Object Detection in Azure Machine Learning vs Azure Custom Vision Studio

Ziggy Zulueta 490 Reputation points MVP
2024-02-04T01:01:20.28+00:00

Azure provides object detection in both Azure Machine Learning https://video2.skills-academy.com/en-us/azure/machine-learning/tutorial-auto-train-image-models?view=azureml-api-2&tabs=cli and Azure Computer Vision Studio https://video2.skills-academy.com/en-us/azure/ai-services/custom-vision-service/get-started-build-detector. What is the difference between the two, which has better results, what are the pros and cons of using each?

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
2,690 questions
Azure Computer Vision
Azure Computer Vision
An Azure artificial intelligence service that analyzes content in images and video.
338 questions
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  1. VasaviLankipalle-MSFT 15,836 Reputation points
    2024-02-05T20:36:13.52+00:00

    Hello @Ziggy Zulueta , Thanks for using Microsoft Q&A Platform.

    Azure Custom Vision provides a user-friendly interface for training and deploying object detection models, and it requires minimal coding or machine learning expertise. You can build an object detector simply with the Custom Vision website.

    However, AutoML models for vision tasks is supported via the Azure Machine Learning Python SDK. With this capability, you can seamlessly integrate with the Azure Machine Learning data labeling, use labeled data for generating image models, optimize model performance by specifying the model algorithm and tuning the hyperparameters, download or deploy the resulting model as a web service in Azure Machine Learning, and operationalize at scale, leveraging Azure Machine Learning MLOps and ML Pipelines capabilities.

    Overall, both Azure Machine Learning and Azure Custom Vision are available tools for object detection, and the choice between the two depends on your specific needs and expertise. If you prefer customization/tuning over the object detection models, Azure Machine Learning may be a better choice.

    I hope this helps.

    Regards,

    Vasavi

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