ariakang/YOLOv11n-face-detection
By ariakang · ↓ 7 · ♥ 4 · Updated 2025-02-07
What's in this repo
This page lists the files in ariakang/YOLOv11n-face-detection, including model.onnx.
- 1 ONNX models (.onnx files)
- 10 files, including 5 .png, 1 .md, 1 .json, 1 .onnx, 1 .pt
- Last updated 2025-02-07
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
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:
==================== Results ====================
Easy Val AP: 0.9420471677096086
Medium Val AP: 0.9210357271019756
Hard Val AP: 0.8099848364072022
=================================================
YOLO results:
[[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
Model info
onnx
pytorch
object-detection
base_model:Ultralytics/YOLO11
base_model:quantized:Ultralytics/YOLO11
license:apache-2.0
region:us
↓ 7
♥ 4
Created: 2025-02-07
Updated: 2025-02-07
View on Hugging FaceFiles (10)
.gitattributes
Precision-confidence.png
Precision-recall.png
README.md
Recall-confidence.png
config.json
confusion-matrix.png
model.onnx
ONNX
model.pt
result.png