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"""

LAB2 Task2

Use Python function “interp2” from packet “scipy” or your own written algorithm to interpolate a grey scale image by using bicubic interpolation.

Enlarge: [461, 461]

Shrink: [205, 205]

"""

import numpy as np

from skimage import io, data

import math

from scipy import interpolate

def small_map2(x, range):

    ratio = (x-1)/(range)

    return 2.01 + ratio*(range-4.02)

def find_value(x, y, z, pix_x, pix_y):

    f = interpolate.interp2d(x, y, z, kind='cubic')

    out = f(pix_x, pix_y)[0]

    print(out)

    print(z)

    return out

def bicubic2_11810818(input_file, dim):

    # Load image

    in_image = io.imread(input_file)

    out_width = dim[0]

    out_height = dim[1]

    in_width = in_image.shape[0]

    in_height = in_image.shape[1]

    out_image = np.zeros(dim, dtype=np.uint8)

    print(in_image)

    # Perform Exchange

    for col in range(out_width):

        for row in range(out_height):

            pix_x = small_map2(col*((in_width-1)/(out_width-1)), out_width)

            pix_y = small_map2(row*((in_height-1)/(out_height-1)), out_height)

            space = np.zeros([4, 4])

            x_range = [math.floor(pix_x) - 1, math.floor(pix_x), math.floor(pix_x) + 1, math.floor(pix_x) + 2]

            y_range = [math.floor(pix_y) - 1, math.floor(pix_y), math.floor(pix_y) + 1, math.floor(pix_y) + 2]

            # print("x: "+str(x_range))

            # print("y: "+str(y_range))

            # print(str(pix_x) + " " + str(pix_y))

            for i in range(4):

                for j in range(4):

                    space[i, j] = in_image[x_range[i], y_range[j]]

            out_image[col, row] = find_value(

                x_range,

                y_range,

                space,

                pix_x,

                pix_y

            )

    # Save Image

    print(out_image)

    io.imsave("enlarged_bicubic3_11810818.tif", out_image)

if __name__ == '__main__':

    # bicubic2_11810818("rice.tif", [205, 205])

    bicubic2_11810818("rice.tif", [461, 461])

import numpy as np

from skimage import io, data

import math

from scipy import interpolate

def interp_test():

    x = [1, 2, 3, 4]

    y = x;

    z = [[106, 110, 154, 188],

         [103,  99, 12, 157],

         [100,  97, 101, 109],

         [102, 104,  96, 105]]

    f1_1 = interpolate.interp1d(x, z[0], kind='cubic')

    f1_2 = interpolate.interp1d(x, z[1], kind='cubic')

    z1 = [f1_1(2.5), f1_2(2.5), f1_1(2.5), f1_2(2.5)]

    f1_3 = interpolate.interp1d(x, z1, kind='cubic')

    print("interpolate.interp1d get: " + str(f1_3(2.5)))

    f2 = interpolate.interp2d(x, y, z, kind='cubic')

    print("interpolate.interp2d get: " + str(f2(2.5, 2.5)[0]))

if __name__ == '__main__':

    interp_test()

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