import math

from skimage import io, color

import numpy as np

from tqdm import trange

class Cluster(object):

    cluster_index = 1

    def __init__(self, h, w, l=0, a=0, b=0):

        self.update(h, w, l, a, b)

        self.pixels = []

        self.no = self.cluster_index

        Cluster.cluster_index += 1

    def update(self, h, w, l, a, b):

        self.h = h

        self.w = w

        self.l = l

        self.a = a

        self.b = b

    def __str__(self):

        return "{},{}:{} {} {} ".format(self.h, self.w, self.l, self.a, self.b)

    def __repr__(self):

        return self.__str__()

class SLICProcessor(object):

    @staticmethod

    def open_image(path):

        """

        Return:

            3D array, row col [LAB]

        """

        rgb = io.imread(path)

        lab_arr = color.rgb2lab(rgb)

        print(lab_arr.shape)

        return lab_arr

    @staticmethod

    def save_lab_image(path, lab_arr):

        """

        Convert the array to RBG, then save the image

        :param path:

        :param lab_arr:

        :return:

        """

        rgb_arr = color.lab2rgb(lab_arr)

        io.imsave(path, rgb_arr)

    def make_cluster(self, h, w):

        return Cluster(h, w,

                       self.data[h][w][0],

                       self.data[h][w][1],

                       self.data[h][w][2])

    def __init__(self, img, K, M):

        self.K = K

        self.M = M

        self.data = img

        self.image_height = self.data.shape[0]

        self.image_width = self.data.shape[1]

        self.N = self.image_height * self.image_width

        self.S = int(math.sqrt(self.N / self.K))

        self.clusters = []

        self.label = {}

        self.dis = np.full((self.image_height, self.image_width), np.inf)

    def init_clusters(self):

        h = self.S // 2

        w = self.S // 2

        while h < self.image_height:

            while w < self.image_width:

                self.clusters.append(self.make_cluster(h, w))

                w += self.S

            w = self.S // 2

            h += self.S

    def get_gradient(self, h, w):

        if w + 1 >= self.image_width:

            w = self.image_width - 2

        if h + 1 >= self.image_height:

            h = self.image_height - 2

        gradient = self.data[w + 1][h + 1][0] - self.data[w][h][0] + \

                   self.data[w + 1][h + 1][1] - self.data[w][h][1] + \

                   self.data[w + 1][h + 1][2] - self.data[w][h][2]

        return gradient

    def move_clusters(self):

        for cluster in self.clusters:

            cluster_gradient = self.get_gradient(cluster.h, cluster.w)

            for dh in range(-1, 2):

                for dw in range(-1, 2):

                    _h = cluster.h + dh

                    _w = cluster.w + dw

                    new_gradient = self.get_gradient(_h, _w)

                    if new_gradient < cluster_gradient:

                        cluster.update(_h, _w, self.data[_h][_w][0], self.data[_h][_w][1], self.data[_h][_w][2])

                        cluster_gradient = new_gradient

    def assignment(self):

        for cluster in self.clusters:

            for h in range(cluster.h - 2 * self.S, cluster.h + 2 * self.S):

                if h < 0 or h >= self.image_height: continue

                for w in range(cluster.w - 2 * self.S, cluster.w + 2 * self.S):

                    if w < 0 or w >= self.image_width: continue

                    L, A, B = self.data[h][w]

                    Dc = math.sqrt(

                        math.pow(L - cluster.l, 2) +

                        math.pow(A - cluster.a, 2) +

                        math.pow(B - cluster.b, 2))

                    Ds = math.sqrt(

                        math.pow(h - cluster.h, 2) +

                        math.pow(w - cluster.w, 2))

                    D = math.sqrt(math.pow(Dc // self.M, 2) + math.pow(Ds // self.S, 2))

                    if D < self.dis[h][w]:

                        if (h, w) not in self.label:

                            self.label[(h, w)] = cluster

                            cluster.pixels.append((h, w))

                        else:

                            self.label[(h, w)].pixels.remove((h, w))

                            self.label[(h, w)] = cluster

                            cluster.pixels.append((h, w))

                        self.dis[h][w] = D

    def update_cluster(self):

        for cluster in self.clusters:

            sum_h = sum_w = number = 0

            for p in cluster.pixels:

                sum_h += p[0]

                sum_w += p[1]

                number += 1

                _h = sum_h // number

                _w = sum_w // number

                cluster.update(_h, _w, self.data[_h][_w][0], self.data[_h][_w][1], self.data[_h][_w][2])

    def save_current_image(self, name):

        image_arr = np.copy(self.data)

        for cluster in self.clusters:

            for p in cluster.pixels:

                image_arr[p[0]][p[1]][0] = cluster.l

                image_arr[p[0]][p[1]][1] = cluster.a

                image_arr[p[0]][p[1]][2] = cluster.b

            '''

            image_arr[cluster.h][cluster.w][0] = 0

            image_arr[cluster.h][cluster.w][1] = 0

            image_arr[cluster.h][cluster.w][2] = 0

            '''

        # self.save_lab_image(name, image_arr)

        return image_arr

    def iterate_10times(self, filename = 'temp'):

        self.init_clusters()

        self.move_clusters()

        temp_img = []

        for i in range(5):

            self.assignment()

            self.update_cluster()

            name = filename[:len(filename) - 4] + 'M{m}_K{k}_loop{loop}.png'.format(loop=i, m=self.M, k=self.K)

            temp_img.append(self.save_current_image(name))

        # print(temp_img[-1].shape)

        return temp_img[-1]

# if __name__ == '__main__':

#     filename = 'LIDC-IDRI-0087_3000640_1.jpeg'

    # p = SLICProcessor(filename, 2048, 3)

    # p.iterate_10times(filename)

    # p = SLICProcessor(filename, 80, 10)

    # p.iterate_10times(filename)

    # p = SLICProcessor(filename, 500, 40)

    # p.iterate_10times()

    # p = SLICProcessor(filename, 1024, 3)

    # p.iterate_10times(filename)

    # p = SLICProcessor(filename, 200, 5)

    # p.iterate_10times()

    # p = SLICProcessor(filename, 300, 5)

    # p.iterate_10times()

    # p = SLICProcessor(filename, 500, 5)

    # p.iterate_10times()

    # import os

    # path = 'res/'

    # filelist = os.listdir(path)

    # for onefile in filelist:

    #     filename = path + onefile

    #     p = SLICProcessor(filename, 1000, 5)

    #     p.iterate_10times(filename)