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Get Started Free →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-le
.claude/skills/microsoftdocs-azure-custom-vision/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 81% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 64% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 9% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 43% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 46% | 0% |
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.
> 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:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| 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. |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
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