def Restore_Image(input, c_or_g)

def Restore_Image(input, c_or_g):
    # print("input's len : {}".format(len(input)))

    if c_or_g == "color":
        one_step = int(len(input) / 3)
        channel_1 = input[0:one_step]
        channel_2 = input[one_step:2 * one_step]
        channel_3 = input[2 * one_step:len(input)]
        print("ch_1 len : {}".format(len(channel_1)))
        print("ch_2 len : {}".format(len(channel_2)))
        print("ch_3 len : {}".format(len(channel_3)))

        str_1 = list()
        str_2 = list()
        str_3 = list()

        for i in range(len(channel_1)):
            str_1.append(str(channel_1[i]))
            str_2.append(str(channel_2[i]))
            str_3.append(str(channel_3[i]))

        print("str_1's len : {}".format(len(str_1)))
        print("str_2's len : {}".format(len(str_2)))
        print("str_3's len : {}".format(len(str_3)))

        pixel_1 = list()
        pixel_2 = list()
        pixel_3 = list()

        for i in range(int(len(channel_1) / 8)):
            pixel_1.append(int(''.join(str_1[8 * i:8 * (i + 1)]), 2))
            pixel_2.append(int(''.join(str_2[8 * i:8 * (i + 1)]), 2))
            pixel_3.append(int(''.join(str_3[8 * i:8 * (i + 1)]), 2))

        print("pixel_1's len : {}".format(len(pixel_1)))
        print("pixel_2's len : {}".format(len(pixel_2)))
        print("pixel_3's len : {}".format(len(pixel_3)))

        array_1 = np.reshape((np.array(pixel_1, dtype=np.uint8)), (int(sqrt(len(pixel_1))), -1))
        array_2 = np.reshape((np.array(pixel_2, dtype=np.uint8)), (int(sqrt(len(pixel_1))), -1))
        array_3 = np.reshape((np.array(pixel_3, dtype=np.uint8)), (int(sqrt(len(pixel_1))), -1))

        print("array_1's shape : {}".format(array_1.shape))
        print("array_2's shape : {}".format(array_2.shape))
        print("array_3's shape : {}".format(array_3.shape))
        print()

        print("array_1 : {}".format(array_1))
        print("array_2 : {}".format(array_2))
        print("array_3 : {}".format(array_3))

        array = np.array([array_1, array_2, array_3])
        ############################  flattend bit stream을 어떻게 3channel image info.로 바꿀 것인지 짜보기

        print("array's shape : {}".format(array.shape))
        print()
        print()
        print(array)


    elif c_or_g == "gray":
        channel = input

        str_1 = list()

        for i in range(len(channel)):
            str_1.append(str(channel[i]))

        pixel_1 = list()

        for i in range(int(len(channel) / 8)):
            pixel_1.append(int(''.join(str_1[8 * i:8 * (i + 1)]), 2))

        array = np.reshape((np.array(pixel_1, dtype=np.uint8)), (int(sqrt(len(pixel_1))), -1))

    return array