Thank you very much Daniel.
This is very handy for sure, I can see every step of image modification in
PyCharm now :)
I tried to transform image in different orders (crop first, gray, thresh;
gray first, crop then tresh etc) but still there is no good result.
Do you have some interesting material that would help to pinpoint what's
wrong in my preprocess ?
Best regards,
Richard
Le lundi 13 janvier 2020 17:48:01 UTC+1, Daniel Anton a écrit :
>
> Hi Richard,
>
> First of all I would recommend you to visualize each step of your process
> (Threshold, Median ...).
> I use matplotlib for that propuse you can find an example bellow.
>
> The problem is not Tesseract but your preprocess, you shouldn't do a blur
> to a text that small and for the Threshold you can just use
> cv2.THRESH_BINARY.
>
> import cv2
> import pytesseract
>
> from loguru import logger
>
> from matplotlib import pyplot as plt
>
>
> image = cv2.imread("test.png")
>
> x = 375
> y = 0
> h = 40
> w = 160
>
> # IN GREY
> image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
>
> plt.figure(figsize = (40,40))
> plt.imshow(image, cmap = "gray")
> plt.title('image')
> plt.show()
>
>
> # THRESH
> image = cv2.threshold(image, 200, 255, cv2.THRESH_BINARY)[1]
>
>
>
> plt.figure(figsize = (40,40))
> plt.imshow(image, cmap = "gray")
> plt.title('image')
> plt.show()
>
> image = image[y:y+h, x:x+w]
>
> plt.figure(figsize = (40,40))
> plt.imshow(image, cmap = "gray")
> plt.title('image')
> plt.show()
>
> cv2.imwrite("output.png", image)
>
> for arg in range(1, 14):
> try:
> text = pytesseract.image_to_string(image, config=f"-l eng --oem 1
> --psm {arg}")
> logger.info(f"Parsed text [{text}] with [{arg}]")
> except Exception as exception:
> logger.exception(exception)
>
>
>
>
> On Monday, January 13, 2020 at 4:18:40 PM UTC+1, Richard wrote:
>>
>> Hello,
>>
>> I'm starting a software that would analyze eSport matchs, mining
>> statistics from screenshots (i.e. video).
>> I've started simple, I'm trying to extract team names.
>>
>> I've tried to crop/gray but it's not efficient (i.e. text doesn't match).
>>
>> Any tip to improve text recognition ?
>>
>> Code sample used:
>>
>> import cv2
>> import pytesseract
>> from loguru import logger
>>
>>
>> image = cv2.imread("test.png")
>>
>> x = 375
>> y = 0
>> h = 40
>> w = 160
>>
>> # IN GREY
>> image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
>>
>> # BLUR
>> image = cv2.medianBlur(image, 3)
>>
>> # THRESH
>> #image = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
>>
>> #image = image[y:y+h, x:x+w]
>> cv2.imwrite("output.png", image)
>>
>> for arg in range(1, 14):
>> try:
>> text = pytesseract.image_to_string(image, config=f"-l eng --oem 1
>> --psm {arg}")
>> logger.info(f"Parsed text [{text}] with [{arg}]")
>> except Exception as exception:
>> logger.exception(exception)
>>
>>
>>
>>
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