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---
base_model:
- Ultralytics/YOLO11
pipeline_tag: object-detection
library_name: ultralytics
metrics:
- mAP50
- mAP50-95
- accuracy50
- precision
- recall
- f1
model-index:
- name: MacPaw/yolov11l-ui-elements-detection
results:
- task:
type: object-detection
metrics:
- type: accuracy
value: 0.65359
name: accuracy@0.5
- task:
type: object-detection
metrics:
- type: precision
value: 0.49055
name: precision
- task:
type: object-detection
metrics:
- type: recall
value: 0.43433
name: recall
- task:
type: object-detection
metrics:
- type: f1
value: 0.43776
name: f1
- task:
type: object-detection
metrics:
- type: map
value: 0.46644
name: mAP@0.5
- task:
type: object-detection
metrics:
- type: map
value: 0.31295
name: mAP@0.5-0.95
datasets:
- MacPaw/Screen2AX-Element
license: agpl-3.0
---
# 🔍 YOLOv11l — UI Elements Detection
This model is a fine-tuned version of [`Ultralytics/YOLO11`](https://huggingface.co/Ultralytics/YOLO11), trained to detect **UI elements** in macOS application screenshots.
It is part of the **Screen2AX** project — a research effort focused on generating accessibility metadata using computer vision.
---
## 🧠 Task Overview
- **Task:** Object Detection
- **Target:** Individual UI elements
- **Supported Labels:**
```
['AXButton', 'AXDisclosureTriangle', 'AXImage', 'AXLink', 'AXTextArea']
```
This model detects common interactive components typically surfaced in accessibility trees on macOS.
---
## 🗂 Dataset
- Training data: [`MacPaw/Screen2AX-Element`](https://huggingface.co/datasets/MacPaw/Screen2AX-Element)
---
## 🚀 How to Use
### 🔧 Install Dependencies
```bash
pip install huggingface_hub ultralytics
```
### 🧪 Load the Model and Run Predictions
```python
from huggingface_hub import hf_hub_download
from ultralytics import YOLO
# Download the model
model_path = hf_hub_download(
repo_id="MacPaw/yolov11l-ui-elements-detection",
filename="ui-elements-detection.pt",
)
# Load and run prediction
model = YOLO(model_path)
results = model.predict("/path/to/your/image")
# Display result
results[0].show()
```
---
## 📜 License
This model is licensed under the **GNU Affero General Public License v3.0 (AGPL-3.0)**, as inherited from the original YOLOv11 base model.
---
## 🔗 Related Projects
- [Screen2AX Project](https://github.com/MacPaw/Screen2AX)
- [Screen2AX HuggingFace Collection](https://huggingface.co/collections/MacPaw/screen2ax-687dfe564d50f163020378b8)
- [YOLOv11l — UI Groups Detection](https://huggingface.co/MacPaw/yolov11l-ui-groups-detection)
---
## ✍️ Citation
If you use this model in your research, please cite the Screen2AX paper:
```bibtex
@misc{muryn2025screen2axvisionbasedapproachautomatic,
title={Screen2AX: Vision-Based Approach for Automatic macOS Accessibility Generation},
author={Viktor Muryn and Marta Sumyk and Mariya Hirna and Sofiya Garkot and Maksym Shamrai},
year={2025},
eprint={2507.16704},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2507.16704},
}
```
---
## 🌐 MacPaw Research
Learn more at [https://research.macpaw.com](https://research.macpaw.com) |