类型错误：预期的 Ptr<cv::umat> 对于参数“%s”</cv::umat>

Question

我有这个我自己无法解决的错误。

你能告诉我如何解决吗？

问题出在这个 function 中：

import numpy as np
import cv2
import matplotlib.pyplot as plt

def histogram_of_pixel_projection(img):

    # list that will contains all digits
    caracrter_list_image = list()

    # img = crop(img)

    # Add black border to the image
    BLACK = [0, 0, 0]
    #img = cv2.copyMakeBorder(img, 3, 3, 3, 3, cv2.BORDER_CONSTANT, value=BLACK)
    img = cv2.copyMakeBorder(img, 10, 10, 10, 10, cv2.BORDER_CONSTANT) 

    # change to gray
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Change to numpy array format
    nb = np.array(gray)

    # Binarization
    nb[nb > 120] = 255
    nb[nb < 120] = 0

    # compute the sommation
    x_sum = cv2.reduce(nb, 0, cv2.REDUCE_SUM, dtype=cv2.CV_32S)
    y_sum = cv2.reduce(nb, 1, cv2.REDUCE_SUM, dtype=cv2.CV_32S)

    # rotate the vector x_sum
    x_sum = x_sum.transpose()

    # get height and weight
    x = gray.shape[1]
    y = gray.shape[0]

    # division the result by height and weight
    x_sum = x_sum / y
    y_sum = y_sum / x

    # x_arr and y_arr are two vector weight and height to plot histogram projection properly
    x_arr = np.arange(x)
    y_arr = np.arange(y)

    # convert x_sum to numpy array
    z = np.array(x_sum)

    # convert y_arr to numpy array
    w = np.array(y_sum)

    # convert to zero small details
    z[z < 15] = 0
    z[z > 15] = 1

    # convert to zero small details and 1 for needed details
    w[w < 20] = 0
    w[w > 20] = 1

    # vertical segmentation
    test = z.transpose() * nb

    # horizontal segmentation
    test = w * test

    # plot histogram projection result using pyplot
    horizontal = plt.plot(w, y_arr)
    vertical = plt.plot(x_arr ,z)

    plt.show(horizontal)
    plt.show(vertical)

    f = 0
    ff = z[0]
    t1 = list()
    t2 = list()
    for i in range(z.size):
        if z[i] != ff:
            f += 1
            ff = z[i]
            t1.append(i)
    rect_h = np.array(t1)

    f = 0
    ff = w[0]
    for i in range(w.size):
        if w[i] != ff:
            f += 1
            ff = w[i]
            t2.append(i)
    rect_v = np.array(t2)

    # take the appropriate height
    rectv = []
    rectv.append(rect_v[0])
    rectv.append(rect_v[1])
    max = int(rect_v[1]) - int(rect_v[0])
    for i in range(len(rect_v) - 1):
        diff2 = int(rect_v[i + 1]) - int(rect_v[i])

        if diff2 > max:
            rectv[0] = rect_v[i]
            rectv[1] = rect_v[i + 1]
            max = diff2

    # extract caracter
    for i in range(len(rect_h) - 1):

        # eliminate slice that can't be a digit, a digit must have width bigger then 8
        diff1 = int(rect_h[i + 1]) - int(rect_h[i])

        if (diff1 > 5) and (z[rect_h[i]] == 1):
            # cutting nb (image) and adding each slice to the list caracrter_list_image
            caracrter_list_image.append(nb[int(rectv[0]):int(rectv[1]), rect_h[i]:rect_h[i + 1]])

            # draw rectangle on digits
            cv2.rectangle(img, (rect_h[i], rectv[0]), (rect_h[i + 1], rectv[1]), (0, 255, 0), 1)

    # Show segmentation result
    image = plt.imshow(img)
    plt.show(image)

    return caracrter_list_image

img='00.PNG'
histogram_of_pixel_projection(img)

该代码应该拍摄图像，然后执行以下操作：

• 为图像添加黑色边框
• 变为灰色
• 更改为 numpy 数组格式
• ...

当我运行代码时，我收到以下错误：

    ---------------------------------------------------------------------------
    TypeError                                 Traceback (most recent call last)
    
    <ipython-input-17-eb57438d5985> in <module>()
        184 img='00.PNG'
    
    --> 185 histogram_of_pixel_projection(img)
    
    
    <ipython-input-17-eb57438d5985> in histogram_of_pixel_projection(img)
    
         72     BLACK = [0, 0, 0]
    
         73     #img = cv2.copyMakeBorder(img, 3, 3, 3, 3, cv2.BORDER_CONSTANT, value=BLACK)
    
    ---> 74     img = cv2.copyMakeBorder(img, 10, 10, 10, 10, cv2.BORDER_CONSTANT)
    
         75 
    
         76     # change to gray
    
    
    TypeError: Expected Ptr<cv::UMat> for argument '%s'

---

编辑：我添加了运行代码所需的导入。

注意：要能够import cv2 ，您需要pip install opencv-python

Answer 1

＃代码

**从 sklearn.preprocessing 导入 LabelEncoder 从 keras.models 导入 model_from_json 导入 numpy 作为 np

加载 model 架构、重量和标签

json_file = open('Caracter_Recognition_Train_Model/MobileNets_character_recognition.json', 'r') loaded_model_json = json_file.read() json_file.close()

model = model_from_json(loaded_model_json)# Load the digit prediction model model.load_weights("Caracter_Recognition_Train_Model/License_character_recognition.h5") print("[INFO] Model loaded successfully...")

labels = LabelEncoder() labels.classes_ = np.load('Caracter_Recognition_Train_Model/license_character_classes.npy') print("[INFO] 标签加载成功...") **

＃错误

** Traceback（最近一次调用最后）：文件“C:/Users/Mahdia/PycharmProjects/ ProjetFinale _/Caracter_Recognition_Avc_Modele.py”，第 1 行，从 sklearn.preprocessing 导入 LabelEncoder 文件“C:\Users\Mahdia\PycharmProjects_ ProjetFinale __\venv\lib\site-packages\sklearn_ init _.py”，第 82 行，在 from.base 导入克隆文件“C:\Users\Mahdia\ PycharmProjects_ProjetFinale __\venv\lib\site-packages\sklearn\base .py”，第 17 行，从.utils 导入IS_32BIT 文件“C:\Users\Mahdia\PycharmProjects_ ProjetFinale _\venv\lib\site-packages\sklearn\ utils_init _.py”，第 20 行，来自 scipy。稀疏导入 issparse 文件“C:\Users\Mahdia\ PycharmProjects_ProjetFinale __\venv\lib\site-packages\scipy_init _.py ”，第 130 行，来自。 在WinDLL (os.path.abspath(filename)) 文件“C:\Program Files \WindowsApps\PythonSoftwareFoundation.Python.3.7_3.7.2544.0_x64__qbz5n2kfra8p0\lib\ctypes_ init _.py"，第 364 行，在init self._handle = _dlopen(self._name, mode) OSError: [Winéest 1666 模块可打扰的**

Answer 2

当它应该是一个数组图像时，您正在发送一个字符串变量，请使用以下内容：

img = cv2.imread('00.PNG') 
histogram_of_pixel_projection(img)