azure-ai-vision-imageanalysis-py
Image captions, tags, OCR, objects
Developer Setup
Setup & Installation
npx skills add https://github.com/microsoft/skills --skill azure-ai-vision-imageanalysis-pynpx skills add https://github.com/microsoft/skills --skill azure-ai-vision-imageanalysis-pyOverview
What This Skill Does
Azure AI Vision Image Analysis SDK for Python wraps the Azure AI Vision 4.0 API. It extracts captions, tags, detected objects with bounding boxes, OCR text, people locations, and suggested crop regions from images submitted by URL or file upload.
Application
When to use this Skill
- Configuring integration settings for custom agent workflows.
- Optimizing query execution and response latency in production.
- Developing clean, standard-compliant implementations for enterprise services.
- Troubleshooting connection timeouts and authentication handshakes.
- Monitoring API rate limits and execution pipelines programmatically.
Documentation
Show Skills.md file
Azure AI Vision Image Analysis SDK for Python
Client library for Azure AI Vision 4.0 image analysis including captions, tags, objects, OCR, and more.
Installation
pip install azure-ai-vision-imageanalysis
Environment Variables
VISION_ENDPOINT=https://<resource>.cognitiveservices.azure.com # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production
VISION_KEY=<your-api-key> # Only required for the legacy API-key auth path below
Authentication & Lifecycle
🔑 Two rules apply to every code sample below:
- Prefer
DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
- Local dev:
DefaultAzureCredentialworks as-is.- Production: set
AZURE_TOKEN_CREDENTIALS=prod(orAZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
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