I am trying to detect some numbers with tesseract in python. Below you will find my starting image and what I can get it down to. Here is the code I used to get it there.

我正在尝试在python中使用tesseract检测一些数字。下面你会发现我的开始图像，以及我可以把它降到什么。这是我用来把它弄到那里的代码。

import pytesseract
import cv2
import numpy as np
pytesseract.pytesseract.tesseract_cmd = "C:\\Users\\choll\\AppData\\Local\\Programs\\Tesseract-OCR\\tesseract.exe"

image = cv2.imread(r'64normalwart.png')
lower = np.array([254, 254, 254])
upper = np.array([255, 255, 255])
image = cv2.inRange(image, lower, upper)
image = cv2.bitwise_not(image)
#Uses a language that should work with minecraft text, I have tried with and without, no luck 
text = pytesseract.image_to_string(image, lang='mc')
print(text)
cv2.imwrite("Wartthreshnew.jpg", image)
cv2.imshow("Image", image)
cv2.waitKey(0)

I end up with black numbers on a white background which seems pretty good but tesseract can still not detect the numbers. I also noticed the numbers were pretty jagged but I don't know how to fix that. Does anyone have recommendations for how I could make tesseract be able to recognize these numbers?

我最终得到了白色背景上的黑色数字，这看起来很好，但tesseract仍然无法检测到数字。我也注意到这些数字相当参差不齐，但我不知道如何解决这个问题。有没有人建议我如何让tesseract能够识别这些数字？

Starting Image

启动图像

What I end up with

我最终得到的是什么

Your problem is with the page segmentation mode. Tesseract segments every image in a different way. When you don't choose an appropriate PSM, it goes for mode 3, which is automatic and might not be suitable for your case. I've just tried your image and it works perfectly with PSM 6.

您的问题出在页面分割模式上。Tesseract以不同的方式对每个图像进行分割。如果您没有选择合适的PSM，则会选择模式3，该模式是自动的，可能不适合您的情况。我刚刚试过你的图像，它和PSM 6完美地搭配在一起。

df = pytesseract.image_to_string(np.array(image),lang='eng', config='--psm 6')

These are all PSMs availabe at this moment:

这些都是目前可用的PSM：

  0    Orientation and script detection (OSD) only.
  1    Automatic page segmentation with OSD.
  2    Automatic page segmentation, but no OSD, or OCR.
  3    Fully automatic page segmentation, but no OSD. (Default)
  4    Assume a single column of text of variable sizes.
  5    Assume a single uniform block of vertically aligned text.
  6    Assume a single uniform block of text.
  7    Treat the image as a single text line.
  8    Treat the image as a single word.
  9    Treat the image as a single word in a circle.
 10    Treat the image as a single character.
 11    Sparse text. Find as much text as possible in no particular order.
 12    Sparse text with OSD.
 13    Raw line. Treat the image as a single text line,
            bypassing hacks that are Tesseract-specific.

Use the pytesseract.image_to_string(img, config='--psm 8') or try diffrent configs to see if the image will get recognized. Useful link here Pytesseract OCR multiple config options

使用pytesseract.IMAGE_TO_STRING(img，CONFIG=‘--PSM 8’)或尝试不同的配置，以查看是否可以识别映像。此处提供了有用的链接，其中包含多个配置选项

I think tesseract is blacklisted numbers by default, so i tried tessedit_char_whitelist to whitelist the characters i want but it didn't work, so i tried to un-blacklist the numbers using this config tessedit_char_unblacklist='0123456789'

我认为tesseract默认情况下是被列入黑名单的数字，所以我尝试tessedit_char_White elist将我想要的字符列入白名单，但它不起作用，所以我尝试使用此配置将数字取消黑名单。tessedit_char_unBlacklist=‘0123456789’

pytesseract.image_to_string(img, lang='eng', config='--psm 6 --oem 3 -c tessedit_char_unblacklist=0123456789')