Run a Core ML image model with Vision
WHAT IT TESTS: Wiring Core ML into Vision for image inference. OUTLINE: Add the .mlmodel so Xcode generates a class, wrap it in a VNCoreMLModel, run a VNCoreMLRequest via a VNImageRequestHandler, read results off the main queue.
WHAT IT TESTS: Whether you know the Vision plus Core ML pipeline for images. ANSWER OUTLINE: Drag the .mlmodel into Xcode, which auto-generates a Swift class. Wrap it with VNCoreMLModel, build a VNCoreMLRequest with a completion handler, and run it through a VNImageRequestHandler created from the image's CGImage or CIImage. Vision handles scaling and color conversion per imageCropAndScaleOption. Read VNClassificationObservation results, then hop to the main queue for UI.
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- #ios
- #coreml
- #vision
- #machine-learning
- #image
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