python - 如何从图像中准确提取数据？使用 PyTesseract

Question

我正在尝试使用 python 从图像中准确提取文本。

这是我在这种情况下使用的图像:

这是我的python文件:

from PIL import Image
import pytesseract

pytesseract.pytesseract.tesseract_cmd = r'C:\Users\test\AppData\Roaming\Python\Python37\site-packages\tesseract.exe'

img=Image.open('C:/Users/test/Desktop/Everything else/work/Almonds.jpg')

text = pytesseract.image_to_string(img, lang = 'eng')


print(text)

这是我在命令提示符下运行 python 文件时的输出:

INGREDIENTS: Almonds: [Nuts] Allergy Advice:
For allergens, see ingredients in Bold

Nutritional Information
TYPICALVALUES Per 100g

Energy kJ 2597.0}
Energy kcal 626.0)
Fat 50.6g|

of which Saturates 3.9g

Carbohy drate 19.7g

of which Sugars 4.89|
Fibre 3.59
Protein 21.3g|

May contain traces of
other nuts, peanut,
sesame or gluten

This product may contain
pieces of shell

Store in a cool dry place
jout of direct sunlight

Net weight:



Salt 0.ig

For Best Before & Batch see pack 1 k

如您所见，并非所有文本都拼写正确。有什么建议可以提高文本输出的准确性吗？

额外

这是我想要实现的目标的想法，与问题无关，但让您了解我在这里想要实现的目标。

我有多个产品图像文件，我将在其中与 Excel 表格进行比较。

Excel 工作表的格式如下(1 个示例数据):

Product Code: 0001
Product Desc: Californian Whole Almonds
Ingredients: Almonds: [Nuts]
Allergy Advice: True
etc...

然后我将编写一个脚本来检测图像文件中的文本，将其与 Excel 工作表进行比较并分析每个部分是否匹配在一起，给出“真”或“假”的输出

Answer 1

在将图像放入 Pytesseract 之前预处理图像以平滑/去除噪声会有所帮助。也许删除水平/垂直线会改善检测

import cv2

image = cv2.imread('1.jpg',0)
thresh = cv2.threshold(image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)[1]

# Remove horizontal lines
horizontal_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25,1))
detect_horizontal = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, horizontal_kernel, iterations=2)
cnts = cv2.findContours(detect_horizontal, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
cv2.fillPoly(thresh, cnts, [0,0,0])

# Remove vertical lines
vertical_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (1,45))
detect_vertical = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, vertical_kernel, iterations=2)
cnts = cv2.findContours(detect_vertical, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
cv2.fillPoly(thresh, cnts, [0,0,0])

result = 255 - thresh

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