The correct option is 5 labeled images.

Most managed AutoML vision services require a small minimum number of examples per class to begin training. Starting with the required number lets the model form initial patterns and you can improve accuracy as you add more diverse labeled images.

15 labeled images is incorrect because it specifies a larger minimum than the documented threshold and you do not need that many to start training.

1 labeled image is incorrect because a single example does not provide sufficient variation for the model to learn class features.

30 labeled images is incorrect because it overestimates the documented minimum and is not the smallest required to begin training.

3 labeled images is incorrect because three examples remain below the service threshold and will not meet the minimum needed to create a usable dataset.

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