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Minor fixes
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@@ -51,7 +51,6 @@ plt.show()
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# and naive threshold value, which is sometimes used as a guess value.
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from skimage.filters.thresholding import threshold_mean
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from skimage import data
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image = data.camera()
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@@ -83,9 +82,6 @@ plt.show()
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# histogram, there can be multiple pixel values with the minimum histogram
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# count, so you can pick the 'min', 'mid', or 'max' of these values.
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import matplotlib.pyplot as plt
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from skimage import data
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from skimage.filters.thresholding import threshold_minimum
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@@ -182,9 +178,6 @@ plt.show()
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# each pixel (i.e. local neighborhoods). Each threshold value is the weighted mean
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# of the local neighborhood minus an offset value.
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import matplotlib.pyplot as plt
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from skimage import data
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from skimage.filters import threshold_otsu, threshold_adaptive
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@@ -223,14 +216,10 @@ plt.show()
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# The example compares the local threshold with the global threshold.
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#
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from skimage import data
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from skimage.morphology import disk
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from skimage.filters import threshold_otsu, rank
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from skimage.util import img_as_ubyte
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import matplotlib
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import matplotlib.pyplot as plt
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img = img_as_ubyte(data.page())
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