How can i resize d435's depth frame?

Hi, im making image classifier with d435. While i do my project there are some problem with our code.

import dlib
import cv2
import pyrealsense2 as rs
import numpy as np
from keras.models import load_model
import os
import tensorflow as tf
from keras.preprocessing import image


def Rotate(src, degrees):
    if degrees == 90:
        dst = cv2.transpose(src)
        dst = cv2.flip(dst, 1)

    elif degrees == 180:
        dst = cv2.flip(src, -1)

    elif degrees == 270:
        dst = cv2.transpose(src)
        dst = cv2.flip(dst, 0)
    else:
        dst = null
    return dst


test_model = load_model("capstone.h5")

if __name__ == "__main__":
    # Configure depth and color streams
    pipeline = rs.pipeline()
    config = rs.config()
    config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
    config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)
    # Start streaming
    pipeline.start(config)

    detector = dlib.get_frontal_face_detector()
    color_green = (0, 255, 0)
    color_red = (0, 0, 255)
    line_width = 3
    try:
        while True:
            # Wait for a coherent pair of frames: depth and color
            frames = pipeline.wait_for_frames()
            depth_frame = frames.get_depth_frame()
            color_frame = frames.get_color_frame()
            if not depth_frame or not color_frame:
                continue
            
            colorizer = rs.colorizer()
            colorized_depth = np.asanyarray(colorizer.colorize(depth_frame).get_data())
    
            
            
            x=image.img_to_array(colorized_depth)
            x=np.expand_dims(x, axis=0)
            images = np.vstack([x])

            classes = test_model.predict(images)
            
            if classes[0][0] == 1:
                output = "Front"
            elif classes[0][1] == 1:
                output = "Left"
            elif classes[0][2] == 1:
                output = "right"
            else:
                output = "Wrong detection"
    

            rgb_image = np.asanyarray(color_frame.get_data())
            dst_image = Rotate(rgb_image, 270)
            # Detection
            dets = detector(dst_image)
            for det in dets:
                if ((det.left()+det.right())//2 - 3*((det.right()-det.left())//2))<=5:
                    left_end = 5
                else:
                    left_end = (det.left()+det.right())//2 - 3*((det.right()-det.left())//2)
                if ((det.left()+det.right())//2 + 5*((det.right()-det.left())//2))>=475:
                    right_end = 475
                else:
                    right_end = (det.left()+det.right())//2 + 3*((det.right()-det.left())//2)
                top_end = det.top() + 10
                if (det.top() - 10)<=5:
                    top_end = 5
                else:
                    top_end = det.top() - 10
                if (det.bottom()*10)>=635:
                    bottom_end = 635
                else:
                    bottom_end = det.bottom()*10
                
                
                cv2.rectangle(dst_image, (left_end,top_end), (right_end,bottom_end), color_green, line_width)
                cv2.putText(dst_image, output, (left_end, top_end-5), cv2.FONT_HERSHEY_DUPLEX, 1, color_green)
            cv2.imshow('my webcam', dst_image)

            key = cv2.waitKey(1)
            # Press esc or 'q' to close the image window
            if key & 0xFF == ord('q') or key == 27:
                cv2.destroyAllWindows()
                break
    finally:
        # Stop streaming
        pipeline.stop()

this is our code and the model were trained with colorized image with resized to (150,150).

i think if we can change depth image's frame size, then the model will work. this is our error message

   ValueError: Input 0 of layer dense is incompatible with the layer: expected axis -1 of input shape to have value 18496 but received input with shape (None, 289536)