我正在OCRing文档图像。我想检测所有图片并从文档图像中删除。我想在文档图像中保留表格。一旦检测到图片,我将删除并想要进行OCR。我试图找到试图检测所有较大区域的轮廓。不幸的是,它也检测到表。还有如何删除在文档图像中保留其他数据的对象。我正在使用opencv和python
这是我的代码
import os
from PIL import Image
import pytesseract
img = cv2.imread('block2.jpg' , 0)
mask = np.ones(img.shape[:2], dtype="uint8") * 255
ret,thresh1 = cv2.threshold(img,127,255,0)
contours, sd = cv2.findContours(thresh1,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
areacontainer = []
for cnt in contours:
area = cv2.contourArea(cnt)
areacontainer.append(area)
avgArea = sum(areacontainer)/len(areacontainer)
[enter code here][1]
for c in contours:# average area heuristics
if cv2.contourArea(c)>6*avgArea:
cv2.drawContours(mask, [c], -1, 0, -1)
binary = cv2.bitwise_and(img, img, mask=mask) # subtracting
cv2.imwrite("bin.jpg" , binary)
cv2.imwrite("mask.jpg" , mask)
答案 0 :(得分:0)
这是一种方法:
这里检测到的肖像以绿色突出显示
现在有了边界框ROI,我们可以通过用白色填充图片来有效地删除它们。这是结果
import cv2
image = cv2.imread('1.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blur = cv2.GaussianBlur(gray, (3,3), 0)
canny = cv2.Canny(blur, 120, 255, 1)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3,3))
close = cv2.morphologyEx(canny, cv2.MORPH_CLOSE, kernel, iterations=2)
cnts = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if len(cnts) == 2 else cnts[1]
for c in cnts:
area = cv2.contourArea(c)
if area > 15000 and area < 35000:
x,y,w,h = cv2.boundingRect(c)
cv2.rectangle(image, (x, y), (x + w, y + h), (255,255,255), -1)
cv2.imshow('image', image)
cv2.waitKey()