类型错误:“key"是此函数的无效关键字参数 [英] TypeError: 'key' is an invalid keyword argument for this function

问题描述

我正在尝试使用 opencv 将图像转换为文本，但代码出现以下错误:

<块引用>

contours.sort(key=lambda x: get_contour_precedence(x, img.shape[1]))TypeError: 'key' 是此函数错误的无效关键字参数.

有什么办法可以解决吗?这是代码:

导入 cv2导入 pytesseract将 numpy 导入为 np将 PIL.Image 导入为 Imagepytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract-OCR\\tesseract'def get_contour_precedence(contour, cols):容差系数 = 20原点 = cv2.boundingRect(contour)return ((origin[0]//tolerance_factor) * tolerance_factor) * cols +起源[1]img = cv2.imread("C:/Users/Akshatha/Desktop/text_detection_from_image/images/news1.jpg")灰色 = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)ret, thresh = cv2.threshold(gray, 0, 255,cv2.THRESH_BINARY_INV +cv2.THRESH_OTSU)内核 = np.ones((5, 5), np.uint8)侵蚀= cv2.erode(阈值，内核，迭代= 1)dilation = cv2.dilate(thresh, kernel, 迭代=3)(contours, heirarchy,_) = cv2.findContours(dilation, cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)层次结构=层次结构[0]打印(开始")打印(np.array(层次结构).形状，np.array(轮廓).形状)打印(停止")轮廓.sort(key=lambda x: get_contour_precedence(x, img.shape[1]))# 打印(轮廓[0])idx = 0文本列表 = []我 = 0rect_list = []对于轮廓中的 c:# 获取边界矩形x, y, w, h = cv2.boundingRect(c)rect_list.append((x, y, x + w, y + h))# 绘制一个绿色矩形来可视化边界矩形cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 0), 3)roi = img[y:y + h, x:x + w]text = pytesseract.image_to_string(roi, lang='eng', config='--oem 1 --psm 6 -c preserve_interword_spaces=1 ')打印(文本)cv2.putText(img, "#{}".format(i + 1), (x, y - 15),cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 4)我 += 1cv2.namedWindow('扩张', cv2.WINDOW_NORMAL)cv2.imshow('扩张', img)cv2.waitKey(0)

解决方案

您使用的 sort() 函数不接受 key 参数.如果 contours 是可迭代的，您可以尝试使用 sorted() 代替，如下所示:

sorted(contours, key=lambda x:x)

请注意，这将返回一个列表.

I'm trying to convert an image to text using opencv, but the code gives the following error:

contours.sort(key=lambda x: get_contour_precedence(x, img.shape[1]))
TypeError: 'key' is an invalid keyword argument for this function error.

Is there any way to fix it? This is the code:

import cv2
import pytesseract
import numpy as np
import PIL.Image as Image


pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract- 
OCR\\tesseract'

def get_contour_precedence(contour, cols):
    tolerance_factor = 20
    origin = cv2.boundingRect(contour)
    return ((origin[0] // tolerance_factor) * tolerance_factor) * cols + 
    origin[1]


img = cv2.imread("C:/Users/Akshatha/Desktop/text_detection_from 
_image/images/news1.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

ret, thresh = cv2.threshold(gray, 0, 255,cv2.THRESH_BINARY_INV + 
cv2.THRESH_OTSU)

kernel = np.ones((5, 5), np.uint8)
erosion = cv2.erode(thresh, kernel, iterations=1)

dilation = cv2.dilate(thresh, kernel, iterations=3)
(contours, heirarchy,_) = cv2.findContours(dilation, cv2.RETR_EXTERNAL, 
cv2.CHAIN_APPROX_SIMPLE)
heirarchy = heirarchy[0]
print("start")
print(np.array(heirarchy).shape, np.array(contours).shape)
print("stop")
contours.sort(key=lambda x: get_contour_precedence(x, img.shape[1]))

# print(contours[0])
idx = 0
textlist = []
i = 0
rect_list = []
for c in contours:
  # get the bounding rect
  x, y, w, h = cv2.boundingRect(c)
  rect_list.append((x, y, x + w, y + h))
  # draw a green rectangle to visualize the bounding rect
  cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 0), 3)

  roi = img[y:y + h, x:x + w]
  text = pytesseract.image_to_string(roi, lang='eng', config='--oem 1 -- 
   psm 6 -c preserve_interword_spaces=1 ')
   print(text)
  cv2.putText(img, "#{}".format(i + 1), (x, y - 15), 
  cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 4)
   i += 1

cv2.namedWindow('Dilation', cv2.WINDOW_NORMAL)
cv2.imshow('Dilation', img)
cv2.waitKey(0)

解决方案

The sort() function you're using doesn't take a key argument. If contours is an iterable, you can try using sorted() instead like this:

sorted(contours, key=lambda x:x)

Note that this will return a list.

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