错误“NoneType”对象没有属性“\uu getitem\uuu”有什么问题

Question

当我运行这个代码时

import numpy as np
import cv2

from sklearn.datasets import fetch_mldata
from skimage.measure import label, regionprops
from sklearn.neighbors import KNeighborsClassifier


def train(data, target):
    knn = KNeighborsClassifier(n_neighbors=1)
    knn.fit(data, target)
    return knn


def move(image, x, y):
    img = np.zeros((28, 28))
    img[:(28-x), :(28-y)] = image[x:, y:]

    return img


def fill(image):
    if np.shape(image)!=(28, 28):
        img = np.zeros((28,28))
        x = 28 - np.shape(image)[0]
        y = 28 - np.shape(image)[1]
        img[:-x,:-y] = image

        return img
    else:
        return image


def my_rgb2gray(img_rgb):
    img_gray = 0.5*img_rgb[:, :, 0] + 0*img_rgb[:, :, 1] + 0.5*img_rgb[:, :, 2]
    img_gray = img_gray.astype('uint8')
    return img_gray


def my_rgb2gray2(img_rgb):
    frame = img_rgb
    grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    ret, frame_bw = cv2.threshold(grey, 170, 255, 0)
    frame_bw = cv2.morphologyEx(frame_bw, cv2.MORPH_CLOSE, cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3)))

    return frame_bw


def count_images(framecal):
    regions = label(framecal)
    labels = regionprops(regions)

    images = []

    for i in range(0, len(labels)):
        if labels[i].centroid[0] < result[0] and labels[i].centroid[1] < result[1]:
            images.append(labels[i].image)

    count = 0
    for img in images:
        obrada = fill(np.array(img.astype('uint8')))
        count += model.predict(obrada.reshape(1, -1))
    return count


def check2(indices, i):
    check = False
    for el in indices:
        if (el == i):
            check = True
            break

    return check


def findPoints(lines):
    Xmin = 1000
    Ymin = 1000
    Ymax = 0
    Xmax = 0
    for i in range(len(lines)):
        for x1, y1, x2, y2 in lines[i]:
            if x1 < Xmin:
                Xmin = x1
                Ymin = y1
            if x2 > Xmax:
                Ymax = y2
                Xmax = x2

    return Xmin, Ymin, Xmax, Ymax


def hough(frame, gray, min_line_len, max_line_gap):
    edges = cv2.Canny(gray, 50, 150, apertureSize=3)
    cv2.imwrite('line.png', frame)
    lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 40, min_line_len, max_line_gap)

    minx, miny, maxx, maxy = findPoints(lines)
    cv2.line(frame, (minx, miny), (maxx, maxy), (233, 0, 0), 2)
    return minx, miny, maxx, maxy


homepath = 'SoftVideoData/'
videopaths = ['video-0.avi',
              'video-1.avi',
              'video-2.avi',
              'video-3.avi',
              'video-4.avi',
              'video-5.avi',
              'video-6.avi',
              'video-7.avi',
              'video-8.avi',
              'video-9.avi']


mnist = fetch_mldata('MNIST original')
data = mnist.data>0
data = data.astype('uint8')
target = mnist.target


fixed = np.empty_like(data)

for i in range(0, len(data)):
    l = label(data[i].reshape(28, 28))
    r = regionprops(l)

    min_x = r[0].bbox[0]
    min_y = r[0].bbox[1]

    for j in range(1, len(r)):
        if r[j].bbox[0] < min_x:
            min_x = r[j].bbox[0]
        if r[j].bbox[1] < min_y:
            min_y = r[j].bbox[1]

    img = move(data[i].reshape(28, 28), min_x, min_y)
    fixed[i] = img.reshape(784, )


model = train(fixed, target)
for index in range(0,9):
    total = 0
    video = cv2.VideoCapture(homepath + videopaths[index])
    flag, frame = video.read()

    bw = my_rgb2gray(frame)
    result = hough(frame, bw, 10, 50)


    while 1:
        flag1, frame1 = video.read()
        last_count = total
        if flag1 is True:
            bwframe = my_rgb2gray2(frame1)

            curr_count = count_images(bwframe)
            if curr_count <= last_count:
                last_count = curr_count
            else:
                total += curr_count - last_count
                last_count = curr_count

            print total
            k = cv2.waitKey(15) & 0xff
            if k == 27:
                break
        else:
            break

    with open('out.txt', 'a') as file:
        file.write(homepath + videopaths[index] + '\t' + str(total))

我得到这个错误：

Traceback (most recent call last):
  File "C:\Users\Joe\Desktop\SOFT-master7o\SoftProject.py", line 147, in <module>
    bw = my_rgb2gray(frame)
  File "C:\Users\Joe\Desktop\SOFT-master7o\SoftProject.py", line 35, in my_rgb2gray
    img_gray = 0.5*img_rgb[:, :, 0] + 0*img_rgb[:, :, 1] + 0.5*img_rgb[:, :, 2]
TypeError: 'NoneType' object has no attribute '__getitem__'

怎么了？谢谢

Answer 1

当您用方括号调用一个名称时，Python会在引擎盖下调用“getitem”。 所以这意味着img_rgb不是你所期望的。它不是numpy数组，而是None。你知道吗

检查代码中分配img_rgb的部分。你知道吗

Answer 2

评论回复：

在对输入进行操作之前，请检查输入。你知道吗

我将使用VS inbuild调试器并在此行上设置断点：

bw = my_rgb2gray(frame)

并在进入函数之前检查每个frame，如果它是None。你知道吗

如果它的None，如何处理它？取决于-要么跳过该视频帧，要么，如果全部都是无，则说明有问题，您需要检查为什么flag, frame = video.read()会产生一个frame即None。有时文档会帮助您：

https://docs.opencv.org/2.4/modules/highgui/doc/reading_and_writing_images_and_video.html#videocapture

https://docs.opencv.org/2.4/modules/highgui/doc/reading_and_writing_images_and_video.html#videocapture-read