pytesseract无法识别图像中的数字 [英] pytesseract fail to recognise digits from image

问题描述

我有此python代码，可用于将写在图片中的文本转换为字符串，它确实适用于某些字符较大的图像，但不适用于我现在尝试的仅包含数字的图像

I've this python code which i use to convert a text written in a picture to a string, it does work for certain images whom have large characters, but not for the one i'm trying right now which contains only digits.

有我的代码:

from PIL import Image


img = Image.open('img.png')
pytesseract.pytesseract.tesseract_cmd = 'C:/Program Files (x86)/Tesseract-OCR/tesseract'
result = pytesseract.image_to_string(img)
print (result)

为什么无法识别此特定图像，我该如何解决此问题?谢谢.

Why is it failing recognising this specific image and how can i solve this problem ? thank you.

有图片:

推荐答案

我有两个建议.

首先，这是迄今为止最重要的，在OCR预处理中，图像是获得良好结果的关键.对于您的情况，我建议进行二值化.您的图像看起来非常好，因此您应该不会有任何问题，但是如果这样做，那么也许应该尝试对图像进行二值化:

First, and this is by far the most important, in OCR preprocessing images is key to obtaining good results. In your case I suggest binarization. Your images look extremely good so you shouldn't have any problem but if you do, then maybe you should try to binarize your images:

import cv2
from PIL import Image

img = cv2.imread('gradient.png')
# If your image is not already grayscale :
# img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
threshold = 180 # to be determined
_, img_binarized = cv2.threshold(img, threshold, 255, cv2.THRESH_BINARY)
pil_img = Image.fromarray(img_binarized)

然后使用二值化图像再次尝试ocr.

And then try the ocr again with the binarized image.

检查图像是否为灰度图像，并在需要时取消注释.

Check if your image is in grayscale and uncomment if needed.

这是简单的阈值处理.自适应阈值处理也存在，但是它很嘈杂，不会给您带来任何影响.

This is simple thresholding. Adaptive thresholding also exists but it is noisy and does not bring anything in your case.

二元化的图像将更易于Tesseract处理.这已经在内部完成( https://github.com/tesseract-ocr/tesseract/wiki/ImproveQuality )，但有时事情可能会变得混乱，通常对自己进行预处理很有用.

Binarized images will be much easier for Tesseract to handle. This is already done internally (https://github.com/tesseract-ocr/tesseract/wiki/ImproveQuality) but sometimes things can be messed up and very often it's useful to do your own preprocessing.

您可以通过查看图像来检查阈值是否正确:

You can check if the threshold value is right by looking at the images :

import matplotlib.pyplot as plt
plt.imshow(img, cmap='gray')
plt.imshow(img_binarized, cmap='gray')

第二，如果我上面所说的仍然不起作用，我知道这不会回答为什么pytesseract在这里不起作用"，但我建议您尝试使用tesserocr.它是Tesseract的维护的python包装器.

Second, if what I said above still doesn't work, I know this doesn't answer "why doesn't pytesseract work here" but I suggest you try out tesserocr. It is a maintained python wrapper for Tesseract.

您可以尝试:

import tesserocr
text_from_ocr = tesserocr.image_to_text(pil_img)

这是来自pypi的tesserocr的文档: https://pypi.org/project/tesserocr/

Here is the doc for tesserocr from pypi : https://pypi.org/project/tesserocr/

对于opencv: https://pypi.org/project/opencv-python/

作为旁注，在Tesseract中对黑白进行了对称处理，因此在黑色背景上具有白色数字并不是问题.

As a side-note, black and white is treated symetrically in Tesseract so having white digits on a black background is not a problem.

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