#!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = "heider"
__doc__ = r"""
Created on 5/5/22
"""
from pathlib import Path
import numpy
from matplotlib import cm, pyplot
from skimage import color, io
from skimage.draw import line
from skimage.transform import hough_line, hough_line_peaks
if __name__ == "__main__":
def aushd():
"""description"""
file = "3.jpg"
# file = "NdNLO.jpg"
# image = cv2.imread(str(Path.home() / "Pictures" / file))
# Constructing test image
image = color.rgb2gray(io.imread(str(Path.home() / "Pictures" / file)))
# Classic straight-line Hough transform
# Set a precision of 0.05 degree.
tested_angles = numpy.linspace(-numpy.pi / 2, numpy.pi / 2, 3600)
h, theta, d = hough_line(image, theta=tested_angles)
hpeaks = hough_line_peaks(h, theta, d, threshold=0.2 * h.max())
fig, ax = pyplot.subplots()
ax.imshow(image, cmap=cm.gray)
for _, angle, dist in zip(*hpeaks):
(x0, y0) = dist * numpy.array([numpy.cos(angle), numpy.sin(angle)])
ax.axline((x0, y0), slope=numpy.tan(angle + numpy.pi / 2))
pyplot.show()
[docs]def auishd():
"""description"""
# Constructing test image
image = numpy.zeros((200, 200))
idx = numpy.arange(25, 175)
image[idx, idx] = 255
image[line(45, 25, 25, 175)] = 255
image[line(25, 135, 175, 155)] = 255
# Classic straight-line Hough transform
# Set a precision of 0.5 degree.
tested_angles = numpy.linspace(-numpy.pi / 2, numpy.pi / 2, 360, endpoint=False)
h, theta, d = hough_line(image, theta=tested_angles)
# Generating figure 1
fig, axes = pyplot.subplots(1, 3, figsize=(15, 6))
ax = axes.ravel()
ax[0].imshow(image, cmap=cm.gray)
ax[0].set_title("Input image")
ax[0].set_axis_off()
angle_step = 0.5 * numpy.diff(theta).mean()
d_step = 0.5 * numpy.diff(d).mean()
bounds = [
numpy.rad2deg(theta[0] - angle_step),
numpy.rad2deg(theta[-1] + angle_step),
d[-1] + d_step,
d[0] - d_step,
]
ax[1].imshow(numpy.log(1 + h), extent=bounds, cmap=cm.gray, aspect=1 / 1.5)
ax[1].set_title("Hough transform")
ax[1].set_xlabel("Angles (degrees)")
ax[1].set_ylabel("Distance (pixels)")
ax[1].axis("image")
ax[2].imshow(image, cmap=cm.gray)
ax[2].set_ylim((image.shape[0], 0))
ax[2].set_axis_off()
ax[2].set_title("Detected lines")
for _, angle, dist in zip(*hough_line_peaks(h, theta, d)):
(x0, y0) = dist * numpy.array([numpy.cos(angle), numpy.sin(angle)])
ax[2].axline((x0, y0), slope=numpy.tan(angle + numpy.pi / 2))
pyplot.tight_layout()
pyplot.show()
auishd()
