---
license: mit
tags:
  - coreml
  - image-segmentation
  - cloth-segmentation
---

# 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.