jerhoads/cloth-segmentation-coreml

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.