如何让所有图像看起来都一样

import cv2
import numpy as np

def standardize_color(image_path, target_color):
    img = cv2.imread(image_path)
    img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
    
    # Adjust the color to match the target color
    img_hsv[:, :, 0] = target_color[0]
    img_hsv[:, :, 1] = target_color[1]
    img_hsv[:, :, 2] = target_color[2]
    
    standardized_img = cv2.cvtColor(img_hsv, cv2.COLOR_HSV2BGR)
    return standardized_img

# Example usage
target_color = np.array([30, 100, 100])  # Example HSV values for a specific color
standardized_image = standardize_color('path_to_image.jpg', target_color)
cv2.imwrite('standardized_image.jpg', standardized_image)

from PIL import Image

def resize_image(image_path, size):
    with Image.open(image_path) as img:
        resized_img = img.resize(size, Image.ANTIALIAS)
        return resized_img

# Example usage
resized_image = resize_image('path_to_image.jpg', (800, 600))
resized_image.save('resized_image.jpg')

import tensorflow as tf
import tensorflow_hub as hub

def apply_style_transfer(content_image_path, style_image_path, output_path):
    hub_module = hub.load('https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2')
    
    content_image = tf.keras.preprocessing.image.load_img(content_image_path)
    style_image = tf.keras.preprocessing.image.load_img(style_image_path)
    
    content_image = tf.keras.preprocessing.image.img_to_array(content_image)
    style_image = tf.keras.preprocessing.image.img_to_array(style_image)
    
    stylized_image = hub_module(tf.constant(content_image), tf.constant(style_image))[0]
    tf.keras.preprocessing.image.save_img(output_path, stylized_image)

# Example usage
apply_style_transfer('path_to_content_image.jpg', 'path_to_style_image.jpg', 'stylized_image.jpg')