Hugging Face's logo

mlboydaisuke
/
Face-Parsing-CoreML

Image Segmentation
Core ML
core-ml
ios
macos
apple
on-device
face-parsing
semantic-segmentation
bisenet
arxiv:1808.00897
Model card Files
xet
 Community
Face-Parsing-CoreML / README.md
mlboydaisuke's picture
mlboydaisuke
Add README.md
bddfbbe verified
preview code
|
Raw
History Blame Contribute Delete
3.15 kB
metadata 
license: mit
library_name: coreml
pipeline_tag: image-segmentation
tags:
  - coreml
  - core-ml
  - ios
  - macos
  - apple
  - on-device
  - face-parsing
  - semantic-segmentation
  - bisenet
  - arxiv:1808.00897

Face Parsing — Core ML

Facial Segmentation, 2019

Semantic face parsing into 19 regions: skin, nose, eyes, eyebrows, ears, mouth, lip, hair, hat, eyeglass, earring, necklace, neck, cloth, background. 512×512 input.

Face Parsing demo Face Parsing demo

Core ML conversion of 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.

Task image segmentation
Upstream zllrunning/face-parsing.PyTorch
Packages 1
Download size 47 MB
Minimum iOS 17.0
Peak RAM ~300 MB

Files

File Size Compute units SHA-256
FaceParsing.mlpackage.zip 47 MB all a6dd498bb4e19df1…
Total 47 MB

compute_units is not a suggestion -- it is the configuration the conversion was verified against. Moving a package to a different compute unit can silently change the numerics (FP16 attention overflow) or crash on the GPU.

Download 

hf download mlboydaisuke/coreml-zoo --include "faceparsing/*" --local-dir ./face_parsing
unzip './face_parsing/faceparsing/*.zip' -d ./face_parsing

Use in Swift 

import CoreML

let config = MLModelConfiguration()
config.computeUnits = .all   // as converted — see the table above

// Unzip the .mlpackage, drop it into your Xcode target and Xcode compiles it
// at build time:
let model = try FaceParsing(configuration: config)

// ...or compile a downloaded .mlpackage at runtime:
let compiled = try await MLModel.compileModel(at: mlpackageURL)
let model = try MLModel(contentsOf: compiled, configuration: config)

Demo

  • Sample app — CoreML-Face-Parsing, a standalone iOS project.
  • Models Zoo — this model is downloadable and runnable inside the Models Zoo app on the App Store, no build required.

Conversion

License

The conversion inherits the upstream license: MIT.

Credits