Cloth Segmentation — Core ML (U²-Net)
On-device clothing segmentation for iOS, converted to Core ML. Segments a person's
clothing into upper-body, lower-body, and full-body (dress) + background.
- Input: RGB image, 768×768 (Core ML
ImageType; normalization baked in).
- Output:
probs — softmax probabilities, shape (1, 4, 768, 768), channels = [background, upper, lower, full].
- Format: FP16 mlprogram, ~84 MB.
ClothSegmentation.mlpackage.zip (download + unzip + compile on device).
Provenance & License
- Architecture: U²-Net (Xuebin Qin et al.) — Apache-2.0.
- Model/code: levindabhi/cloth-segmentation — MIT.
- Weights trained on iMaterialist (Fashion) 2019 @ FGVC6 (competition dataset).
- Checkpoint mirror:
maiti/cloth-segmentation (cloth_segm_u2net_latest.pth).
- Converted with the included
convert.py (PyTorch 2.2 → coremltools 8.3).
Used by Chromaform (chromaform.art) for its Clothing Recolor tool.
