text_based_recognition.py

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



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("removed_noise.jpg", 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("thres.jpg", img)

    # Recognize text with tesseract for python
    result = pytesseract.image_to_string(Image.open("im1.jpg"))

    # Remove template file
    #os.remove(temp)

    return result


print ('--- Start recognize text from image ---')
print (get_string("im1.jpg"))

print ("------ Done -------")