| license: agpl-3.0 | |
| library_name: mlx | |
| tags: | |
| - mlx | |
| - yolo | |
| - yolo11 | |
| - omniparser | |
| - object-detection | |
| - apple-silicon | |
| pipeline_tag: object-detection | |
| # OmniParser icon_detect — MLX (YOLO11) | |
| **MLX weights of [microsoft/OmniParser-v2.0](https://huggingface.co/microsoft/OmniParser-v2.0)'s `icon_detect`** — a YOLO11m fine-tuned on 67K screenshots to detect interactive UI elements. Runs on Apple Silicon with **no PyTorch / no ultralytics at inference**. | |
| ## ⚠️ License: AGPL-3.0 | |
| This model derives from **Ultralytics YOLO11**, which is **AGPL-3.0** (strong copyleft). This repo is therefore licensed **AGPL-3.0** — see `LICENSE`. If you build a network service on top of it, AGPL §13 requires you to offer users the corresponding source. For a commercial/proprietary product, consider an [Ultralytics Enterprise License](https://www.ultralytics.com/license) instead. | |
| ## Provenance (corresponding source) | |
| - Original detector: microsoft/OmniParser-v2.0 `icon_detect/model.pt` (AGPL-3.0, Ultralytics YOLO11m). | |
| - MLX conversion format + inference code: [yolo11-mlx](https://github.com/walter-grace/yolo11-mlx). | |
| - `omniparser_mlx.json`: `nc=1`, class `icon`. | |
| ## Usage | |
| ```python | |
| from yolo11_mlx import YOLO11 # pip install from github.com/walter-grace/yolo11-mlx | |
| model = YOLO11("omniparser_mlx.npz") | |
| boxes = model.predict("screenshot.png", conf=0.05, iou=0.5)[0].boxes.xyxy | |
| ``` | |