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fixed plot in plot_glcm.py

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Siva Prasad Varma
2014-03-14 21:41:02 +05:30
parent f4bef8d5c8
commit c2e380cf34
1 changed files with 32 additions and 29 deletions
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doc/examples/plot_glcm.py
+32 -29
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@@ -53,41 +53,44 @@ for i, patch in enumerate(grass_patches + sky_patches):
ys.append(greycoprops(glcm, 'correlation')[0, 0])
# create the figure
fig, ax = plt.subplots(3, 4, figsize=(8, 8))
fig = plt.figure(figsize=(8, 8))
# display original image with locations of patches
ax = fig.add_subplot(3, 2, 1)
ax.imshow(image, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
for (y, x) in grass_locations:
ax.plot(x + PATCH_SIZE / 2, y + PATCH_SIZE / 2, 'gs')
for (y, x) in sky_locations:
ax.plot(x + PATCH_SIZE / 2, y + PATCH_SIZE / 2, 'bs')
ax.set_xlabel('Original Image')
ax.set_xticks([])
ax.set_yticks([])
ax.axis('image')
# for each patch, plot (dissimilarity, correlation)
ax = fig.add_subplot(3, 2, 2)
ax.plot(xs[:len(grass_patches)], ys[:len(grass_patches)], 'go',
label='Grass')
ax.plot(xs[len(grass_patches):], ys[len(grass_patches):], 'bo',
label='Sky')
ax.set_xlabel('GLCM Dissimilarity')
ax.set_ylabel('GLVM Correlation')
ax.legend()
# display the image patches
for i, patch in enumerate(grass_patches):
ax[1, i].imshow(patch, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
ax[1, i].set_xlabel('Grass %d' % (i + 1))
ax = fig.add_subplot(3, 4, 4+i+1)
ax.imshow(patch, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
ax.set_xlabel('Grass %d' % (i + 1))
for i, patch in enumerate(sky_patches):
ax[2, i].imshow(patch, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
ax[2, i].set_xlabel('Sky %d' % (i + 1))
ax = fig.add_subplot(3, 4, 4*2+i+1)
ax.imshow(patch, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
ax.set_xlabel('Sky %d' % (i + 1))
# display original image with locations of patches
ax1 = fig.add_subplot(321)
ax1.imshow(image, cmap=plt.cm.gray, interpolation='nearest',
vmin=0, vmax=255)
for (y, x) in grass_locations:
ax1.plot(x + PATCH_SIZE / 2, y + PATCH_SIZE / 2, 'gs')
for (y, x) in sky_locations:
ax1.plot(x + PATCH_SIZE / 2, y + PATCH_SIZE / 2, 'bs')
ax1.set_xlabel('Original Image')
ax1.set_xticks([])
ax1.set_yticks([])
ax1.axis('image')
# for each patch, plot (dissimilarity, correlation)
ax2 = fig.add_subplot(322)
ax2.plot(xs[:len(grass_patches)], ys[:len(grass_patches)], 'go',
label='Grass')
ax2.plot(xs[len(grass_patches):], ys[len(grass_patches):], 'bo',
label='Sky')
ax2.set_xlabel('GLCM Dissimilarity')
ax2.set_ylabel('GLVM Correlation')
ax2.legend()
# display the patches and plot
fig.suptitle('Grey level co-occurrence matrix features', fontsize=14)