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Once you've annotated your dataset, you can [train](/data-ai/train/train-tflite/) an ML model to make inferences.
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### Detect objects with bounding boxes
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### Label objects within an image
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Object detection identifies and determines the location of certain objects in an image.
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For example, object detection could help you identify:
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- how many `pizza` objects appear on a counter
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- the number of `bicycle` and `pedestrian` objects on a greenway
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- which `plant` objects are popular with `deer` in your garden
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To create a training set for object detection, annotate bounding boxes to teach your model to identify objects that you want to detect in future images.
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Use labels to add metadata about objects within an image, for example by drawing bounding boxes around each bicycle in a street scene and adding the bicycle label.
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