config.py

#config.py 
#overall system manager

import os
import cv2

# Paths
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
MODEL_DIR = os.path.join(BASE_DIR, "models")
DATA_DIR = os.path.join(BASE_DIR, "data")
TEST_IMAGE_PATH = os.path.join(DATA_DIR, "finalTest", "image_016.jpg")
LENET_MODEL_PATH = os.path.join(MODEL_DIR, "lenet5_model.h5")
YOLO_MODEL_PATH = os.path.join(MODEL_DIR, "best.pt")
PROCESSED_IMAGES_DIR = os.path.join(DATA_DIR, "processed_images")
 
LICENSE_PLATE_CLASS_ID = 0
MINIBUS_CLASS_ID = 1

# YOLO Detection Settings
CONFIDENCE_THRESHOLD = 0.3  # Minimum confidence for YOLO detections
IOU_THRESHOLD = 0.4         # Intersection-over-Union threshold for YOLO

# Double-line Plates
DOUBLE_LINE_PLATES = True  # Enable or disable double-line plate handling

# Utility Functions

def save_results(segmented_characters, license_plate_number):
    """
    Save segmented characters and recognition results to the processed images directory.

    Args:
        segmented_characters (list): List of segmented character images.
        license_plate_number (str): Recognized license plate number.
    """
    os.makedirs(PROCESSED_IMAGES_DIR, exist_ok=True)

    # Save segmented characters
    for idx, char_img in enumerate(segmented_characters):
        char_path = os.path.join(PROCESSED_IMAGES_DIR, f"char_{idx + 1}.png")
        cv2.imwrite(char_path, char_img)

    # Atomic write with proper format
    temp_path = os.path.join(PROCESSED_IMAGES_DIR, "temp_result.txt")
    final_path = os.path.join(PROCESSED_IMAGES_DIR, "result.txt")
    
    try:
        with open(temp_path, "w", encoding="utf-8") as f:
            # Write in the expected format with prefix
            f.write(f"{license_plate_number}\n")
        
        # Atomic rename to prevent partial reads
        os.replace(temp_path, final_path)
    
    except Exception as e:
        if os.path.exists(temp_path):
            os.remove(temp_path)
        raise RuntimeError(f"Failed to save results: {str(e)}")