Jun-10-2019, 02:07 PM
import cv2 import numpy as np import pytesseract from PIL import Image from pytesseract import image_to_string # Path of working folder on Disk src_path = "tes-img/" def get_string(img_path): # Read image with opencv img = cv2.imread(img_path) # Convert to gray img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Apply dilation and erosion to remove some noise kernel = np.ones((1, 1), np.uint8) img = cv2.dilate(img, kernel, iterations=1) img = cv2.erode(img, kernel, iterations=1) # Write image after removed noise cv2.imwrite(src_path + "removed_noise.png", img) # Apply threshold to get image with only black and white #img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2) # Write the image after apply opencv to do some ... cv2.imwrite(src_path + "thres.png", img) # Recognize text with tesseract for python result = pytesseract.image_to_string(Image.open(src_path + "thres.png")) # Remove template file #os.remove(temp) return result print('--- Start recognize text from image ---') print(get_string(src_path + "cont.jpg") ) 