YOLOv11n-Face-Detection

A lightweight face detection model based on YOLO architecture (YOLOv11 nano), trained for 225 epochs on the WIDERFACE dataset.

It achieves the following results on the evaluation set: Yolov11n results

Confusion matrix:

[[23577 2878]

[16098 0]]

Usage

from huggingface_hub import hf_hub_download
from ultralytics import YOLO

model_path = hf_hub_download(repo_id="AdamCodd/YOLOv11n-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
Downloads last month
0
Inference Examples
Unable to determine this model's library. Check the docs .

Model tree for AdamCodd/YOLOv11n-face-detection

Base model

Ultralytics/YOLO11
Quantized
(8)
this model

Collection including AdamCodd/YOLOv11n-face-detection