Re: [tesseract-ocr] Tessaract not able to output detected text

[payel roy]

Hi  Zdenko

Thanks for your email. I already tried with multiple combination changing
different parameters. However I am still not able to get text from the
image. Attached my pre-processing code, which I am running before using
tesseract. But however I am unable to get text still. Please help.

On Tue, 28 Apr 2020 at 23:57, Zdenko Podobny <zde...@gmail.com> wrote:

> https://tesseract-ocr.github.io/tessdoc/ImproveQuality.html
>
> Zdenko
>
>
> ut 28. 4. 2020 o 20:26 payel roy <smithpa...@gmail.com> napísal(a):
>
>> Hi Team,
>>
>> I am new to Tessaract. Following the code snippet. While running it, I
>> can't get result back from Tesseract on the detect texts. Please help.
>>
>> #!/usr/bin/python
>>
>> import cv2
>> import pytesseract
>> import sys
>> from PIL import Image
>>
>> filename=sys.argv[1]
>>
>> print(pytesseract.image_to_string(Image.open(filename)))
>>
>>
>> Both of the above images get detected by Amazon rekognition system with
>> 80% confidence score. Would you please help how I can get this working on
>> Tesseract?
>>
>> Thanks
>>
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#!/usr/bin/python

import cv2
import numpy as np
import sys

# get grayscale image
def get_grayscale(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# noise removal
def remove_noise(image):
    return cv2.medianBlur(image,5)
 
#thresholding
def thresholding(image):
    return cv2.threshold(image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

#dilation
def dilate(image):
    kernel = np.ones((5,5),np.uint8)
    return cv2.dilate(image, kernel, iterations = 1)
    
#erosion
def erode(image):
    kernel = np.ones((5,5),np.uint8)
    return cv2.erode(image, kernel, iterations = 1)

#opening - erosion followed by dilation
def opening(image):
    kernel = np.ones((5,5),np.uint8)
    return cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)

#canny edge detection
def canny(image):
    return cv2.Canny(image, 100, 200)

#skew correction
def deskew(image):
    coords = np.column_stack(np.where(image > 0))
    angle = cv2.minAreaRect(coords)[-1]
    if angle < -45:
        angle = -(90 + angle)
    else:
        angle = -angle
    (h, w) = image.shape[:2]
    center = (w // 2, h // 2)
    M = cv2.getRotationMatrix2D(center, angle, 1.0)
    rotated = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, 
borderMode=cv2.BORDER_REPLICATE)
    return rotated

#template matching
def match_template(image, template):
    return cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)


if __name__ == "__main__":
    filename=sys.argv[1]
    image = cv2.imread(filename)

    gray = get_grayscale(image)
    thresh = thresholding(gray)
    opening = opening(gray)
    canny = canny(gray)
    #deskew=deskew(canny)
    

    outputFilename="pre-"+filename;
    cv2.imwrite(outputFilename, canny)