threshhold.py

from doctest import OutputChecker

import cv2

import pytesseract

import csv
from pytesseract import Output

 # reading image using opencv

path=r'C:\Users\tapiw\OneDrive\Pictures\Background.jpg'

image = cv2.imread(path)

#converting image into gray scale image

gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# converting it to binary image by Thresholding

 # this step is require if you have colored image because if you skip this part

 # then tesseract won't able to detect text correctly and this will give incorrect result
threshold_img = cv2.threshold(gray_image, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

 # display image
 #--------------------------------------------------------------------------------------------------------------skipping the show and wait key

cv2.imshow('threshold image', threshold_img)

 # Maintain output window until user presses a key

cv2.waitKey(0)

 # Destroying present windows on screen

cv2.destroyAllWindows()

  #configuring parameters for tesseract

custom_config = r'--oem 3 --psm 6'

 # now feeding image to tesseract
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'

details = pytesseract.image_to_data(threshold_img, output_type=Output.DICT, config=custom_config, lang='eng')

print(details.keys())

total_boxes = len(details['text'])

for sequence_number in range(total_boxes):

	if int(details['conf'][sequence_number]) >30:

		(x, y, w, h) = (details['left'][sequence_number], details['top'][sequence_number], details['width'][sequence_number],  details['height'][sequence_number])

		threshold_img = cv2.rectangle(threshold_img, (x, y), (x + w, y + h), (0, 255, 0), 2)

# display image
#-------------------------------------------------------------------------------------------------------------------------------------------------------------------------Skipping captured windows 
cv2.imshow('captured text', threshold_img)

# Maintain output window until user presses a key

cv2.waitKey(0)

# Destroying present windows on screen

cv2.destroyAllWindows()

parse_text = []

word_list = []

last_word = ''

for word in details['text']:

    if word!='':

        word_list.append(word)

        last_word = word

    if (last_word!='' and word == '') or (word==details['text'][-1]):

        parse_text.append(word_list)

        word_list = []
results=r'C:\Users\tapiw\OneDrive\Pictures\opencvtestresults.txt'
with open(results,  'w', newline="") as file:
    csv.writer(file, delimiter=" ").writerows(parse_text)