pharmapsychotic/clip-interrogator

Health v2 · maintenance only

Adoption not part of the score

2982 stars · 434 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Python library that combines OpenAI's CLIP and Salesforce's BLIP to reverse-engineer text prompts from images, optimized for use with text-to-image models like Stable Diffusion. It is available as a pip package, Colab notebooks, HuggingFace Space, Replicate demo, and a Stable Diffusion Web UI extension.

Use cases

• generate a text prompt from an image
• reverse-engineer prompts for stable diffusion
• find what prompt would recreate an existing image
• caption images with detailed style descriptions
• compare different CLIP models for image-to-prompt matching
• integrate image-to-prompt into a python pipeline

When to choose

• you need to derive prompts from reference images for text-to-image generation
• you want a pip-installable library or hosted demo for image captioning with CLIP/BLIP
• you want to pick specific CLIP models like ViT-L-14/openai for Stable Diffusion versions

When to avoid

• you need general-purpose image classification or object detection
• you need a production image captioning service with high throughput
• you don't have GPU resources and need fast inference

Facets

library · maturity stable

machine-learning image-processing prompt-engineering nlp artificial-intelligence image-processing large-language-models python cross-platform clip blip stable-diffusion text-to-image image-captioning pytorch gpu

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markdown · JSON · MCP: product_card(name="pharmapsychotic/clip-interrogator")