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Reading Text from the Image using Tesseract

Pytesseract or Python-tesseract is an Optical Character Recognition (OCR) tool for python. It will read and recognize the text in images, license plates, etc. Here, we will use the tesseract package to read the text from the given image. 
 

Mainly, 3 simple steps are involved here as shown below:-  



Implementation:

The following python code represents the Localizing of the Text and correctly guessing the text written in the image. 
 




# We import the necessary packages
#import the needed packages
import cv2
import os,argparse
import pytesseract
from PIL import Image
 
#We then Construct an Argument Parser
ap=argparse.ArgumentParser()
ap.add_argument("-i","--image",
                required=True,
                help="Path to the image folder")
ap.add_argument("-p","--pre_processor",
                default="thresh",
                help="the preprocessor usage")
args=vars(ap.parse_args())
 
#We then read the image with text
images=cv2.imread(args["image"])
 
#convert to grayscale image
gray=cv2.cvtColor(images, cv2.COLOR_BGR2GRAY)
 
#checking whether thresh or blur
if args["pre_processor"]=="thresh":
    cv2.threshold(gray, 0,255,cv2.THRESH_BINARY| cv2.THRESH_OTSU)[1]
if args["pre_processor"]=="blur":
    cv2.medianBlur(gray, 3)
     
#memory usage with image i.e. adding image to memory
filename = "{}.jpg".format(os.getpid())
cv2.imwrite(filename, gray)
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
print(text)
 
# show the output images
cv2.imshow("Image Input", images)
cv2.imshow("Output In Grayscale", gray)
cv2.waitKey(0)

Now, follow the below steps to successfully Read Text from an image: 



Example 1:

Execute the command below to view the Output.

python  tesseract.py --image Images/title.png

We have The Original Image displayed.

title

We have the GrayScale Image Displayed. (p.png)

p

Output:

Example 2:

Execute the command below to view the Output.

python  tesseract.py --image Images/OCR.png

We have The Original Image displayed.

OCR

We have the GrayScale Image Displayed. (p.png)

p

Output:


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