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  pexel End-to-End Number Plate Detection and Recognition using YOLO Application Flow: Image Capture: Acquire an image of a vehicle. Image Preprocessing: Resize and normalize the image. Number Plate Detection: Use YOLOv3 (or YOLOv4/v5) to locate the number plate region. Number Plate Extraction: Crop the detected region from the original image. Image Enhancement: Improve the quality of the extracted image (e.g., thresholding, edge detection). OCR: Use Tesseract-OCR to recognize text from the enhanced image. Number Plate Recognition: Validate and format the extracted text. Implementation Details: YOLO Model: Use a pre-trained YOLO model and fine-tune it on a dataset of number plate images. OCR Library: Employ Tesseract-OCR with a custom-trained model for number plate fonts. Programming Language: Python is a popular choice, with libraries like OpenCV, NumPy, and PyTesseract. Example Code Snippet (Python): Python import cv2 import numpy as np import pytesserac...