## Computer Vision with AI APIs
### Vision Through LLMs
Modern multimodal LLMs provide powerful vision capabilities through simple API calls:
```typescript const response = await openai.chat.completions.create({ model: "gpt-4o", messages: [{ role: "user", content: [ { type: "image_url", image_url: { url: imageUrl } }, { type: "text", text: "Classify this image. Return the category and confidence." } ], }], }); ```
### Structured Image Analysis
```typescript const response = await openai.chat.completions.create({ model: "gpt-4o", messages: [{ role: "user", content: [ { type: "image_url", image_url: { url: imageUrl } }, { type: "text", text: "Analyze this image and return JSON with: objects, scene, colors, mood, text_content" } ], }], response_format: { type: "json_object" }, }); ```
### Dedicated Vision APIs
| API | Strengths | Best For | |-----|-----------|----------| | Google Cloud Vision | OCR, labels, faces, landmarks | Production OCR | | AWS Rekognition | Faces, moderation, custom labels | Content moderation | | Azure Computer Vision | OCR, spatial analysis, captions | Enterprise | | GPT-4o / Gemini | General understanding, reasoning | Flexible analysis | | Roboflow | Custom object detection | Specialized detection |
### Choosing Your Approach
- LLM Vision: Best for general understanding, reasoning about images, flexible queries
- Specialized APIs: Best for specific tasks (OCR, face detection) with structured output
- Custom models: Best when you need domain-specific detection (defects, medical imaging)