Recognize objects in ARKit with a Core ML model
WHAT IT TESTS: Combining ARKit, Vision, and Core ML plus 2D-to-3D mapping. OUTLINE: Pull the frame's capturedImage, run Vision/Core ML off the main thread, raycast the 2D detection point into the scene, add an ARAnchor.
WHAT IT TESTS: Whether you can architect a real-time ARKit plus ML pipeline and handle the 2D-to-3D leap. ANSWER OUTLINE: In the session delegate read ARFrame.capturedImage (a CVPixelBuffer), run a VNCoreMLRequest on a background queue so the 60fps render loop is not blocked, and apply the correct orientation. Map the 2D bounding-box center to a world position with raycasting (raycastQuery) against detected planes, then add an ARAnchor.
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- #ios
- #arkit
- #coreml
- #vision
- #augmented-reality
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