Depth Estimation sample Apps for iOS and macOS, using the FCRN-DepthPrediction models Apple provided on their model page.
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Loads an image and crops it to the input size requested by the FCRN model
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The same helper class ImagePlatform provides hardware accelerated processing tools for both iOS and macOS images and buffers
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Supports both FCRN-16 and FCRN-32 models
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You can post the predicted cropped portrait photo to Facebook as a 3D photo directly from your iPhone
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You can also post the cropped predicted depthmap together with the cropped input image photo to Facebook as a 3D photo directly using a browser on your Mac or PC. See this guide for more information.
You can download FCRN-DepthPrediction CoreML models from https://developer.apple.com/machine-learning/models/
You can download just one of them, both work with this project. Choose which one to use by setting the relevant build target in Xcode
FCRN.mlmodel Storing model weights using full precision (32 bit) floating points numbers. 254.7MB https://docs-assets.developer.apple.com/coreml/models/Image/DepthEstimation/FCRN/FCRN.mlmodel
FCRNFP16.mlmodel Storing model weights using half-precision (16 bit) floating points numbers. 127.3MB https://docs-assets.developer.apple.com/coreml/models/Image/DepthEstimation/FCRN/FCRNFP16.mlmodel