def test_hsobel_horizontal():
"""Horizontal Sobel on an edge should be a horizontal line."""
i, j = np.mgrid[-5:6, -5:6]
image = (i >= 0).astype(float)
result = filters.hsobel(image)
# Fudge the eroded points
i[np.abs(j) == 5] = 10000
assert (np.all(result[i == 0] == 1))
assert (np.all(result[np.abs(i) > 1] == 0))
"""
Created on Tue Jun 13 19:56:42 2017
@author: user
"""
import matplotlib.pyplot as plt
import numpy as np
from skimage import filters as filters
import skimage.io as io
import scipy.ndimage as ndi
from skimage import feature
w = io.imread('x-ray.jpg', "gray")
wh = filters.hsobel(w)
wv = filters.vsobel(w)
wall = filters.sobel(w)
fig = plt.figure(figsize=(15, 8))
ax1 = fig.add_subplot(2, 2, 1)
io.imshow(w)
plt.title('original', fontsize=10)
ax1 = fig.add_subplot(2, 2, 2)
plt.imshow(wh * 10, 'gray')
plt.title('Sobel (x direction)', fontsize=10)
ax1 = fig.add_subplot(2, 2, 3)
plt.imshow(wv * 10, 'gray')
plt.title('Sobel (y direction)', fontsize=10)
ax1 = fig.add_subplot(2, 2, 4)
plt.imshow(wall * 10, 'gray')
plt.title('Sobel filter', fontsize=10)
# filter 1: horizontal Sobel filter import matplotlib.pyplot as plt from skimage import data , filters camera = data.camera() hsobel_camera = filters.hsobel(camera) plt.figure(figsize=(8, 4)) plt.subplot(121) plt.imshow(camera) plt.subplot(122) plt.imshow(hsobel_camera) plt.tight_layout() plt.show()
def test_hsobel_vertical():
"""Horizontal Sobel on a vertical edge should be zero."""
i, j = np.mgrid[-5:6, -5:6]
image = (j >= 0).astype(float) * np.sqrt(2)
result = filters.hsobel(image)
assert_allclose(result, 0, atol=1e-10)
def test_hsobel_mask():
"""Horizontal Sobel on a masked array should be zero."""
np.random.seed(0)
result = filters.hsobel(np.random.uniform(size=(10, 10)),
np.zeros((10, 10), bool))
assert (np.all(result == 0))
def test_hsobel_zeros():
"""Horizontal sobel on an array of all zeros."""
result = filters.hsobel(np.zeros((10, 10)), np.ones((10, 10), bool))
assert (np.all(result == 0))
"""
Computing horizontal gradients with the Sobel filter
=====================================================
This example illustrates the use of the horizontal Sobel filter, to compute
horizontal gradients.
"""
from skimage import data
# scikit-image has changes its API
try:
from skimage import filters
except ImportError:
from skimage import filter as filters
import matplotlib.pyplot as plt
text = data.text()
hsobel_text = filters.hsobel(text)
plt.figure(figsize=(12, 3))
plt.subplot(121)
plt.imshow(text, cmap='gray', interpolation='nearest')
plt.axis('off')
plt.subplot(122)
plt.imshow(hsobel_text, cmap='spectral', interpolation='nearest')
plt.axis('off')
plt.tight_layout()
plt.show()
