trainImage.py

import os
import cv2
import numpy as np
from PIL import Image

def TrainImages():
    print("Training images...")
    
    # Define the paths
    trainimage_path = "TrainingImage"
    image_paths = [os.path.join(trainimage_path, f) for f in os.listdir(trainimage_path) if f.endswith(".jpg")]
    
    faces = []
    labels = []

    for image_path in image_paths:
        img = Image.open(image_path).convert("L")  # Convert to grayscale
        img_np = np.array(img)
        enrollment = int(image_path.split('.')[1])
        faces.append(img_np)
        labels.append(enrollment)

    # Train the model
    recognizer = cv2.face.LBPHFaceRecognizer_create()
    recognizer.train(faces, np.array(labels))
    
    # Save the model
    recognizer.save("trainer.yml")
    print("Training complete.")