問題描述
上面是圖片，我已經嘗試了從 SO 或 google 獲得的一切，似乎沒有任何效果.我無法在圖像中得到確切的值，我應該得到 2.10，而不是總是得到 210.
并且不僅限于此圖像，只有在數字 1 tesseract 之前具有小數的任何圖像都會忽略十進制值.
def returnAllowedAmount(self,imgpath):th = 127最大值 = 255img = cv2.imread(imgpath,0) #在內存中加載圖片img = cv2.resize(img, None, fx=2.5, fy=2.5, interpolation=cv2.INTER_CUBIC) #rescale Imageimg = 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在將圖像放入 Pytesseract 之前，一些預處理以清理/平滑圖像會有所幫助.這是一個簡單的方法
- 將圖像轉換為灰度并放大圖像
- 門檻
- 執行形態學操作以清潔圖像
- 反轉圖像
首先我們將圖像轉換為灰度，使用
現在我們執行
現在我們為 Pytesseract 反轉圖像并添加高斯模糊
我們使用 --psm 10 配置標志，因為我們希望將圖像視為單個字符.以下是一些可能有用的額外配置標志
結果
<塊引用>2.10 美元
過濾后
<塊引用>2.10
導入 cv2導入 pytesseract導入 imutilspytesseract.pytesseract.tesseract_cmd = r"C:Program FilesTesseract-OCR esseract.exe"圖像 = cv2.imread('1.png',0)圖像 = imutils.resize(圖像，寬度 = 300)thresh = cv2.threshold(圖像, 150, 255, cv2.THRESH_BINARY_INV)[1]內核 = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))關閉 = cv2.morphologyEx(閾值，cv2.MORPH_CLOSE，內核)結果 = 255 - 關閉結果 = cv2.GaussianBlur(結果, (5,5), 0)數據 = pytesseract.image_to_string(結果，lang='eng'，config='--psm 10')processes_data = ''.join(char for char in data if char.isnumeric() or char == '.')打印(數據)打印(已處理數據)cv2.imshow('thresh', thresh)cv2.imshow('關閉'，關閉)cv2.imshow('結果', 結果)cv2.waitKey()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.
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
Before throwing the image into Pytesseract, some preprocessing to clean/smooth the image helps. Here's a simple approach
- Convert image to grayscale and enlarge image
- Threshold
- Perform morphological operations to clean image
- Invert image
First we convert the image to grayscale, resize using the imutils library then threshold to obtain a binary image
Now we perform morphological transformations to smooth the image
Now we invert the image for Pytesseract and add a Gaussian blur
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
Results
$2.10
After filtering
2.10
import cv2
import pytesseract
import imutils
pytesseract.pytesseract.tesseract_cmd = r"C:Program FilesTesseract-OCR esseract.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()
這篇關于如何使用 Pytesseract 提取圖像中的小數點的文章就介紹到這了，希望我們推薦的答案對大家有所幫助，也希望大家多多支持html5模板網！