import numpy as np
import matplotlib.pyplot as plt
import math
import collections
def Histogram(obraz,iloscP):
    unique_elements, counts_elements = np.unique(obraz, return_counts=True)
    zakres = math.ceil(255 / iloscP)
    Y = np.zeros(iloscP)
    X = [x * zakres for x in range(1, iloscP + 1)]
    for x in range(0, iloscP):
        for y, z in zip(unique_elements, counts_elements):
            if x == 0 and (X[x] > y):
                Y[x] = Y[x] + z
            elif (x < iloscP - 1) and (X[x - 1] <= y) and (X[x] > y):
                Y[x] = Y[x] + z
            elif (x == iloscP - 1) and (X[x] <= y):
                Y[x] = Y[x] + z
    return X,Y,unique_elements,counts_elements

obraz = plt.imread("kierowca.jpg")
obraz = obraz[:,:,2]
iloscP = 15
zakres = math.ceil(255 / iloscP)
X,Y,uniqueE,countsE = Histogram(obraz,iloscP)

#plt.subplot(2,6,1)
plt.bar(X,Y,width = zakres,edgecolor='red',align = "edge")
plt.xticks(X,fontsize = 10)
#plt.subplot(2,6,7)

plt.show()

x1 = (np.where(Y > 1000)[0][0] + 1) * zakres
x2 = (np.where(Y > 1000)[0][-1] + 2) * zakres
a = 150 / (x2 - x1)

# image = np.array(plt.imread("kierowca.jpg"))
# image2 = image[:,:,2]
# mean = np.mean(image)
#
# unique_elements, counts_elements = np.unique(image2, return_counts=True)
# cumulativeSumCounts = np.cumsum(counts_elements)
# for x,y in zip(unique_elements,cumulativeSumCounts):
#     image2[image2 == x] = ((y - min(cumulativeSumCounts)) * 255)/ (np.size(image2))
# X,Y,uniqueE,countsE = Histogram(image2,iloscP)
# plt.bar(X,Y,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(X,fontsize = 10)
# plt.show()
# image2 = np.where(np.logical_or(image < x1 , image > x2),image2,image2 * a )
# image2[image < x1] = 0
# image2[image > x2] = 255
# image2[image2 < 0] = 0
# image2[image2 > 255] = 255
# Xl,Yl,uniqueEL,countsEL = Histogram(image2,iloscP)
# plt.subplot(2,6,2)
# plt.bar(Xl,Yl,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(Xl,fontsize = 1.5)
# plt.subplot(2,6,8)
# plt.plot(uniqueEL,countsEL)
#
# image2 = image
# image2 = np.where(np.logical_or(image < x1 , image > x2),image2,image2 ** 2 )
# image2[image < x1] = 0
# image2[image > x2] = 255
# image2[image2 < 0] = 0
# image2[image2 > 255] = 255
# Xp,Yp,uniqueEP,countsEP = Histogram(image2,iloscP)
# plt.subplot(2,6,3)
# plt.bar(Xp,Yp,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(Xp,fontsize = 1.5)
# plt.subplot(2,6,9)
# plt.plot(uniqueEP,countsEP)
#
# image2 = image
# image2 = np.where(np.logical_or(image < x1 , image > x2),image2,np.sqrt(image2))
# image2[image < x1] = 0
# image2[image > x2] = 255
# image2[image2 < 0] = 0
# image2[image2 > 255] = 255
# Xs,Ys,uniqueES,countsES = Histogram(image2,iloscP)
# plt.subplot(2,6,4)
# plt.bar(Xs,Ys,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(Xs,fontsize = 1.5)
# plt.subplot(2,6,10)
# plt.plot(uniqueES,countsES)
#
# image2 = image
# image2 = np.where(np.logical_or(image < x1 , image > x2),image2,np.log(image2))
# image2[image < x1] = 0
# image2[image > x2] = 255
# image2[image2 < 0] = 0
# image2[image2 > 255] = 255
# XL,YL,uniqueEL,countsEL = Histogram(image2,iloscP)
# plt.subplot(2,6,5)
# plt.bar(XL,YL,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(XL,fontsize = 1.5)
# plt.subplot(2,6,11)
# plt.plot(uniqueEL,countsEL)
#
# image2 = image
# image2 = np.where(np.logical_or(image < x1 , image > x2),image2,image2 ** a)
# image2[image < x1] = 0
# image2[image > x2] = 255
# image2[image2 < 0] = 0
# image2[image2 > 255] = 255
# Xpa,Ypa,uniqueEPA,countsEPA = Histogram(image2,iloscP)
# plt.subplot(2,6,6)
# plt.bar(Xpa,Ypa,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(Xpa,fontsize = 1.5)
# plt.subplot(2,6,12)
# plt.plot(uniqueEPA,countsEPA)
#
#
#
#
# plt.savefig("graph.svg")
# plt.show()
# image = np.array(plt.imread("kierowca.jpg"))
# image2 = image[:,:,2]
# mean = np.mean(image)
#
#
# cumulativeSumCounts = np.cumsum(Y)
# cumulativeSumCounts = cumulativeSumCounts / np.size(image2)
#
# indexMIN = np.where(cumulativeSumCounts > 0)[0][0]
# valMin = cumulativeSumCounts[indexMIN]
# newX = []
# for x, y in zip(X,cumulativeSumCounts):
#     newX.append(((y - valMin) / (1 - valMin) ) * iloscP)
# print(newX)
# unique_elements, counts_elements = np.unique(image2, return_counts=True)
# cumulativeSumCounts = np.cumsum(counts_elements)
# for x,y in zip(unique_elements,cumulativeSumCounts):
#     image2[image2 == x] = ((y - min(cumulativeSumCounts)) * 255)/ (np.size(image2))
# X,Y,uniqueE,countsE = Histogram(image2,iloscP)
# plt.bar(X,Y,width = zakres,edgecolor='red',align = "edge")
# plt.xticks(X,fontsize = 10)
# plt.show()