scipyを使わずにリサイズ関数を実装する1つの方法は、pythonのcv2ライブラリを使うことです。cv2を使ったリサイズ関数の例を示します：

```
import cv2

def resize_images(images, res_x, res_y):
    resized_images = np.zeros((images.shape[0], res_x, res_y))
    for n in range(len(images)):
        resized_image = cv2.resize(images[n, :, :], (res_x, res_y), interpolation=cv2.INTER_NEAREST)
        resized_images[n, :, :] = resized_image
    return resized_images
```

この実装では， scipy.misc.resize 関数の代わりに cv2.resize 関数が利用されています．cv2.resize 関数は，リサイズされる画像，指定されたサイズ（ res_x, res_y ），リサイズ時に利用される補間法を引数にとります．この例では，補間方法を cv2.INTER_NEAREST とし，最近傍補間を用いています．
One way to implement the resize function without using scipy is to use the cv2 library in python. Here's an example of a resizing function using cv2:

import cv2

def resize_images(images, res_x, res_y):
    resized_images = np.zeros((images.shape[0], res_x, res_y))
    for n in range(len(images)):
        resized_image = cv2.resize(images[n, :, :], (res_x, res_y), interpolation=cv2.INTER_NEAREST)
        resized_images[n, :, :] = resized_image
    return resized_images

In this implementation, the cv2.resize function is used instead of the scipy.misc.resize function. The cv2.resize function takes in the image to be resized, the desired size (res_x, res_y), and the interpolation method to use during resizing. In this example, the interpolation method is set to cv2.INTER_NEAREST, which uses nearest neighbor interpolation.