Question

我是python的新手，我正尝试在youtube https://www.youtube.com/watch?v=6tNS--WetLI&t=168s上浏览该教程我有错误信息代码：

import unittest
import calc

class TestCalc(unittest.Testcase):
    def test_add(self):
        result=calc.add(10,5)
        self.assertEqual(result,15)

suite = unittest.TestLoader().loadTestsFromTestCase(TestCalc)
unittest.TextTestRunner(verbosity=2).run(suite)

我已经看到了关于stackoverflow的所有答案，但是可以抗错误。

请帮助

Answer 1

您在写课程名称时打了错字。大写字母import numpy as np from PIL import Image import tensorflow as tf import os import pytesseract import sys import re #from pdf2image import convert_from_path #need proppeler windows distrubution import cv2 #from pdf2image.exceptions import PDFInfoNotInstalledError,PDFPageCountError,PDFSyntaxError pdftoppm_path = r"C:\Program Files (x86)\Poppler\poppler-0.68.0\bin\pdftoppm.exe" #path to tesseract instalattion pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract-OCR\\tesseract.exe' def sort_contours(cnts, method="left-to-right"): # initialize the reverse flag and sort index reverse = False i = 0 # handle if we need to sort in reverse if method == "right-to-left" or method == "bottom-to-top": reverse = True # handle if we are sorting against the y-coordinate rather than # the x-coordinate of the bounding box if method == "top-to-bottom" or method == "bottom-to-top": i = 1 # construct the list of bounding boxes and sort them from top to # bottom boundingBoxes = [cv2.boundingRect(c) for c in cnts] (cnts, boundingBoxes) = zip(*sorted(zip(cnts, boundingBoxes), key=lambda b: b[1][i], reverse=reverse)) # return the list of sorted contours and bounding boxes return (cnts, boundingBoxes) def box_extraction(img_for_box_extraction_path, cropped_dir_path): img1 = cv2.imread(img_for_box_extraction_path, 0) # Read the image img = cv2.resize(img1, (800, 800)) (thresh, img_bin) = cv2.threshold(img, 120, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU) # Thresholding the image img_bin = 255-img_bin # Invert the image ##cv2.imshow("Image_bin.jpg",img_bin) # Defining a kernel length kernel_length = np.array(img).shape[1]//150 # A verticle kernel of (1 X kernel_length), which will detect all the verticle lines from the image. verticle_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1, kernel_length)) # A horizontal kernel of (kernel_length X 1), which will help to detect all the horizontal line from the image. hori_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (kernel_length, 1)) # A kernel of (3 X 3) ones. kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2)) # Morphological operation to detect verticle lines from an image img_temp1 = cv2.erode(img_bin, verticle_kernel, iterations=3) verticle_lines_img = cv2.dilate(img_temp1, verticle_kernel, iterations=3) #cv2.imwrite("verticle_lines.jpg",verticle_lines_img) # Morphological operation to detect horizontal lines from an image img_temp2 = cv2.erode(img_bin, hori_kernel, iterations=3) horizontal_lines_img = cv2.dilate(img_temp2, hori_kernel, iterations=3) #cv2.imwrite("horizontal_lines.jpg",horizontal_lines_img) # Weighting parameters,a=0.4 and b=0.8. this will decide the quantity of an image to be added to make a new image. alpha = 0.8 beta = 5.0 - alpha # This function helps to add two image with specific weight parameter to get a third image as summation of two image. img_final_bin = cv2.addWeighted(verticle_lines_img, alpha, horizontal_lines_img, beta, 0.0) img_final_bin = cv2.erode(~img_final_bin, kernel, iterations=2) (thresh, img_final_bin) = cv2.threshold(img_final_bin, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU) # For Debugging # Enable this line to see verticle and horizontal lines in the image which is used to find boxes ##cv2.imshow("img_final_bin.jpg",img_final_bin) # Find contours for image, which will detect all the boxes contours, hierarchy = cv2.findContours( img_final_bin, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # Sort all the contours by top to bottom. (contours, boundingBoxes) = sort_contours(contours)#, method="top-to-bottom") idx = 0 for c in contours: # Returns the location and width,height for every contour x, y, w, h = cv2.boundingRect(c) #print(x,y,w,h) # If the box height is less than 80, widht is <400, then only save it as a box in "cropped/" folder. if (w < 400 and h < 80): # and h < 6*w: idx += 1 new_img = img[y:y+h+10, x:x+w+10] contours1, hierarchy1 = cv2.findContours(img_final_bin, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # Sort all the contours by top to bottom. (contours1, boundingBoxes) = sort_contours(contours1, method="top-to-bottom") # get the thresholded crop retval, thresh_crop = cv2.threshold(new_img, thresh=200, maxval=255, type=cv2.THRESH_BINARY) cv2.imwrite(cropped_dir_path+str(idx) + '.png', thresh_crop) # For Debugging # Enable this line to see all contours. # cv2.drawContours(img, contours, -1, (0, 0, 255), 3) # cv2.imwrite("./Temp/img_contour.jpg", img) box_extraction("X:\PDF2IMG\TEST.jpeg", "X:\PDF2IMG\cropped") #cv2.waitKey(0) #cv2.destroyAllWindows()中使用大写字母，就像您在documentation中看到的一样。

AttributeError：模块“ unittest”没有属性“ Testcase”

1 个答案: