Take look at the attached file.
How can I implement ALTO in it and what will the command look like in
teminal?
Tommy
torsdag 8. august 2019 12.04.23 UTC+2 skrev Tommy Klausen følgende:
>
> Ok.
>
> Because if a config file for alto exists (which didn`t for some reason in
> the install) I can just write the command with "alto" in the end, right?
>
> Can you give me the two different commands for reading an image (with and
> without the confg file)?
>
> torsdag 8. august 2019 11.51.27 UTC+2 skrev shree følgende:
>>
>>
>> https://github.com/tesseract-ocr/tesseract/blob/master/tessdata/configs/alto
>>
>>
>> You can use `alto` config file or use the config variable as part of
>> command
>>
>> -c tessedit_create_alto=1
>>
>> On Thu, Aug 8, 2019 at 2:59 PM Tommy Klausen <[email protected]> wrote:
>>
>>> Hi.
>>>
>>> Is the ALTO config option supported in the last linux version of
>>> Tesseract?
>>> I have managed to use the HOCR but not ALTO.
>>> Is it something I need to do with the config files?
>>>
>>> Tommy
>>>
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>>>
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>>> .
>>>
>>
>>
>> --
>>
>> ____________________________________________________________
>> भजन - कीर्तन - आरती @ http://bhajans.ramparivar.com
>>
>
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# import the necessary packages
from PIL import Image
import pytesseract
import argparse
import cv2
import os
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
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 example image and convert it to grayscale
image = cv2.imread(args["image"])
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
# check to see if we should apply thresholding to preprocess the
# image
if args["preprocess"] == "thresh":
gray = cv2.threshold(gray, 0, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
# make a check to see if median blurring should be done to remove
# noise
elif args["preprocess"] == "blur":
gray = cv2.medianBlur(gray, 3)
# write the grayscale image to disk as a temporary file so we can
# apply OCR to it
filename = "{}.png".format(os.getpid())
cv2.imwrite(filename, gray)
# load the image as a PIL/Pillow image, apply OCR, and then delete
# the temporary file
text = pytesseract.image_to_string(Image.open(filename))
os.remove(filename)
print(text)
# show the output images
cv2.imshow("Image", image)
cv2.imshow("Output", gray)
cv2.waitKey(0)
