Object detection is a form of computer vision in which a model is trained to detect the presence and location of one or more classes of object in an image.
There are two components to an object detection prediction:
- The class label of each object detected in the image. For example, you might ascertain that an image contains an apple, an orange, and a banana.
- The location of each object within the image, indicated as coordinates of a bounding box that encloses the object.
To train an object detection model, you can use the Azure AI Custom Vision portal to upload and label images before training, evaluating, testing, and publishing the model; or you can use the REST API or a language-specific SDK to write code that performs the training tasks.
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