azure-custom-vision

name	azure-custom-vision
description	Expert knowledge for Azure AI Custom Vision development including best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. Use when exporting Custom Vision models, calling prediction APIs, using ONNX/TensorFlow, managing CMK/RBAC, or Smart Labeler, and other Azure AI Custom Vision related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Foundry Local (use microsoft-foundry-local).
compatibility	Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
metadata	{"generated_at":"2026-06-21","generator":"docs2skills/1.0.0"}

Azure AI Custom Vision Skill

This skill provides expert guidance for Azure AI Custom Vision. Covers best practices, decision making, limits & quotas, security, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.

How to Use This Skill

IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file

IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide

This skill requires network access to fetch documentation content:

• Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
• Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.

Category Index

Category	Lines	Description
Best Practices	L34-L39	Improving Custom Vision model quality with better data collection/labeling strategies and using Smart Labeler to speed and automate image annotation
Decision Making	L40-L45	Guidance on selecting the best Custom Vision domain for your scenario and planning migrations from Custom Vision to other Azure or third‑party vision services.
Limits & Quotas	L46-L50	Details on Custom Vision usage limits per pricing tier, including training/prediction quotas, project and image caps, and how limits affect model training and deployment.
Security	L51-L57	Managing Custom Vision security: encryption with customer-managed keys, secure data handling/export/deletion, and configuring Azure RBAC roles and permissions.
Integrations & Coding Patterns	L58-L68	Using Custom Vision models and APIs in apps: exporting via SDK, running ONNX/TensorFlow in Windows ML/Python, calling classification/detection APIs, and integrating with Azure Storage.
Deployment	L69-L73	Deploying Custom Vision models: copying/backing up projects across regions and exporting models for offline, edge, and mobile (TensorFlow, ONNX, iOS/Android) use.

Best Practices

Topic	URL
Apply Custom Vision data strategies to improve models	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/getting-started-improving-your-classifier
Speed up Custom Vision labeling with Smart Labeler	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/suggested-tags

Decision Making

Topic	URL
Plan migration from Custom Vision to alternative services	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/migration-options
Choose the right Custom Vision domain for your project	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/select-domain

Limits & Quotas

Topic	URL
Review Custom Vision limits and quotas by tier	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/limits-and-quotas

Security

Topic	URL
Configure customer-managed keys for Custom Vision encryption	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/encrypt-data-at-rest
View, export, and delete Custom Vision data securely	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/export-delete-data
Configure Azure RBAC roles for Custom Vision projects	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/role-based-access-control

Integrations & Coding Patterns

Topic	URL
Integrate Custom Vision ONNX models with Windows ML apps	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/custom-vision-onnx-windows-ml
Run exported Custom Vision TensorFlow models in Python	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/export-model-python
Export Custom Vision models programmatically with SDK	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/export-programmatically
Use Custom Vision SDK for image classification	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/quickstarts/image-classification
Call Custom Vision object detection APIs with SDK	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/quickstarts/object-detection
Integrate Custom Vision with Azure Storage queues and blobs	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/storage-integration
Use Custom Vision prediction API to test images	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/use-prediction-api

Deployment

Topic	URL
Copy and back up Custom Vision projects across regions	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/copy-move-projects
Export Custom Vision models for offline and mobile use	https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/export-your-model