better link? <https://www.toptal.com/developers/hastebin/nonepalihe>
On Friday, December 31, 2021 at 10:27:41 AM UTC-8 Cyrus Yip wrote: > Right now I'm installing tesseract 4 in docker with > RUN apt-get install -y tesseract-ocr > That might be a reason why it's way slower than on my computer, how can I > install tesseract 5? > > Dockerfile # syntax=docker/dockerfile:1 > > ARG TOKEN > > FROM python:3.8-slim-buster > > RUN apt-get update > RUN apt-get install -y software-properties-common > RUN apt-get update > RUN add-apt-repository ppa:alex-p/tesseract-ocr-devel > > RUN apt-get update > RUN apt-get install -y build-essential > > COPY requirements.txt requirements.txt > RUN pip3 install -r requirements.txt > > COPY . . > > RUN apt-get install -y tesseract > > CMD ["python3", "bot.py"] > > Build logs > <https://appbuild-logs-ams3.ams3.digitaloceanspaces.com/a7609af2-64e1-4ba2-8555-87a4fac8a37f/9420eaef-131e-410f-8add-bbfb870b2693/981a4c35-45d7-41b5-8619-3d9125d60c25/build.log?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=2JPIHVK4OTM6S5VRFBCK%2F20211231%2Fams3%2Fs3%2Faws4_request&X-Amz-Date=20211231T182608Z&X-Amz-Expires=900&X-Amz-SignedHeaders=host&X-Amz-Signature=3ae248ce9fb9e6fef0c71955d9cd9496feb8311162bdda8921750a21544f79a6> > > > On Friday, December 31, 2021 at 3:18:18 AM UTC-8 zdenop wrote: > >> You are right - np.isin is working another way than I expected (it does >> not match tuples, but individual values at tuples) and by coincidence, it >> produces similar results as your code. >> >> Here is updated code that produces the same result as PIL. It is faster >> but with an increasing number of colors in filter_colors, it will be >> slower. >> >> filter_colors = [(51, 51, 51), (69, 69, 65), (65, 64, 60), (59, 58, 56), >> (67, 66, 62), >> (67, 67, 63), (67, 67, 62), (53, 53, 53), (54, 54, 53), (61, >> 61, 58), >> (62, 62, 60), (55, 55, 54), (59, 59, 57), (56, 56, 55)] >> >> image = np.array(Image.open('mai.png').convert("RGB")) >> mask = np.array([], dtype=bool) >> for color in filter_colors: >> if mask.size == 0: >> mask = (image == color).all(-1) >> else: >> mask = mask | (image == color).all(-1) >> img = Image.fromarray(~mask) >> >> >> Zdenko >> >> >> pi 31. 12. 2021 o 1:45 Cyrus Yip <[email protected]> napísal(a): >> >>> For some reason, using the numpy array has a different result than mine. >>> >>> Numpy array: >>> >>> [image: hi.png] >>> Loop through pixels: >>> [image: hi.png] >>> The second was is more accurate but way slower. >>> On Thursday, December 30, 2021 at 11:43:01 AM UTC-8 zdenop wrote: >>> >>>> try this: >>>> >>>> import numpy as np >>>> from PIL import Image >>>> >>>> filter_colors = [(51, 51, 51), (69, 69, 65), (65, 64, 60), (59, 58, >>>> 56), (67, 66, 62), >>>> >>>> (67, 67, 63), (67, 67, 62), (53, 53, 53), (54, 54, 53), (61, >>>> 61, 58), >>>> (62, 62, 60), (55, 55, 54), (59, 59, 57), (56, 56, 55)] >>>> image = np.array(Image.open('mai.png').convert("RGB")) >>>> mask = np.isin(image, filter_colors, invert=True) >>>> img = Image.fromarray(mask.any(axis=2)) >>>> >>>> >>>> Zdenko >>>> >>>> >>>> št 30. 12. 2021 o 18:14 Cyrus Yip <[email protected]> napísal(a): >>>> >>>>> I also tried many things like cropping, colour changing, colour >>>>> replacing, and mixing them together. >>>>> >>>>> I landed on checking if a pixel is not one of these: >>>>> >>>>> [(51, 51, 51), (69, 69, 65), (65, 64, 60), (59, 58, 56), (67, 66, 62), >>>>> (67, 67, 63), (67, 67, 62), (53, 53, 53), (54, 54, 53), (61, 61, 58), >>>>> (62, >>>>> 62, 60), (55, 55, 54), (59, 59, 57), (56, 56, 55)] >>>>> >>>>> colours, replace it with white. It is pretty accurate but is there a >>>>> way to do this with numpy arrays? >>>>> >>>>> (code) >>>>> for x in range(im.width): >>>>> if pixels[x, y] not in [(51, 51, 51), (69, 69, 65), (65, 64, 60), >>>>> (59, 58, 56), (67, 66, 62), (67, 67, 63), (67, 67, 62), (53, 53, 53), >>>>> (54, >>>>> 54, 53), (61, 61, 58), (62, 62, 60), (55, 55, 54), (59, 59, 57), (56, 56, >>>>> 55)]: >>>>> pixels[x, y] = (255, 255, 255) >>>>> On Thursday, December 30, 2021 at 8:46:51 AM UTC-8 zdenop wrote: >>>>> >>>>>> OK. I played a little bit ;-): >>>>>> >>>>>> I tested the speed of your code with your image: >>>>>> >>>>>> import timeit >>>>>> >>>>>> pil_color_replace = """ >>>>>> from PIL import Image >>>>>> >>>>>> im = Image.open('mai.png').convert("RGB") >>>>>> >>>>>> pixdata = im.load() >>>>>> for y in range(im.height): >>>>>> for x in range(im.width): >>>>>> if pixdata[x, y] != (51, 51, 51): >>>>>> pixdata[x, y] = (255, 255, 255) >>>>>> """ >>>>>> >>>>>> elapsed_time = timeit.timeit(pil_color_replace, number=100)/100 >>>>>> print(f"duration: {elapsed_time:.4} seconds") >>>>>> >>>>>> I got an average speed 0.08547 seconds on my computer. >>>>>> On internet I found the suggestion to use numpy for this and I >>>>>> finished with the following code: >>>>>> >>>>>> np_color_replace_rgb = """ >>>>>> import numpy as np >>>>>> from PIL import Image >>>>>> >>>>>> data = np.array(Image.open('mai.png').convert("RGB")) >>>>>> mask = (data == [51, 51, 51]).all(-1) >>>>>> img = Image.fromarray(np.invert(mask)) >>>>>> """ >>>>>> >>>>>> elapsed_time = timeit.timeit(np_color_replace_rgb, number=100)/100 >>>>>> print(f"duration: {elapsed_time:.4} seconds") >>>>>> >>>>>> I got an average speed 0.01774 seconds e.g. 4.8 faster than the PIL >>>>>> code. >>>>>> It is a little bit cheating as it does not replace colors - just take >>>>>> a mask of target color and return it as a binarized image, what is >>>>>> exactly >>>>>> what you need for OCR ;-) >>>>>> >>>>>> Also, I would like to point out that the result OCR output is not so >>>>>> perfect (compared to OCR of unmodified text areas), as this kind of >>>>>> binarization is very simple. >>>>>> >>>>>> >>>>>> Zdenko >>>>>> >>>>>> >>>>>> št 30. 12. 2021 o 11:19 Zdenko Podobny <[email protected]> napísal(a): >>>>>> >>>>>>> Just made your tests ;-) >>>>>>> >>>>>>> You can use tesserocr (maybe quite difficult installation if you are >>>>>>> on windows) instead of pytesseract (e.g. initialize tesseract API once >>>>>>> and >>>>>>> use is multiple times). But it does not provide DICT output. >>>>>>> >>>>>>> >>>>>>> Zdenko >>>>>>> >>>>>>> >>>>>>> st 29. 12. 2021 o 21:18 Cyrus Yip <[email protected]> napísal(a): >>>>>>> >>>>>>>> but won't multiple ocr's and crops use a lot of time? >>>>>>>> >>>>>>>> On Wednesday, December 29, 2021 at 10:15:26 AM UTC-8 zdenop wrote: >>>>>>>> >>>>>>>>> IMO if the text is always in the same area, cropping and OCR just >>>>>>>>> that area will be faster. >>>>>>>>> >>>>>>>>> Zdenko >>>>>>>>> >>>>>>>>> >>>>>>>>> st 29. 12. 2021 o 18:58 Cyrus Yip <[email protected]> napísal(a): >>>>>>>>> >>>>>>>>>> I played around a bit and replacing all colours except for text >>>>>>>>>> colour and it works pretty well! >>>>>>>>>> >>>>>>>>>> The only thing is replacing colours with: >>>>>>>>>> im = im.convert("RGB") >>>>>>>>>> pixdata = im.load() >>>>>>>>>> for y in range(im.height): >>>>>>>>>> for x in range(im.width): >>>>>>>>>> if pixdata[x, y] != (51, 51, 51): >>>>>>>>>> pixdata[x, y] = (255, 255, 255) >>>>>>>>>> is a bit slow. Do you know a better way to replace pixels in >>>>>>>>>> python? I don't know if this is off topic. >>>>>>>>>> On Wednesday, December 29, 2021 at 9:46:13 AM UTC-8 zdenop wrote: >>>>>>>>>> >>>>>>>>>>> If you properly crop text areas you get good output. E.g. >>>>>>>>>>> >>>>>>>>>>> [image: r_cropped.png] >>>>>>>>>>> >>>>>>>>>>> > tesseract r_cropped.png - --dpi 300 >>>>>>>>>>> >>>>>>>>>>> Rascal Does Not Dream >>>>>>>>>>> of Bunny Girl Senpai >>>>>>>>>>> >>>>>>>>>>> Zdenko >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> st 29. 12. 2021 o 18:21 Cyrus Yip <[email protected]> >>>>>>>>>>> napísal(a): >>>>>>>>>>> >>>>>>>>>>>> here is an example of an image i would like to use ocr on: >>>>>>>>>>>> [image: drop8.png] >>>>>>>>>>>> I would like the results to be like: >>>>>>>>>>>> ["Naruto Uzumaki Naruto", "Mai Sakurajima Rascal Does Not Dream >>>>>>>>>>>> of Bunny Girl Senpai", "Keqing Genshin Impact"] >>>>>>>>>>>> >>>>>>>>>>>> Right now I'm using >>>>>>>>>>>> region1 = im.crop((0, 55, im.width, 110)) >>>>>>>>>>>> region2 = im.crop((0, 312, im.width, 360)) >>>>>>>>>>>> image = Image.new("RGB", (im.width, region1.height + >>>>>>>>>>>> region2.height + 20)) >>>>>>>>>>>> image.paste(region1) >>>>>>>>>>>> image.paste(region2, (0, region1.height + 20)) >>>>>>>>>>>> results = pytesseract.image_to_data(image, >>>>>>>>>>>> output_type=pytesseract.Output.DICT) >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> the processed image looks like >>>>>>>>>>>> [image: hi.png] >>>>>>>>>>>> but getting results like: >>>>>>>>>>>> [' ', '»MaiSakurajima¥RascalDoesNotDreamofBunnyGirlSenpai', >>>>>>>>>>>> 'iGenshinImpact'] >>>>>>>>>>>> >>>>>>>>>>>> How do I optimize the image/configs so the ocr is more accurate? >>>>>>>>>>>> >>>>>>>>>>>> Thank you. >>>>>>>>>>>> >>>>>>>>>>>> -- >>>>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>>>> To unsubscribe from this group and stop receiving emails from >>>>>>>>>>>> it, send an email to [email protected]. >>>>>>>>>>>> To view this discussion on the web visit >>>>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/1a2fa0e4-b998-4931-ad7d-ae069a46568bn%40googlegroups.com >>>>>>>>>>>> >>>>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/1a2fa0e4-b998-4931-ad7d-ae069a46568bn%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>>>> . >>>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>> You received this message because you are subscribed to the >>>>>>>>>> Google Groups "tesseract-ocr" group. >>>>>>>>>> To unsubscribe from this group and stop receiving emails from it, >>>>>>>>>> send an email to [email protected]. >>>>>>>>>> >>>>>>>>> To view this discussion on the web visit >>>>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/3c60a0fd-a213-4caa-8a0d-6888a116b08an%40googlegroups.com >>>>>>>>>> >>>>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/3c60a0fd-a213-4caa-8a0d-6888a116b08an%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>>>> . >>>>>>>>>> >>>>>>>>> -- >>>>>>>> You received this message because you are subscribed to the Google >>>>>>>> Groups "tesseract-ocr" group. >>>>>>>> To unsubscribe from this group and stop receiving emails from it, >>>>>>>> send an email to [email protected]. >>>>>>>> To view this discussion on the web visit >>>>>>>> https://groups.google.com/d/msgid/tesseract-ocr/8d80ed59-6163-48c9-adb8-975d8274a9adn%40googlegroups.com >>>>>>>> >>>>>>>> <https://groups.google.com/d/msgid/tesseract-ocr/8d80ed59-6163-48c9-adb8-975d8274a9adn%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>>>>> . >>>>>>>> >>>>>>> -- >>>>> You received this message because you are subscribed to the Google >>>>> Groups "tesseract-ocr" group. >>>>> To unsubscribe from this group and stop receiving emails from it, send >>>>> an email to [email protected]. >>>>> >>>> To view this discussion on the web visit >>>>> https://groups.google.com/d/msgid/tesseract-ocr/8749a458-6938-4894-aa67-804631b5139dn%40googlegroups.com >>>>> >>>>> <https://groups.google.com/d/msgid/tesseract-ocr/8749a458-6938-4894-aa67-804631b5139dn%40googlegroups.com?utm_medium=email&utm_source=footer> >>>>> . >>>>> >>>> -- >>> You received this message because you are subscribed to the Google >>> Groups "tesseract-ocr" group. >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected]. >>> >> To view this discussion on the web visit >>> https://groups.google.com/d/msgid/tesseract-ocr/83f7473f-a2c5-4d5c-8a45-450cb9a630c1n%40googlegroups.com >>> >>> <https://groups.google.com/d/msgid/tesseract-ocr/83f7473f-a2c5-4d5c-8a45-450cb9a630c1n%40googlegroups.com?utm_medium=email&utm_source=footer> >>> . >>> >> -- You received this message because you are subscribed to the Google Groups "tesseract-ocr" group. 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