python 實現臨近值插入和雙線性插入

上篇筆記記過這兩種方法了，這裏用代碼實現一下

臨近值插入

from skimage import io,data
import numpy as np

def function(img,widths,heights):
    rows,cols,dims = img.shape

    emptyImage = np.zeros((widths,heights,dims),dtype=np.uint8)
    sw = widths/rows
    sh = heights/cols

    for m in range(dims):
        for i in range(widths):
             for j in range(heights):
                 x = min(int(i/sh),rows-1)
                 y = min(int(j/sw),cols-1)
                 emptyImage[i,j,m] = img[x,y,m]
    return emptyImage


img = io.imread('11.jpg')
print(img.shape)
result = function(img,500,500)
print(result.shape)
io.imshow(result)
io.show()

雙線性插入

from skimage import io,data
import numpy as np
import math


def function(img,widths,heights):
    rows,cols,dims = img.shape

    emptyImage = np.zeros((widths,heights,dims),np.uint8)
    sw = widths/rows
    sh = heights/cols

    for m in range(dims):
        for i in range(widths):
            for j in range(heights):
               
                x = i/sw
                y = j/sh
                src_x_0 = int(x)
                src_y_0 = int(y)
                u = x - src_x_0
                v = y - src_y_0
                src_x_1 = src_x_0+1
                src_y_1 = src_y_0+1
                #防止超界
                if src_x_1+1<rows and src_y_1+1< cols:
                    emptyImage[i,j,m] = int((1-u)*(1-v)*img[src_x_0,src_y_0,m] + u*(1-v)*img[src_x_1,src_y_0,m] + (1-u)*v*img[src_x_0,src_y_1,m] + u*v*img[src_x_1,src_y_1,m])
    return emptyImage


if __name__ == '__main__':
    img = io.imread('1.jpg')
    print(img.shape)
    result = function(img,900,900)
    print(result.shape)
    io.imshow(result)
    io.show()