Roboflow Docs
DashboardResourcesProducts
  • Product Documentation
  • Developer Reference
  • Changelog
  • Roboflow Documentation
  • Quickstart
  • Workspaces
    • Workspaces, Projects, and Models
    • Create a Workspace
    • Rename a Workspace
    • Delete a Workspace
  • Team Members
    • Invite a Team Member
    • Role-Based Access Control (RBAC)
    • Change a Team Member Role
    • Remove a Team Member
  • Single Sign On (SSO)
  • Workflows
    • What is Workflows?
    • Create a Workflow
    • Build a Workflow
    • Test a Workflow
    • Deploy a Workflow
    • Workflow Examples
      • Multimodal Model Workflow
    • Share a Workflow
    • Workflows AI Assistant
  • Enterprise Integrations
  • Dataset Management
    • Create a Project
    • Upload Images, Videos, and Annotations
      • Import Data from Cloud Providers
        • AWS S3 Bucket
        • Azure Blob Storage
        • Google Cloud Storage
      • Import from Roboflow Universe
    • Manage Datasets
      • Dataset Batches
      • Search a Dataset
      • Set Dataset Classes
      • Add Tags to Images
      • Create an Annotation Attribute
      • Download an Image
      • Delete an Image
    • Dataset Versions
      • Create a Dataset Version
      • Preprocess Images
      • Augment Images
      • Delete a Version
      • Export a Dataset Version
    • Dataset Analytics
    • Merge Projects
    • Rename a Project
    • Delete a Project
    • Project Folders
    • Make a Project Public
  • Annotate
    • Introduction to Roboflow Annotate
    • Annotate an Image
      • Keyboard Shortcuts
      • Comment on an Image
      • Annotation History
      • Similarity Search
    • AI Labeling
      • Label Assist
      • Enhanced Smart Polygon with SAM
        • Smart Polygon (Legacy)
      • Box Prompting
      • Auto Label
    • Set Keypoint Skeletons
    • Annotate Keypoints
    • Annotate Multimodal Data
    • Collaborate on Labeling
    • Annotation Insights
  • Managed Labeling
  • Train
    • Train a Model
      • Train from a Universe Checkpoint
      • Train from Azure Vision
      • Train from Google Cloud
    • Roboflow Instant
    • Cancel a Training Job
    • Stop Training Early
    • View Training Results
    • View Trained Models
    • Evaluate Trained Models
  • Download a Dataset Version
  • Deploy
    • Deploy a Model or Workflow
    • Managed Deployments
    • Serverless Hosted API V2
      • Use in a Workflow
      • Use with the REST API
      • Run an Instant Model
    • Serverless Hosted API
      • Object Detection
      • Classification
      • Instance Segmentation
        • Semantic Segmentation
      • Keypoint Detection
      • Foundation Models
        • CLIP
        • OCR
        • YOLO-World
      • Video Inference
        • Use a Fine-Tuned Model
        • Use CLIP
        • Use Gaze Detection
        • API Reference
        • Video Inference JSON Output Format
      • Pre-Trained Model APIs
        • Blur People API
        • OCR API
        • Logistics API
        • Image Tagging API
        • People Detection API
        • Fish Detection API
        • Bird Detection API
        • PPE Detection API
        • Barcode Detection API
        • License Plate Detection API
        • Ceramic Defect Detection API
        • Metal Defect Detection API
    • Dedicated Deployments
      • Create a Dedicated Deployment
      • Make Requests to a Dedicated Deployment
      • Manage Dedicated Deployments with an API
    • Batch Processing
    • SDKs
      • Python inference-sdk
      • Web Browser
        • inferencejs Reference
        • inferencejs Requirements
      • Lens Studio
        • Changelog - Lens Studio
      • Luxonis OAK
    • Upload Custom Model Weights
    • Download Model Weights
    • Enterprise Deployment
      • License Server
      • Offline Mode
      • Kubernetes
      • Docker Compose
    • Monitor Deployed Models
      • Alerting
  • Universe
    • What is Roboflow Universe?
    • Find a Dataset on Universe
    • Explore Images in a Universe Dataset
    • Fork a Universe Dataset
    • Find a Model on Universe
    • Download a Universe Dataset
  • Set a Project Description
  • View Project Analytics
  • Support
    • Share a Workspace with Support
    • Delete Your Roboflow Account
    • Apply for Academic Credits
  • Billing
    • Premium Trial
    • Credits
      • View Credit Usage
      • Enable or Disable Flex Billing
      • Purchase Prepaid Credits
    • Plans
      • Purchase a Plan
      • Cancel a Plan
      • Update Billing Details
      • Update Payment Method
      • View Invoices
Powered by GitBook
On this page
  • Microsoft Azure Custom Vision Training Integration
  • Pre-requisites:
  • Setup: Adding Your Microsoft Azure API Keys to Roboflow
  • Training in Azure Custom Vision

Was this helpful?

  1. Train
  2. Train a Model

Train from Azure Vision

Train a model on Azure Vision and upload to Roboflow.

PreviousTrain from a Universe CheckpointNextTrain from Google Cloud

Last updated 8 days ago

Was this helpful?

This training option is only available on .

Microsoft Azure Custom Vision Training Integration

Once you've created a version of your dataset in Roboflow, you can export it directly to Microsoft Azure Custom Vision for training.

Pre-requisites:

A dataset version in Roboflow:

A Custom Vision project in Microsoft Azure:

Setup: Adding Your Microsoft Azure API Keys to Roboflow

1. Select your project name in Microsoft Azure

2. Select API Key under "1" in order to take you to this page:

We'll copy the keys from this page to your Roboflow Workspace.

3. Navigate to your Roboflow Workspace's API keys in settings by clicking the dropdown menu n the Workspace.

You'll see "API Keys" as a sub menu:

4. Copy KEY 1 from your Microsoft Azure account to the "training-key" in Roboflow

NOTE: For datasets larger than 1000 images, Azure will require S0 pricing tier.

5. Update the Endpoint field in Roboflow to match the Endpoint field from your Microsoft Custom Vision project.

From here, you're ready to start training with Roboflow and Microsoft Custom Azure together. Steps 1-5 only need to be completed once. To continue training with Azure, proceed.

Training in Azure Custom Vision

6. Once you've generated a dataset version, export the project as "Azure Custom Vision."

The project will automatically upload to your Azure account, and you'll be able to proceed with training there.

(Note: ensure you're logged into your Microsoft Azure account in the same browser as your Roboflow account.)

Your exported dataset version will appear directly in your Azure account.

Growth and Enterprise plans
Example generated dataset version in Roboflow
Example Custom Vision project in Microsoft Azure