CODEWITHSUNDEEP
pythontesseract
S demitri
S demitri

Reputation: 13

How can I get text from this image with Tesseract?

Currently I'm using the code below to get text from image and it works fine, but it doesn't work well with these two images, it seems like tesseract cannot scan these types of image. Please show me how to fix it

https://i.ibb.co/zNkbhKG/Untitled1.jpg

https://i.ibb.co/XVbjc3s/Untitled3.jpg

def read_screen():
        spinner = Halo(text='Reading screen', spinner='bouncingBar')
        spinner.start()
        screenshot_file="Screens/to_ocr.png"
        screen_grab(screenshot_file)

        #prepare argparse
        ap = argparse.ArgumentParser(description='HQ_Bot')
        ap.add_argument("-i", "--image", required=False,default=screenshot_file,help="path to input image to be OCR'd")
        ap.add_argument("-p", "--preprocess", type=str, default="thresh", help="type of preprocessing to be done")
        args = vars(ap.parse_args())

        # load the image 
        image = cv2.imread(args["image"])
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

        if args["preprocess"] == "thresh":
                gray = cv2.threshold(gray, 177, 177,
                        cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
        elif args["preprocess"] == "blur":
                gray = cv2.medianBlur(gray, 3)

        # store grayscale image as a temp file to apply OCR
        filename = "Screens/{}.png".format(os.getpid())
        cv2.imwrite(filename, gray)

        # load the image as a PIL/Pillow image, apply OCR, and then delete the temporary file
        pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files\\Tesseract-OCR\\tesseract.exe'
        #ENG
        #text = pytesseract.image_to_string(Image.open(filename))

        #VIET
        text = pytesseract.image_to_string(Image.open(filename), lang='vie')

        os.remove(filename)
        os.remove(screenshot_file)

        # show the output images

        '''cv2.imshow("Image", image)
        cv2.imshow("Output", gray)
        os.remove(screenshot_file)
        if cv2.waitKey(0):
                cv2.destroyAllWindows()
        print(text)
        '''
        spinner.succeed()
        spinner.stop()
        return text

Upvotes: 1

Views: 4056

Answers (1)

CodeSamurai777
CodeSamurai777

Reputation: 3355

You should try different psm modes instead of default like so:

target = pytesseract.image_to_string(im,config='--psm 4',lang='vie')

Exert from docs:

Page segmentation modes:
  0    Orientation and script detection (OSD) only.
  1    Automatic page segmentation with OSD.
  2    Automatic page segmentation, but no OSD, or OCR.
  3    Fully automatic page segmentation, but no OSD. (Default)
  4    Assume a single column of text of variable sizes.
  5    Assume a single uniform block of vertically aligned text.
  6    Assume a single uniform block of text.
  7    Treat the image as a single text line.
  8    Treat the image as a single word.
  9    Treat the image as a single word in a circle.
 10    Treat the image as a single character.
 11    Sparse text. Find as much text as possible in no particular order.
 12    Sparse text with OSD.
 13    Raw line. Treat the image as a single text line,
                        bypassing hacks that are Tesseract-specific.

So for example for /Untitled3.jpg you could try --psm 4 and failing that you could try --psm 11 for both.

Depending on your version of tesseract you could also try different oem modes:

Use --oem 1 for LSTM, --oem 0 for Legacy Tesseract. Please note that Legacy Tesseract models are only included in traineddata files from tessdata repo.

EDIT

Also as seen in your images there are two languages so if you wish to use lang parameter you need to manually separate image into two to not to confuse tesseract engine and use different lang values for them.

EDIT 2

Below a full working example with Unitiled3. What I noticed was your improper use of thresholding. You should set maxval to something bigger than the value you are thresholding at. Like in my example I set thresh 177 but maxval to 255 so everything above 177 will be black. I didn't even had to do any binarization.

import cv2
import pytesseract
from cv2.cv2 import imread, cvtColor, COLOR_BGR2GRAY, threshold, THRESH_BINARY

image = imread("./Untitled3.jpg")
image = cvtColor(image,COLOR_BGR2GRAY)
_,image = threshold(image,177,255,THRESH_BINARY)
cv2.namedWindow("TEST")
cv2.imshow("TEST",image)
cv2.waitKey()
text = pytesseract.image_to_string(image, lang='eng')
print(text)

Output:

New York, New York

Salzburg, Austria

Hollywood, California

Upvotes: 2

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