Your company manufactures widgets. You have 1,000 digital photos of the widgets. You need to identify the location of the widgets within the photos. What should you use?

Computer Vision Spatial Analysis is typically used for analyzing people's movement and presence in a physical space, not for locating specific objects like widgets in static images.

Custom Vision object detection allows training a model to identify specific objects (widgets) and their bounding box locations within images using your own dataset. This is ideal for finding custom items like manufactured widgets in a collection of photos.

Computer Vision Image Analysis provides general insights like tags, descriptions, and categories for an image, but it does not specifically locate custom objects within the image.

Custom Vision classification assigns a single label to an entire image (e.g., "widget photo" or "not widget photo"), rather than identifying and locating multiple specific objects within an image.