YOLOv11 Sign Language Detection

This project uses a custom-trained YOLOv11 model with 40 classes to detect hand signs for sign language recognition. The project employs OpenCV for real-time inference through webcam feed.

Requirements

Python 3.x
OpenCV
PyTorch
Ultralytics YOLO (for ONNX model support)

Installation

Clone the repository:

git clone https://github.com/alihassanml/Yolo11-sign-language-detection.git
cd Yolo11-sign-language-detection

Install dependencies:
```
pip install -r requirements.txt
```
Ensure that best.onnx (the trained model) is in the project directory.

Code Usage

Use the following code to run real-time sign language detection from your webcam:

from ultralytics import YOLO
import cv2

model = YOLO('best.onnx')
cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        print("Failed to grab frame.")
        break  

    results = model(frame)
    result = results[0]

    annotated_frame = result.plot() 
    cv2.imshow('YOLO Inference', annotated_frame)
    
    if cv2.waitKey(1) == 27:
        break

cap.release()
cv2.destroyAllWindows()

Run the Project

Run the script with:

python sign_language_detection.py

Repository Link