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  Semantic face parsing into 19 regions: skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, cloth, background. 512×512 input.
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  Core ML conversion of [zllrunning/face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch) for on-device inference on iPhone, iPad and Mac. Converted with `coremltools`; the packages are stateless, so all sequencing and buffering lives in your Swift code.
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  Semantic face parsing into 19 regions: skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, cloth, background. 512×512 input.
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+ <p><img src="https://huggingface.co/mlboydaisuke/Face-Parsing-CoreML/resolve/main/media/19082e4ae1.png" alt="Face Parsing demo" width="49%"> <img src="https://huggingface.co/mlboydaisuke/Face-Parsing-CoreML/resolve/main/media/4ca1b439ca.png" alt="Face Parsing demo" width="49%"></p>
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  Core ML conversion of [zllrunning/face-parsing.PyTorch](https://github.com/zllrunning/face-parsing.PyTorch) for on-device inference on iPhone, iPad and Mac. Converted with `coremltools`; the packages are stateless, so all sequencing and buffering lives in your Swift code.
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