Update README.md

README.md

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----
-license: agpl-3.0
----
+---
+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: [email protected]
+  - 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: [email protected]
+  - task:
+      type: object-detection
+    metrics:
+    - type: map
+      value: 0.31295
+      name: [email protected]
+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
+...
+```
+
+---
+
+## 🌐 MacPaw Research
+
+Learn more at [https://research.macpaw.com](https://research.macpaw.com)