[英]How to improve the OCR accuracy in this image?
I am going to extract text from a picture using OpenCV in Python and OCR by pytesseract
.我将使用 Python 中的
pytesseract
和 pytesseract 的 OCR 从图片中提取文本。 I have an image like this:我有这样的图像:
Then I have written some code to extract the text from that picture, nut it does not have enough accuracy to extract the text properly.然后我写了一些代码来从那张图片中提取文本,但是它没有足够的准确性来正确提取文本。
That is my code:那是我的代码:
import cv2
import pytesseract
img = cv2.imread('photo.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
_,img = cv2.threshold(img,110,255,cv2.THRESH_BINARY)
custom_config = r'--oem 3 --psm 6'
text = pytesseract.image_to_string(img, config=custom_config)
print(text)
cv2.imshow('pic', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
I have tested cv2.adaptiveThreshold
, but it does not work like cv2.threshold
.我已经测试
cv2.adaptiveThreshold
,但它不像cv2.threshold
那样工作。
And, finally, this is my result which is does not like my result in the picture:最后,这是我的结果,与图片中的结果不同:
Color Yellow RBC/hpf 4-6
Appereance Semi Turbid WBC/hpf 2-3
Specific Gravity 1014 Epithelial cells/Lpf 1-2
PH 7 Bacteria (Few)
Protein Pos(+) Casts Negative
Glucose Negative Mucous (Few)
Keton Negative
Blood Pos(+)
Bilirubin Negative
Urobilinogen Negative
Nigitesse 5 ed eg ative
Do you have any way to improve the accuracy?你有什么方法可以提高准确性吗?
I was actually quite surprised, how good the result already is, seeing this noticable skew.看到这个明显的偏差,我实际上很惊讶,结果已经有多好。 But, that's not the actual problem with the last line, but the shadow: This is your thresholded image:
但是,这不是最后一行的实际问题,而是阴影:这是您的阈值图像:
So, pytesseract
has no chance to properly detect anything meaningful from the last line.因此,
pytesseract
没有机会从最后一行正确检测到任何有意义的内容。 Let's try to remove the shadow, following Dan Mašek's answer here , and let Otsu do the thresholding:让我们按照Dan Mašek 在此处的回答尝试移除阴影,并让 Otsu 进行阈值处理:
import cv2
import numpy as np
import pytesseract
# Read input image, convert to grayscale
img = cv2.imread('NiVUK.jpg')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Remove shadows, cf. https://stackoverflow.com/a/44752405/11089932
dilated_img = cv2.dilate(gray, np.ones((7, 7), np.uint8))
bg_img = cv2.medianBlur(dilated_img, 21)
diff_img = 255 - cv2.absdiff(gray, bg_img)
norm_img = cv2.normalize(diff_img, None, alpha=0, beta=255,
norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)
# Threshold using Otsu's
work_img = cv2.threshold(norm_img, 0, 255, cv2.THRESH_OTSU)[1]
# Tesseract
custom_config = r'--oem 3 --psm 6'
text = pytesseract.image_to_string(work_img, config=custom_config)
print(text)
The shadow-removed, thresholded image looks like this:去除阴影的阈值图像如下所示:
And, the final output seems to be correct to me:而且,最终的 output 对我来说似乎是正确的:
Color Yellow RBC/hpf 4-6
Appereance Semi Turbid WBC/hpf 2-3
Specific Gravity 1014 Epithelial cells/Lpf 1-2
PH 7 Bacteria (Few)
Protein Pos(+) Casts Negative
Glucose Negative Mucous (Few)
Keton Negative
Blood Pos(+)
Bilirubin Negative
Urobilinogen Negative
Nitrite Negative
----------------------------------------
System information
----------------------------------------
Platform: Windows-10-10.0.16299-SP0
Python: 3.9.1
PyCharm: 2021.1.1
NumPy: 1.20.2
OpenCV: 4.5.1
pytesseract: 4.00.00alpha
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