import cv2

from PIL import Image 

import numpy as np



#Wyświetlanie grafiki

def show_image(img):

    cv2.imshow("image", img)

    cv2.waitKey(0)

    cv2.destroyAllWindows()



#Wczytanie grafiki z pliku

def read_image_cv(path):

    img = cv2.imread(path, cv2.IMREAD_COLOR)

    print(img)

    print(img.shape)

    print(type(img))

    show_image(img)

    return img



'''

#Wczytywanie obrazów za pomocą biblioteki Pillow

def read_image_PIL(path):

    im = Image.open("image.jpg")

    try:

        print(im)

    except:

        print(type(im))

    im.show()

    return im

read_image_PIL("image.jpg")

'''



image = read_image_cv("image.jpg")



def reverse_image(img):

    new_img = []

    for row in range(img.shape[0]):

        new_row = []

        for column in range(img.shape[1]):

            new_row.append(img[-1-row][column])

        new_img.append(new_row)

    return np.array(new_img)

show_image(reverse_image(image))





def reverse_image_short(img):

    img_reverse = img[::-1]

    return img_reverse

show_image(reverse_image_short(image))



show_image(cv2.flip(image, 0) )





def gray_scale(img):

    for row in range(img.shape[0]):

        for column in range(img.shape[1]):

            gray = int(sum(img[row][column])/3)

            img[row][column][0] = gray

            img[row][column][1] = gray

            img[row][column][2] = gray

    return np.array(img)



show_image(gray_scale(image) )



show_image(cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) )





def sepia(img):

    for row in range(img.shape[0]):

        for column in range(img.shape[1]):

            B = img[row][column][0]

            G = img[row][column][1]

            R = img[row][column][2]

            img[row][column][2] =  min(255, (0.393*R + 0.769*G + 0.189*B))

            img[row][column][1] =  min(255, (0.349*R + 0.686*G + 0.168*B))

            img[row][column][0] =  min(255, (0.272*R + 0.534*G + 0.131*B))

    return np.array(img, dtype= np.uint8)



show_image(sepia(image))





def change_colors(img,R_scale,G_scale,B_scale):

    for row in range(img.shape[0]):

        for column in range(img.shape[1]):

            img[row][column][2] =  img[row][column][2] * R_scale

            img[row][column][1] =  img[row][column][1] * G_scale

            img[row][column][0] =  img[row][column][0] * B_scale

    return np.array(img, dtype= np.uint8)



#show_image(change_colors(image,1.4,0,0))



def tresholding(img,treshold):

    for row in range(img.shape[0]):

        for column in range(img.shape[1]):

            gray = int(sum(img[row][column])/3)

            if gray <= treshold:

                img[row][column] = [255,255,255]

            else:

                img[row][column] = [0,0,0]

    return np.array(img)

show_image(tresholding(image,200))