CV FAQs

Question 1

What is CV?

Accepted Answer

CV is a minimal computer vision server designed to generate detailed alt text, dense captions, and structured JSON metadata for images. It leverages large vision models to automate image recognition and rich data generation for various applications.

Question 2

How does CV generate image metadata?

Accepted Answer

CV utilizes large vision models, accessible through OpenRouter or local backends, to analyze images. It can produce concise alt text, detailed multi-sentence captions, and comprehensive structured JSON metadata. You can configure processing modes, such as 'double' (vision for alt/caption, text-only for metadata) or 'triple' (vision for both steps).

Question 3

What types of image inputs does CV support?

Accepted Answer

CV is versatile, supporting image processing from both remote URLs (e.g., `https://example.com/image.jpg`) and local file paths (`./image.png`), offering flexibility for various workflows.

Question 4

Can I use CV with local AI models?

Accepted Answer

Yes, CV is highly configurable and supports local backends. You can install optional dependencies, set up a locally available large vision model (like Qwen2-VL-2B-Instruct), and configure CV to use it, overriding the default OpenRouter integration for privacy or specific model needs.

Question 5

How can CV improve my content and SEO?

Accepted Answer

By generating accurate alt text and detailed captions, CV significantly enhances image accessibility for visually impaired users and boosts your content's SEO ranking. Structured JSON metadata further streamlines content management by providing rich, machine-readable data for better indexing and understanding by search engines.

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