Update README.md

README.md

@@ -1,3 +1,36 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- Ultralytics/YOLO11
+pipeline_tag: object-detection
+---
+
+## YOLOv11-Face-Detection
+
+A lightweight face detection model based on YOLO architecture ([YOLOv11 nano](https://huggingface.co/Ultralytics/YOLO11)), trained for 225 epochs on the WIDERFACE dataset.
+
+It achieves the following results on the evaluation set:
+![Yolov11n results](https://huggingface.co/AdamCodd/YOLOv11-face-detection/resolve/main/result.png)
+
+[Confusion matrix](https://huggingface.co/AdamCodd/YOLOv11-face-detection/blob/main/confusion-matrix.png):
+
+[[23577 2878]
+
+[16098 0]]
+
+### Usage
+```python
+from huggingface_hub import hf_hub_download
+from ultralytics import YOLO
+
+model_path = hf_hub_download(repo_id="AdamCodd/YOLOv11-face-detection", filename="model.pt")
+model = YOLO(model_path)
+
+results = model.predict("/path/to/your/image", save=True) # saves the result in runs/detect/predict
+```
+
+### Limitations
+
+- Performance may vary in extreme lighting conditions
+- Best suited for frontal and slightly angled faces
+- Optimal performance for faces occupying >20 pixels