汽车相关识别体验

import cv2
import pytesseract

# 加载预训练的车牌检测模型
plate_cascade = cv2.CascadeClassifier('path_to_haarcascade_russian_plate_number.xml')

def detect_and_recognize_plate(image_path):
    # 读取图像
    img = cv2.imread(image_path)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # 检测车牌
    plates = plate_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

    for (x, y, w, h) in plates:
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]

        # 使用Tesseract OCR识别车牌号码
        plate_number = pytesseract.image_to_string(roi_gray, config='--psm 7')
        print(f"Detected Plate Number: {plate_number}")

        # 绘制矩形框
        cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2)

    # 显示结果图像
    cv2.imshow('Plate Detection', img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

# 测试函数
detect_and_recognize_plate('path_to_test_image.jpg')