README.md

metadata

license: apache-2.0
base_model:
  - Ultralytics/YOLO11
pipeline_tag: object-detection
tags:
  - pytorch

YOLOv11x-Face-Detection

A lightweight face detection model based on YOLO architecture (YOLOv11 xlarge), trained for 100 epochs on the WIDERFACE dataset. It's way more accurate than my YOLOv11n model, but slower.

It achieves the following results on the evaluation set:

==================== Results ====================
Easy   Val AP: 0.9629194049702874
Medium Val AP: 0.9519172409689101
Hard   Val AP: 0.8800338681974709
=================================================

YOLO results:

Confusion matrix:

[[27338 3110]

[12337 0]]

Usage

from huggingface_hub import hf_hub_download
from ultralytics import YOLO

model_path = hf_hub_download(repo_id="AdamCodd/YOLOv11x-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