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https://github.com/wassname/scikit-image.git
synced 2026-07-30 12:31:08 +08:00
changed subplot creation to preferred matplotlib style
This commit is contained in:
martin
@@ -70,24 +70,31 @@ noisy_image = img_as_ubyte(data.camera())
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noisy_image[noise > 0.99] = 255
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noisy_image[noise < 0.01] = 0
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fig, ax = plt.subplots(2, 2, figsize=(10, 7), sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, figsize=(10, 7), sharex=True, sharey=True)
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.imshow(noisy_image, vmin=0, vmax=255, cmap=plt.cm.gray)
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ax1.set_title('Noisy image')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(median(noisy_image, disk(1)), vmin=0, vmax=255, cmap=plt.cm.gray)
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ax2.set_title('Median $r=1$')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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ax3.imshow(median(noisy_image, disk(5)), vmin=0, vmax=255, cmap=plt.cm.gray)
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ax3.set_title('Median $r=5$')
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ax3.axis('off')
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ax3.set_adjustable('box-forced')
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ax4.imshow(median(noisy_image, disk(20)), vmin=0, vmax=255, cmap=plt.cm.gray)
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ax4.set_title('Median $r=20$')
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ax4.axis('off')
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ax4.set_adjustable('box-forced')
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"""
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@@ -109,17 +116,19 @@ image.
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from skimage.filters.rank import mean
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=[10, 7], sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=[10, 7], sharex=True, sharey=True)
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loc_mean = mean(noisy_image, disk(10))
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ax1.imshow(noisy_image, vmin=0, vmax=255, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(loc_mean, vmin=0, vmax=255, cmap=plt.cm.gray)
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ax2.set_title('Local mean $r=10$')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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"""
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@@ -143,22 +152,26 @@ noisy_image = img_as_ubyte(data.camera())
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bilat = mean_bilateral(noisy_image.astype(np.uint16), disk(20), s0=10, s1=10)
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fig, ax = plt.subplots(2, 2, figsize=(10, 7), sharex='row', sharey='row', subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, figsize=(10, 7), sharex='row', sharey='row')
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.imshow(noisy_image, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(bilat, cmap=plt.cm.gray)
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ax2.set_title('Bilateral mean')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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ax3.imshow(noisy_image[200:350, 350:450], cmap=plt.cm.gray)
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ax3.axis('off')
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ax3.set_adjustable('box-forced')
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ax4.imshow(bilat[200:350, 350:450], cmap=plt.cm.gray)
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ax4.axis('off')
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ax4.set_adjustable('box-forced')
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"""
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@@ -196,13 +209,8 @@ hist = np.histogram(noisy_image, bins=np.arange(0, 256))
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glob_hist = np.histogram(glob, bins=np.arange(0, 256))
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loc_hist = np.histogram(loc, bins=np.arange(0, 256))
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fig = plt.figure()
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ax1 = plt.subplot(3, 2, 1, adjustable='box-forced')
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ax2 = plt.subplot(3, 2, 2)
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ax3 = plt.subplot(3, 2, 3, adjustable='box-forced', sharex=ax1, sharey=ax1)
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ax4 = plt.subplot(3, 2, 4)
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ax5 = plt.subplot(3, 2, 5, adjustable='box-forced', sharex=ax1, sharey=ax1)
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ax6 = plt.subplot(3, 2, 6)
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fig, ax = plt.subplots(3, 2, figsize=(10, 10))
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ax1, ax2, ax3, ax4, ax5, ax6 = ax.ravel()
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ax1.imshow(noisy_image, interpolation='nearest', cmap=plt.cm.gray)
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ax1.axis('off')
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@@ -241,15 +249,17 @@ noisy_image = img_as_ubyte(data.camera())
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auto = autolevel(noisy_image.astype(np.uint16), disk(20))
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=[10, 7], sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=[10, 7], sharex=True, sharey=True)
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ax1.imshow(noisy_image, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(auto, cmap=plt.cm.gray)
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ax2.set_title('Local autolevel')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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"""
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@@ -276,7 +286,7 @@ loc_perc_autolevel1 = autolevel_percentile(image, selem=selem, p0=.01, p1=.99)
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loc_perc_autolevel2 = autolevel_percentile(image, selem=selem, p0=.05, p1=.95)
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loc_perc_autolevel3 = autolevel_percentile(image, selem=selem, p0=.1, p1=.9)
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fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(7, 8), sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, axes = plt.subplots(nrows=3, ncols=2, figsize=(7, 8), sharex=True, sharey=True)
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ax0, ax1, ax2 = axes
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plt.gray()
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@@ -298,6 +308,7 @@ for i in range(0,len(image_list)):
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axes_list[i].imshow(image_list[i], cmap=plt.cm.gray, vmin=0, vmax=255)
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axes_list[i].set_title(title_list[i])
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axes_list[i].axis('off')
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axes_list[i].set_adjustable('box-forced')
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"""
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@@ -315,22 +326,26 @@ noisy_image = img_as_ubyte(data.camera())
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enh = enhance_contrast(noisy_image, disk(5))
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex='row', sharey='row', subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex='row', sharey='row')
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.imshow(noisy_image, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(enh, cmap=plt.cm.gray)
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ax2.set_title('Local morphological contrast enhancement')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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ax3.imshow(noisy_image[200:350, 350:450], cmap=plt.cm.gray)
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ax3.axis('off')
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ax3.set_adjustable('box-forced')
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ax4.imshow(enh[200:350, 350:450], cmap=plt.cm.gray)
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ax4.axis('off')
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ax4.set_adjustable('box-forced')
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"""
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@@ -347,22 +362,22 @@ noisy_image = img_as_ubyte(data.camera())
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penh = enhance_contrast_percentile(noisy_image, disk(5), p0=.1, p1=.9)
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex='row', sharey='row', subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex='row', sharey='row')
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.imshow(noisy_image, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax2.imshow(penh, cmap=plt.cm.gray)
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ax2.set_title('Local percentile morphological\n contrast enhancement')
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ax2.axis('off')
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ax3.imshow(noisy_image[200:350, 350:450], cmap=plt.cm.gray)
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ax3.axis('off')
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ax4.imshow(penh[200:350, 350:450], cmap=plt.cm.gray)
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ax4.axis('off')
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for ax in ax.ravel():
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ax.axis('off')
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ax.set_adjustable('box-forced')
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"""
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@@ -404,24 +419,24 @@ loc_otsu = p8 >= t_loc_otsu
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t_glob_otsu = threshold_otsu(p8)
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glob_otsu = p8 >= t_glob_otsu
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fig, ax = plt.subplots(2, 2, sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, sharex=True, sharey=True)
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ax1, ax2, ax3, ax4 = ax.ravel()
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fig.colorbar(ax1.imshow(p8, cmap=plt.cm.gray), ax=ax1)
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ax1.set_title('Original')
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ax1.axis('off')
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fig.colorbar(ax2.imshow(t_loc_otsu, cmap=plt.cm.gray), ax=ax2)
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ax2.set_title('Local Otsu ($r=%d$)' % radius)
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ax2.axis('off')
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ax3.imshow(p8 >= t_loc_otsu, cmap=plt.cm.gray)
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ax3.set_title('Original >= local Otsu' % t_glob_otsu)
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ax3.axis('off')
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ax4.imshow(glob_otsu, cmap=plt.cm.gray)
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ax4.set_title('Global Otsu ($t=%d$)' % t_glob_otsu)
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ax4.axis('off')
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for ax in ax.ravel():
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ax.axis('off')
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ax.set_adjustable('box-forced')
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"""
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@@ -440,15 +455,17 @@ m = (np.tile(x, (n, 1)) * np.linspace(0.1, 1, n) * 128 + 128).astype(np.uint8)
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radius = 10
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t = rank.otsu(m, disk(radius))
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fig, (ax1, ax2) = plt.subplots(1, 2, sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, (ax1, ax2) = plt.subplots(1, 2, sharex=True, sharey=True)
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ax1.imshow(m)
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ax1.set_title('Original')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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ax2.imshow(m >= t, interpolation='nearest')
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ax2.set_title('Local Otsu ($r=%d$)' % radius)
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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"""
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@@ -479,25 +496,24 @@ opening = minimum(maximum(noisy_image, disk(5)), disk(5))
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grad = gradient(noisy_image, disk(5))
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# display results
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, ax = plt.subplots(2, 2, figsize=[10, 7], sharex=True, sharey=True)
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ax1, ax2, ax3, ax4 = ax.ravel()
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ax1.imshow(noisy_image, cmap=plt.cm.gray)
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ax1.set_title('Original')
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ax1.axis('off')
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ax2.imshow(closing, cmap=plt.cm.gray)
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ax2.set_title('Gray-level closing')
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ax2.axis('off')
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ax3.imshow(opening, cmap=plt.cm.gray)
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ax3.set_title('Gray-level opening')
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ax3.axis('off')
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ax4.imshow(grad, cmap=plt.cm.gray)
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ax4.set_title('Morphological gradient')
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ax4.axis('off')
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for ax in ax.ravel():
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ax.axis('off')
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ax.set_adjustable('box-forced')
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"""
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.. image:: PLOT2RST.current_figure
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@@ -529,15 +545,17 @@ import matplotlib.pyplot as plt
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image = data.camera()
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), sharex=True, sharey=True)
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fig.colorbar(ax1.imshow(image, cmap=plt.cm.gray), ax=ax1)
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ax1.set_title('Image')
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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fig.colorbar(ax2.imshow(entropy(image, disk(5)), cmap=plt.cm.jet), ax=ax2)
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ax2.set_title('Entropy')
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ax2.axis('off')
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ax2.set_adjustable('box-forced')
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"""
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@@ -691,13 +709,15 @@ Comparison of outcome of the three methods:
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"""
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fig, (ax0, ax1) = plt.subplots(ncols=2, sharex=True, sharey=True, subplot_kw={'adjustable':'box-forced'})
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fig, (ax0, ax1) = plt.subplots(ncols=2, sharex=True, sharey=True)
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ax0.set_title('filters.rank.median')
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ax0.imshow(rc)
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ax0.axis('off')
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ax0.set_adjustable('box-forced')
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ax1.set_title('scipy.ndimage.percentile')
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ax1.imshow(rndi)
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ax1.axis('off')
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ax1.set_adjustable('box-forced')
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"""
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.. image:: PLOT2RST.current_figure
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