#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "heider"
__doc__ = r"""
Created on 5/5/22
"""
from typing import Any
import cv2
import numpy
from draugr.opencv_utilities import ThresholdTypeFlag, show_image, to_gray
__all__ = ["hough_lines"]
[docs]def hough_lines(
img,
kernel_size=11,
sigma=1.4, # 0
aperture_size=3,
rho=1,
theta=numpy.pi / 180,
min_votes=99,
lines=100,
min_line_length=10,
max_line_gap=250,
debug: bool = False,
) -> Any:
"""
:param img:
:type img:
:param kernel_size:
:type kernel_size:
:param sigma:
:type sigma:
:param aperture_size:
:type aperture_size:
:param rho:
:type rho:
:param theta:
:type theta:
:param min_votes:
:type min_votes:
:param lines:
:type lines:
:param min_line_length:
:type min_line_length:
:param max_line_gap:
:type max_line_gap:
:param debug:
:type debug:
:return:
:rtype:
"""
gray = to_gray(img)
if True: # remove noise
# gray = cv2.medianBlur(gray, kernel_size)
gray = cv2.GaussianBlur(gray, (kernel_size, kernel_size), sigma)
if False:
if False:
edges = cv2.Canny(
gray, threshold1=50, threshold2=200, apertureSize=aperture_size
)
else:
adapt_type = cv2.ADAPTIVE_THRESH_GAUSSIAN_C
thresh_type = cv2.THRESH_BINARY_INV
edges = cv2.adaptiveThreshold(gray, 255, adapt_type, thresh_type, 11, 2)
else:
laplacian = cv2.Laplacian(
gray, cv2.CV_8UC1, ksize=3
) # ,cv2.CV_16UC1, #cv2.CV_16S, # cv2.CV_64F
# blurryness = resLap.var()
# sobelx = cv.Sobel(img, cv.CV_64F, 1, 0, ksize=5)
# sobely = cv.Sobel(img, cv.CV_64F, 0, 1, ksize=5)
edges = cv2.threshold(
laplacian,
0,
255,
ThresholdTypeFlag.otsu.value
+ ThresholdTypeFlag.binary.value, # ThresholdTypeFlag.to_zero.value
)[1]
if True:
lines = cv2.HoughLinesP(
edges,
rho=rho,
theta=theta,
threshold=min_votes,
minLineLength=min_line_length,
maxLineGap=max_line_gap,
)
else:
lines = None
if debug:
show_image(gray)
# show_image(laplacian)
show_image(edges, wait=True)
if False:
for line in lines: # Draw lines on the image
x1, y1, x2, y2 = line[0]
cv2.line(img, (x1, y1), (x2, y2), (255, 0, 0), 3)
return lines
