如何使用Pytesseract提取图像中的小数 [英] How to extract decimal in image with Pytesseract

问题描述

以上是图片，我已经尝试过可以从SO或google获得的所有内容，但似乎没有任何效果.我无法在image中获得确切的值，我应该得到2.10，而总是得到210.

Above is the image ,I have tried everything I could get from SO or google ,nothing seems to work. I can not get the exact value in image , I should get 2.10 , Instead it always get 210.

并且不仅限于此图像，任何在数字1 tesseract之前具有十进制的图像都将忽略该十进制值.

And it is not limited to this image only any image which have a decimal before number 1 tesseract ignores the decimal value.

 def returnAllowedAmount(self,imgpath):
        th = 127
        max_val = 255
        img = cv2.imread(imgpath,0) #Load Image in Memory
        img = cv2.resize(img, None, fx=2.5, fy=2.5, interpolation=cv2.INTER_CUBIC) #rescale Image
        img = cv2.medianBlur(img, 1)
        ret , img = cv2.threshold(img,th,max_val,cv2.THRESH_TOZERO)
        self.showImage(img)

        returnData = pytesseract.image_to_string(img,lang='eng',config='-psm 13 ' )
        returnData = ''.join(p for p in returnData if p.isnumeric() or p == ".") # REMOVE $ SIGN

推荐答案

在将图像放入Pytesseract之前，进行一些清理/平滑图像的预处理会有所帮助.这是一种简单的方法

Before throwing the image into Pytesseract, some preprocessing to clean/smooth the image helps. Here's a simple approach

• 将图像转换为灰度并放大图像
• 阈值
• 执行形态学操作以清洁图像
• 反转图像

首先，我们将图像转换为灰度，然后使用 imutils 库调整大小，然后将阈值设置为获取二进制图像

First we convert the image to grayscale, resize using the imutils library then threshold to obtain a binary image

现在，我们执行形态转换平滑图像

Now we perform morphological transformations to smooth the image

现在，我们将Pytesseract的图像反转并添加高斯模糊

Now we invert the image for Pytesseract and add a Gaussian blur

我们使用--psm 10 config标志，因为我们希望将图像视为单个字符.这是一些有用的其他配置标志

We use the --psm 10 config flag since we want to treat the image as a single character. Here's some additional configuration flags that could be useful

结果

2.10美元

$2.10

过滤后

2.10

2.10

import cv2
import pytesseract
import imutils

pytesseract.pytesseract.tesseract_cmd = r"C:\Program Files\Tesseract-OCR\tesseract.exe"

image = cv2.imread('1.png',0)
image = imutils.resize(image, width=300)
thresh = cv2.threshold(image, 150, 255, cv2.THRESH_BINARY_INV)[1]

kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
close = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)

result = 255 - close 
result = cv2.GaussianBlur(result, (5,5), 0)

data = pytesseract.image_to_string(result, lang='eng',config='--psm 10 ')
processed_data = ''.join(char for char in data if char.isnumeric() or char == '.')
print(data)
print(processed_data)

cv2.imshow('thresh', thresh)
cv2.imshow('close', close)
cv2.imshow('result', result)
cv2.waitKey()

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