雑谈2017
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This document discusses several core technologies for augmented reality development including ARKit, SceneKit, SpriteKit, and Metal. It covers capturing video and motion data, world tracking to determine position and orientation, plane detection and scene understanding, and optimized rendering using hardware acceleration. Key features covered include frame updating, hit testing, light estimation, and model deployment for tasks like image classification, style transfer, and language processing.
雑谈2017
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- 9. AVFoundation CoreMotion Capturing ARKit Rendering Application SceneKit SpriteKit Metal Processing ARKit ARSessionConfiguration ARFrame ARFrame ARFrame AVCaptureSession CMMotionManager run(_ configuration) currentFrame ARSession World Tracking Position and orientation Physical distances Relative to starting position 3D-feature points 1m
- 10. Scene Understanding Plane detection Hit-testing Light estimation Plane Detection Horizontal with respect to gravity Runs over multiple frames Aligned extent for surface Plane merging Existing plane using extent Existing plane Estimated plane Hit-Test Types Light Estimation Ambient intensity based on captured image Defaults to 1000 lumen Enabled by default configuration.isLightEstimationEnabled = true // Get ambient intensity value let intensity = frame.lightEstimate?.ambientIntensity
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- 20. Optimized for Hardware Dog playing in a soccer field Context Switching Runs on GPU Runs on CPU Today’s lunch was terrible and disappointing Word Counts Use NLP to Process Text { "Core" : 1, "ML" : 1, "is" : 1, "awesome" : 1, "I" : 1, "love" : 1, "using" : 1, "it" : 1, } Xcode Your App Model as CodeGetting the Model Model Function learned from data Observed inputs Predicts outputs ?Model photo: flowerType: Underlying Function Scene Classification Style TransferTranslation Sentiment Analysis Handwriting Recognition Music Tagging Predicting Text !That was totally ? awesome Leo! I love you mom ??? ?? 7 Do you know the way to San Jose Beach Rock