line detection

hough

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt
import glob
import imutils

img_rgb = cv.imread('/home/sdh/Downloads/multiscale-template-matching-master/images/newspaper3.jpg')
img_gray = cv.cvtColor(img_rgb, cv.COLOR_BGR2GRAY)
blank_image = np.zeros(shape=img_rgb.shape, dtype=np.uint8)

for i in glob.glob("templates" + "/*.png"):
	template = cv.imread('/home/sdh/Downloads/multiscale-template-matching-master/'+i,0)
	w, h = template.shape[::-1]
	res = cv.matchTemplate(img_gray,template,cv.TM_CCOEFF_NORMED)
	threshold = 0.8
	loc = np.where( res >= threshold)
	for pt in zip(*loc[::-1]):
		#cv.rectangle(blank_image, pt, (pt[0] + w, pt[1] + h), (0,0,255), -1)
		cv.circle(blank_image, (int(pt[0]+w/2), int(pt[1]+h/2)), 1, (0, 0, 255), -1)
cv.imwrite('res.png',blank_image)

#resized = imutils.resize(blank_image, width = int(blank_image.shape[1] * 0.25))
#resized = cv.resize(blank_image, (int(blank_image.shape[0]/4), int(blank_image.shape[1]/4)), interpolation = cv.INTER_AREA)

dst = cv.Canny(blank_image, 50, 200, None, 3)

linesP = cv.HoughLinesP(dst, 1, np.pi/180, 20, None, 20, 12)
newblank_image = np.zeros((dst.shape[0], dst.shape[1], 3), dtype=np.uint8)
if linesP is not None:
    for i in range(0, len(linesP)):
        l = linesP[i][0]
        angle = np.arctan2(l[1] - l[3], l[0] - l[2])
        deg = np.degrees([angle])
        if(deg[0] == 90.0 or deg[0] == 180.0):
          cv.line(img_rgb, (l[0], l[1]), (l[2], l[3]), (0,0,255), 3)

cv.imshow("Source", img_rgb)
cv.waitKey()