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imageManipulation.py

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+__all__ = ['rgb2gray', 'rgb2mix','rgb2red','rgb2blue','plotHist','makeHist','myHist','saveNifti', 'hist2curve']
+import numpy as np
+import nibabel as nib
+import matplotlib.pyplot as plt
+import os
+
+
+def rgb2gray(rgb): # visual weight
+    r, g, b = rgb[:,:,0], rgb[:,:,1], rgb[:,:,2]
+    gray = 0.2989 * r + 0.5870 * g + 0.1140 * b
+    return gray
+
+def rgb2mix(rgb):
+    return 1/3. * (1.0 * rgb[:,:,0] + 1.0 * rgb[:,:,1] + 1.0 * rgb[:,:,2])
+
+def rgb2red(rgb):
+    return rgb[:,:,0]
+
+def rgb2green(rgb):
+    return rgb[:,:,1]
+
+def rgb2blue(rgb):
+    return rgb[:,:,2]
+
+def plotHist(hist, bins):
+    width = 0.7 * (bins[1] - bins[0])
+    center = (bins[:-1] + bins[1:]) / 2
+    plt.bar(center, hist, align='center', width=width)
+    plt.show();plt.close()
+
+def makeHist(data):
+    mhist, mbins = np.histogram(data, bins = np.around(np.amax(data)))
+    plotHist(mhist, mbins)
+
+def myHist(data, nbins):
+    mhist, mbins = np.histogram(data, nbins)
+    plotHist(mhist, mbins)
+
+def saveNifti(data, name):
+    img = nib.Nifti1Image(data, np.eye(4))
+
+    nib.save(img, name)#
+
+def hist2curve(hist): # Takes a tuple as generated by pyplot's hist()
+    y,bins, delme = np.array(hist)
+    x = [(bins[i+1]+bins[i])/2 for i in range(bins.shape[0]-1)]
+    return np.asarray([x,y])