python 探测表格的横线和竖线，找到表格区域

Posted 2021-05-09

# coding: utf-8

import cv2 
 
class detectTable(object):
    def __init__(self, image):

        self.src_img = image

    def run(self):
        if len(self.src_img.shape) == 2:  # 灰度图
            gray_img = self.src_img
        elif len(self.src_img.shape) ==3:
            gray_img = cv2.cvtColor(self.src_img, cv2.COLOR_BGR2GRAY)

        # thresh_img = cv2.adaptiveThreshold(~gray_img,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,15,-2)

        thresh_img = cv2.Canny(gray_img, 50, 150, apertureSize=3)
        h_img = thresh_img.copy()
        v_img = thresh_img.copy()
        scale = 20
        h_size = int(h_img.shape[1]/scale)

        h_structure = cv2.getStructuringElement(cv2.MORPH_RECT,(h_size,1)) # 形态学因子
        h_erode_img = cv2.erode(h_img,h_structure,1)

        h_dilate_img = cv2.dilate(h_erode_img,h_structure,1)
        # cv2.imshow("h_erode",h_dilate_img)
        v_size = int(v_img.shape[0] / scale)

        v_structure = cv2.getStructuringElement(cv2.MORPH_RECT, (1, v_size))  # 形态学因子
        v_erode_img = cv2.erode(v_img, v_structure, 1)
        # cv2.imshow("v_erode_img",v_erode_img)
        v_dilate_img = cv2.dilate(v_erode_img, v_structure, 1)

        mask_img = h_dilate_img+v_dilate_img
        joints_img = cv2.bitwise_and(h_dilate_img,v_dilate_img)

    
        #在mask的基础上找边框
        thresh1, contours1, hierarchy1 = cv2.findContours(h_dilate_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        image_copy=self.src_img.copy()

        i=1
        predict_area=[]
        for cnt in contours1:
            x, y, w, h = cv2.boundingRect(cnt)
            if h>10 and w>12 and h<self.src_img.shape[0]-5 and w<self.src_img.shape[1]-5:
                predict_area.append((x-3,y-3,w+x+3,y+h+3))
        #         cv2.rectangle(image_copy, (x, y), (x + w, y + h), (0, 255, 0), 5)  # blue
                          
        cv2.imwrite("test.jpg",image_copy)
        cv2.imshow("h_dilate_img",h_dilate_img)
        cv2.imshow("mask",mask_img)
        cv2.imshow("image_copy",image_copy)
        
        cv2.waitKey(0)

        return predict_area

def main():
    temp_image=cv2.imread("./000217.png")
    cc=detectTable(temp_image).run()
    print(cc)


if __name__ == '__main__':
    main()