Learn how to generate predictions for your object detection solution using the prediction endpoint of the Custom Vision service in Azure. Find out the difference between the prediction endpoint and the training endpoint, and how to use them correctly.
You created a solution the makes use of object detection. You deployed two separate resources in Azure -one that manages the training of the model, and one that manages the predictions. To which endpoint should you make calls to generate predictions?
A. Training endpoint
B. Prediction endpoint
C. Any endpoint (prediction or training), both will work
B. Prediction endpoint
To generate predictions, it must be used the HTTP address of the endpoint for the prediction resource to which you published the model.
The correct answer is B. Prediction endpoint.
Object detection is a type of computer vision task that involves identifying and locating objects in an image or video. To create a solution that makes use of object detection, you need to train a model that can learn from labeled data and generate predictions for new data.
In Azure, you can use the Custom Vision service to create and manage object detection models. The Custom Vision service provides two types of resources: a training resource and a prediction resource. The training resource is used to train the model using your own data, while the prediction resource is used to generate predictions using the trained model.
To generate predictions, you need to make calls to the prediction endpoint of the Custom Vision service. The prediction endpoint is a REST API that accepts an image or video as input and returns a JSON response with the detected objects and their coordinates. The prediction endpoint is different from the training endpoint, which is used to create, update, and delete projects, tags, and images.
Therefore, to generate predictions for your object detection solution, you should make calls to the prediction endpoint of the Custom Vision service, not the training endpoint.
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