/open-manus --skill clip-garrettroi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: clip
Source: https://github.com/GarrettRoi/open-manus/tree/main/skills/mlops/models/clip
Command: npx skills add https://github.com/GarrettRoi/open-manus --skill clip-garrettroi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires transformers, torch, pillow, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables AI to understand images based on natural language descriptions, facilitating tasks that require connecting visual content with textual concepts without specific training data.

Core Features & Use Cases

  • Zero-Shot Image Classification: Categorize images using text labels without prior training.
  • Image-Text Similarity: Measure how well an image matches a given text description.
  • Semantic Image Search: Find images based on their semantic meaning described in text.
  • Content Moderation: Identify potentially inappropriate or sensitive content in images.

Quick Start

Use the clip skill to classify the attached image 'photo.jpg' against the labels 'a dog', 'a cat', and 'a bird'.

Frequently Asked Questions about clip

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

FAQPage Schema
How do I perform zero-shot image classification without fine-tuning?

Zero-shot image classification is achieved by matching images against text labels using a vision-language model. This Skill categorizes images based on natural language descriptions without requiring specific training data.

What is the best way to measure image-text similarity for content moderation?

Image-text similarity measures how well visual content matches a text description. This Skill connects vision and language models to identify inappropriate or sensitive content based on semantic meaning.

Can I use transformers and torch for cross-modal retrieval tasks?

Yes, cross-modal retrieval is supported using transformers and torch. This Skill enables semantic image search by finding images based on text descriptions across vision and language modalities.

Do I need to install pillow to enable zero-shot image classification?

Yes, pillow is required for image processing. Along with transformers and torch, these libraries provide the environment needed to process images and connect them with language models for classification.

How does a vision-language model handle image search without prior training?

A vision-language model handles image search by leveraging pre-training on 400M image-text pairs. This allows the Skill to perform general-purpose image understanding and retrieval based on semantic meaning rather than fine-tuning.