imageManipulation.py

__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])