车牌识别python代码

以下是一个基于Python和OpenCV的简单车牌识别代码示例：

import cv2
import numpy as np

def preprocess(image):
    # 图像预处理，包括缩放、灰度化、去噪声等
    resized = cv2.resize(image, (640, 480))
    gray = cv2.cvtColor(resized, cv2.COLOR_BGR2GRAY)
    blurred = cv2.GaussianBlur(gray, (5, 5), 0)
    thresh = cv2.adaptiveThreshold(blurred, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 2)
    return thresh

def find_contours(image):
    # 寻找图像中的轮廓
    contours, _ = cv2.findContours(image.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    return contours

def find_license_plate(contours):
    # 根据轮廓，寻找可能的车牌区域
    for contour in contours:
        perimeter = cv2.arcLength(contour, True)
        approx = cv2.approxPolyDP(contour, 0.02 * perimeter, True)
        if len(approx) == 4:
            x, y, w, h = cv2.boundingRect(approx)
            aspect_ratio = w / float(h)
            if 2.5 < aspect_ratio < 4.5:
                return x, y, w, h

def recognize_license_plate(image, x, y, w, h):
    # 车牌字符识别
    plate_roi = image[y:y+h, x:x+w]
    plate_gray = cv2.cvtColor(plate_roi, cv2.COLOR_BGR2GRAY)
    _, plate_thresh = cv2.threshold(plate_gray, 0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
    plate_text = pytesseract.image_to_string(plate_thresh, config='--psm 7')
    return plate_text

# 加载车牌识别模型
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

# 读取图像
image = cv2.imread('car_plate.jpg')

# 图像预处理
preprocessed = preprocess(image)

# 寻找轮廓
contours = find_contours(preprocessed)

# 寻找车牌区域
plate_coords = find_license_plate(contours)
if plate_coords is not None:
    x, y, w, h = plate_coords

    # 车牌字符识别
    plate_text = recognize_license_plate(image, x, y, w, h)
    print("识别结果：", plate_text)
else:
    print("未找到车牌区域")

注意，这只是一个简单的示例代码，实际的车牌识别需要更多的优化和处理，以适应不同的场景和条件。此外，代码中使用了Tesseract OCR库进行字符识别，需要先安装Tesseract OCR并配置正确的路径。