from numpy import *
from scipy import *
from scipy.signal import *
from scipy.stats import *
from pylab import*

''' Funkcja obliczajaca dwt '''
def dwt(img):
    maskL = [0.02674875741080976, -0.01686411844287795, -0.07822326652898785, 0.2668641184428723, 0.6029490182363579, 0.2668641184428723,
    -0.07822326652898785, -0.01686411844287795, 0.02674875741080976]
    maskH = [0.09127176311424948, -0.05754352622849957, -0.5912717631142470, 1.115087052456994, -0.5912717631142470, -0.05754352622849957,
    0.09127176311424948]
    height = img.shape[0]
    width = img.shape[1]
    bandL = zeros([height,int(width/2)])
    bandH = zeros(bandL.shape)
    for r in range(0, height): #1D-DWT dla wierszy
        bandL[r,:] = convolve(img[r,:], maskL, mode='same')[::2]
        bandH[r,:] = convolve(img[r,:], maskH, mode='same')[::2]
    bandLL = zeros([int(height/2),int(width/2)])
    bandLH = zeros(bandLL.shape)
    bandHL = zeros(bandLL.shape)
    bandHH = zeros(bandLL.shape)
    for c in range(0, int(width/2)): #1D-DWT dla kolumn
        bandLL[:,c] = convolve(bandL[:,c], maskL, mode='same')[::2]
        bandLH[:,c] = convolve(bandL[:,c], maskH, mode='same')[::2]
        bandHL[:,c] = convolve(bandH[:,c], maskL, mode='same')[::2]
        bandHH[:,c] = convolve(bandH[:,c], maskH, mode='same')[::2]
    return clip(bandLL, 0.0, 1.0), bandLH, bandHL, bandHH

''' funkcja wyswietlajaca i zapisujaca obraz '''
def showAndSaveImg(img, imgTitle):
    figure()
    axis('off')
    title(imgTitle)
    imshow(img, cmap = cm.gray, vmin = -1.0, vmax = 1.0)
    imsave("C:/Users/Wojtek/Documents/" + imgTitle + '.png', img, cmap = cm.gray)

def histogram1(img, ilosc, minimum, histTitle):
    figure()
    hist(img.flatten(), ilosc, range = [minimum, 1.0])
    title('Histogram pasma ' + histTitle)
    xlabel('Wartosc piksela')
    ylabel('Ilosc wystapien')

''' funkcja obliczajaca entropie '''
def entropia(img, ilosc, minimum):
    hist = histogram(img.flatten(), ilosc, range = [minimum, 1.0])[0] + sys.float_info.epsilon #utworzenie histogramu
    pstwo = hist/sum(hist)
    ent = -1.0*sum(pstwo*log2(pstwo)) #obliczenie entropii
    return ent

obraz = imread(r"C:\Users\Wojtek\Downloads\pto_obrazytestowepng (2)\obrazyTestowe\monochrome\galera_mono.png") #wczytanie obrazu

obrazLL, obrazLH, obrazHL, obrazHH = dwt(obraz) #wywolanie funkcji dwt

#otworzenie i zapisanie obrazow dla wszystkich pasm
showAndSaveImg(obrazLL, 'Pasmo LL')
showAndSaveImg(obrazLH, 'Pasmo LH')
showAndSaveImg(obrazHL, 'Pasmo HL')
showAndSaveImg(obrazHH, 'Pasmo HH')

#stworzenie histogramow dla poszczegolnych pasm
histogram1(obrazLL, 256, 0.0, 'LL')
histogram1(obrazLH, 511, -1.0, 'LH')
histogram1(obrazHL, 511, -1.0, 'HL')
histogram1(obrazHH, 511, -1.0, 'HH')

#obliczenie entropii dla poszczegolnch pasm
print ('Entropia dla pasma LL: ', entropia(obrazLL, 256, 0.0))
print ('Entropia dla pasma LH: ', entropia(obrazLH, 511, -1.0))
print ('Entropia dla pasma HL: ', entropia(obrazHL, 511, -1.0))
print ('Entropia dla pasma HH: ', entropia(obrazHH, 511, -1.0))

show()