wassname/scikit-image
1
0
Fork 0
mirror of https://github.com/wassname/scikit-image.git synced 2026-07-27 11:27:08 +08:00
Code Issues Packages Projects Releases Wiki Activity

used plt.subplots everywhere

Browse Source
This commit is contained in:
Siva Prasad Varma
2014-03-14 17:37:14 +05:30
parent c60d15f2f4
commit fb72fb04b2
22 changed files with 350 additions and 405 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/examples/plot_line_hough_transform.py
+25 -26
View File
@@ -77,30 +77,30 @@ image[idx, idx] = 255
h, theta, d = hough_line(image)
plt.figure(figsize=(8, 4))
f, ax = plt.subplots(1, 3, figsize=(8, 4))
plt.subplot(131)
plt.imshow(image, cmap=plt.cm.gray)
plt.title('Input image')
ax[0].imshow(image, cmap=plt.cm.gray)
ax[0].set_title('Input image')
ax[0].axis('image')
plt.subplot(132)
plt.imshow(np.log(1 + h),
ax[1].imshow(np.log(1 + h),
extent=[np.rad2deg(theta[-1]), np.rad2deg(theta[0]),
d[-1], d[0]],
cmap=plt.cm.gray, aspect=1/1.5)
plt.title('Hough transform')
plt.xlabel('Angles (degrees)')
plt.ylabel('Distance (pixels)')
ax[1].set_title('Hough transform')
ax[1].set_xlabel('Angles (degrees)')
ax[1].set_ylabel('Distance (pixels)')
ax[1].axis('image')
plt.subplot(133)
plt.imshow(image, cmap=plt.cm.gray)
ax[2].imshow(image, cmap=plt.cm.gray)
rows, cols = image.shape
for _, angle, dist in zip(*hough_line_peaks(h, theta, d)):
y0 = (dist - 0 * np.cos(angle)) / np.sin(angle)
y1 = (dist - cols * np.cos(angle)) / np.sin(angle)
plt.plot((0, cols), (y0, y1), '-r')
plt.axis((0, cols, rows, 0))
plt.title('Detected lines')
ax[2].plot((0, cols), (y0, y1), '-r')
ax[2].axis((0, cols, rows, 0))
ax[2].set_title('Detected lines')
ax[2].axis('image')
# Line finding, using the Probabilistic Hough Transform
@@ -108,23 +108,22 @@ image = data.camera()
edges = canny(image, 2, 1, 25)
lines = probabilistic_hough_line(edges, threshold=10, line_length=5, line_gap=3)
plt.figure(figsize=(8, 3))
f2, ax = plt.subplots(1, 3, figsize=(8, 3))
plt.subplot(131)
plt.imshow(image, cmap=plt.cm.gray)
plt.title('Input image')
ax[0].imshow(image, cmap=plt.cm.gray)
ax[0].set_title('Input image')
ax[0].axis('image')
plt.subplot(132)
plt.imshow(edges, cmap=plt.cm.gray)
plt.title('Canny edges')
ax[1].imshow(edges, cmap=plt.cm.gray)
ax[1].set_title('Canny edges')
ax[1].axis('image')
plt.subplot(133)
plt.imshow(edges * 0)
ax[2].imshow(edges * 0)
for line in lines:
p0, p1 = line
plt.plot((p0[0], p1[0]), (p0[1], p1[1]))
ax[2].plot((p0[0], p1[0]), (p0[1], p1[1]))
plt.title('Probabilistic Hough')
plt.axis('image')
ax[2].set_title('Probabilistic Hough')
ax[2].axis('image')
plt.show()