image processing and get all text

# Import some modules import cv2 # An image proccessing library import pytesseract # an image to text library import numpy as np # used for mathematics but can be used in image proccessing # Configure the module pytesseract.pytesseract.tesseract_cmd = r'C:UsersyournameAppDataLocalTesseract-OCRtesseract.exe' # Make the image grey img = cv2.imread('your_img.png') gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) gray, img_bin = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU) gray = cv2.bitwise_not(img_bin) kernel = np.ones((2, 1), np.uint8) img = cv2.erode(gray, kernel, iterations=1) img = cv2.dilate(img, kernel, iterations=1) # Use OCR to read the text from the image out_below = pytesseract.image_to_string(img) # Print the text print(out_below)

image processing for OCR using python

1| # importing modules
2| import cv2
3| import pytesseract
5| # reading image using opencv
6| image = cv2.imread(sample_image.png’)
7| #converting image into gray scale image
8| gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
9| # converting it to binary image by Thresholding
10| # this step is require if you have colored image because if you skip this part 
11| # then tesseract won't able to detect text correctly and this will give incorrect result
11|threshold_img = cv2.threshold(gray_image, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
12| # display image
13| cv2.imshow(‘threshold image’, threshold_img)
14| # Maintain output window until user presses a key
15| cv2.waitKey(0)
16| # Destroying present windows on screen
17| cv2.destroyAllWindows()

Posted by: Guest on September-22-2020

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