skvideo is a python package can be used to read video and stores into the multi-dimensional array.

import skvideo.io  
videodata = skvideo.io.vread("video_file_name")  
print(videodata.shape)

For more details: http://www.scikit-video.org/stable/index.html and http://mllearners.blogspot.in/2018/01/scikit-video-skvideo-tutorial-for.html

The script below does what you want. You may separate part of it into the function.

Code below doesn't check for errors, in particular, production code will check that every frame* variable is greater than zero.

import cv2
import numpy as np

cap = cv2.VideoCapture('test.mp4')
frameCount = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
frameWidth = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frameHeight = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

buf = np.empty((frameCount, frameHeight, frameWidth, 3), np.dtype('uint8'))

fc = 0
ret = True

while (fc < frameCount  and ret):
    ret, buf[fc] = cap.read()
    fc += 1

cap.release()

cv2.namedWindow('frame 10')
cv2.imshow('frame 10', buf[9])

cv2.waitKey(0)

When we look to the video from image processing perspective, we can assume that it is a sequence of images. From this point, you can loop over the frames of your video and convert them into a numpy array.

Here is an example with Pillow and OpenCV libraries, where I'm converting the screenshots from my webcam into numpy arrays:

import cv2
import numpy as np
from PIL import Image, ImageOps    


def screenshot():
    global cam
    cv2.imwrite('screenshot.png', cam.read()[1])


if __name__ == '__main__':
    np.set_printoptions(suppress=True)

    cam = cv2.VideoCapture(0) # You can replace it with your video path
    
    while True:
        ret, img = cam.read()

        cv2.imshow('My Camera', img)

        ch = cv2.waitKey(5)
        if ch == 27:
            break

        screenshot()

        data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)

        image = Image.open('screenshot.png')

        size = (224, 224) # Put your suitable size
        image = ImageOps.fit(image, size, Image.ANTIALIAS)

        image_array = np.asarray(image) # Here, an image -> numpy array
        print(image_array)

    cv2.destroyAllWindows()