帮我以python写一个用opencv的停车车牌识别的程序

好的，这个问题我可以回答。以下是一个简单的用Python和OpenCV实现的停车车牌识别程序：

import cv2

# 载入模型
net = cv2.dnn.readNet('yolo-voc.weights', 'yolo-voc.cfg')

# 读取图像并进行预处理
img = cv2.imread('car.jpg')
blob = cv2.dnn.blobFromImage(img, scalefactor=1/255, size=(416, 416), mean=(0,0,0), swapRB=True, crop=False)

# 将输入数据传入模型进行预测
net.setInput(blob)
out_layer_names = net.getUnconnectedOutLayersNames()
outs = net.forward(out_layer_names)

# 解析预测结果并作出判断
class_ids = []
confidences = []
boxes = []
for out in outs:
    for detection in out:
        scores = detection[5:]
        class_id = np.argmax(scores)
        confidence = scores[class_id]
        if confidence > 0.5 and class_id == 2:
            center_x = int(detection[0] * img.shape[1])
            center_y = int(detection[1] * img.shape[0])
            w = int(detection[2] * img.shape[1])
            h = int(detection[3] * img.shape[0])
            x1 = int(center_x - w/2)
            y1 = int(center_y - h/2)
            class_ids.append(class_id)
            confidences.append(float(confidence))
            boxes.append([x1, y1, w, h])
            
# 显示结果图像
indices = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
for i in indices:
    i = i[0]
    box = boxes[i]
    x,y,w,h = box
    cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)
    
cv2.imshow("car plate detection", img)
cv2.waitKey(0)

cv2.destroyAllWindows()

这段代码可实现从图像中识别出停车车牌的位置，并在图像上用矩形框标注出来。识别算法采用了YOLO v2算法，训练数据采用的是VOC格式的数据集。你需要下载正确的权重文件及配置文件，才能运行此代码。