newspaper article segment into different parapgraphs stackoverflow
grad_x = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=3)
grad_y = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=3)
abs_grad_x = cv2.convertScaleAbs(grad_x)
abs_grad_y = cv2.convertScaleAbs(grad_y)
# threshold
thresh_x = cv2.threshold(abs_grad_x, 0, 255, cv2.THRESH_OTSU)[1]
thresh_y = cv2.threshold(abs_grad_y, 0, 255, cv2.THRESH_OTSU)[1]
# bluring
kernel_size = 3
blur_thresh_x = cv2.GaussianBlur(thresh_x,(kernel_size, kernel_size),0)
blur_thresh_y = cv2.GaussianBlur(thresh_y,(kernel_size, kernel_size),0)
# Run Hough on edge detected image
rho = 1 # distance resolution in pixels of the Hough grid
theta = np.pi / 180 # angular resolution in radians of the Hough grid
threshold = 15 # minimum number of votes (intersections in Hough grid cell)
min_line_length = 200 # minimum number of pixels making up a line
max_line_gap = 1 # maximum gap in pixels between connectable line segments
line_image = np.copy(gray) * 0 # creating a blank to draw lines on
# Vertical lines
vertical_lines = cv2.HoughLinesP(blur_thresh_x, rho, theta, threshold, np.array([]), min_line_length, max_line_gap)
if vertical_lines is not None:
for line in vertical_lines:
for x1,y1,x2,y2 in line:
# here it's possible to add a selection of only vertical lines
if np.abs(y1-y2)> 0.1 * np.abs(x1-x2):
cv2.line(line_image,(x1,y1),(x2,y2),255,5)
# Horizontal lines
horizontal_lines = cv2.HoughLinesP(blur_thresh_y, rho, theta, threshold, np.array([]), min_line_length, max_line_gap)
if horizontal_lines is not None:
for line in horizontal_lines:
for x1,y1,x2,y2 in line:
# here it's possible to add a selection of only horizontal lines
if np.abs(x1-x2)> 0.1 * np.abs(y1-y2):
cv2.line(line_image,(x1,y1),(x2,y2),255,5)