How can a computer vision team improve collaboration?
Empower computer vision teams to organize data chaos & supercharge collaboration.
Increase AI team time spent on hight-value tasks by +33% to unleash collective intelligence.
Rely on the right development backbone.
Increase research velocity.
Build, deploy, and improve high-performing CV models at scale.
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How can Computer Vision Help Your Business?
Get Real-Time Actionable Data.
Automate Processes.
Increase Revenue.
Labor shortages, safety issues, and lack of data (about inventory, customers, and business operations) are costing you money.
Computer vision is the solution.
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How do I generate a responsible AI vision dashboard?
You can generate a Responsible AI vision dashboard via an Azure Machine Learning pipeline job by using Responsible AI components.
Locate and identify the class of multiple objects for a given image.
An object is defined with a bounding box.
Responsible AI vision insights is currently in public preview.
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Integration with AutoML Image
Automated ML in Azure Machine Learning supports model training for computer vision tasks like image classification and object detection.
To debug AutoML vision models and explain model predictions, AutoML models for computer vision are integrated with Responsible AI dashboard.
To generate Responsible AI insights for AutoML computer vision models, register your best AutoML model in the Azure Machine Learning workspace and run it through the Responsible AI vision insights pipeline.
To learn, see how to set up AutoML to train computer vision models.
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Limitations
•All models must be registered in Azure Machine Learning in MLflow format and with a PyTorch flavor.
HuggingFace models are also supported.
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Overview
APPLIES TO: Azure CLI ml extension v2 (current) Python SDK azure-ai-ml v2 (current)
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Responsible AI component
The core component for constructing the Responsible AI image dashboard in Azure Machine Learning is the RAI Vision Insights component, which differs from how to construct the Responsible AI dashboard for tabular data.
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Responsible AI vision insights
The Responsible AI vision insights component has three major input ports:
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Understand the Responsible AI image dashboard
To learn more about how to use the Responsible AI image dashboard, see Responsible AI image dashboard in Azure Machine Learning studio.
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What are the benefits of a computer vision dashboard?
There is no one-size-fits-all.
Create and optimize interactive dashboards for your own vision system.
Dashboards help to catch and solve problems efficiently.
Alerts and notifications help to find issues even faster.
Real-time dashboard to monitor collected data of your computer vision applications.
Integrated Edge-to-Cloud data synchronization.
