Learn how to use Custom Vision to build, deploy, and improve your own image classifiers and detect objects in images with Azure AI. Compare Custom Vision with Computer Vision and understand the differences between them.
You have built a solution that detects objects in images. You are using the same endpoint and key to predict as you used when you trained the model. What type of service are you using?
A. Cognitive Service
B. Computer Vision
C. Custom Vision
C. Custom Vision
The simplest approach is to use a general Cognitive Services resource for both training and prediction.
The correct answer is C. Custom Vision.
Custom Vision is a service that allows you to build, deploy, and improve your own image classifiers. You can use Custom Vision to detect objects in images by creating a custom model that is trained on your own data. You can then use the same endpoint and key to predict as you used when you trained the model. This means that you are using a custom vision prediction resource, which is a type of Azure Cognitive Services resource that enables you to use your custom models to get predictions from new images.
Cognitive Service is a general term that refers to a collection of AI services and cognitive APIs that enable developers to build intelligent applications. Computer Vision is a specific service within Cognitive Services that provides pre-trained models for analyzing and understanding images. You cannot use Computer Vision to detect objects in images with your own custom model, as it only supports the built-in models that are provided by the service.
Therefore, the best option for building a solution that detects objects in images with your own custom model is Custom Vision.
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