无缝合并两张图片（封面右上角添加logo）-- opencv ： 进行添加logo(水印)由于使用了cv2.seamlessClone，cv2.seamlessClone使用了泊松克隆（Poisson Cloning），会根据周围的颜色信息进行颜色调整，使得融合后的区域更加自然，但这也可能导致颜色发生变化。

logo 都花了，颜色也不对了。
为了保留原来的颜色，可以使用简单的覆盖方法而不是cv2.seamlessClone。

import os
import cv2
import sys
import traceback
import numpy as np
import requests
import logging





def get_logoUrl(logoUrl, uid):
    """
        Download logo image from URL and save it locally.

        Args:
        - logoUrl (str): URL of the logo image.
        - uid (str): Unique identifier for the image.

        Returns:
        - str: File path where the logo image is saved.
        """
    end = logoUrl.split('.')[-1]
    content = requests.get(logoUrl).content
    #logger.info(os.getcwd())
    try:
        logo_name = f'logo_images/{uid}.{end}'
        #logger.info(logo_name)
        print(logo_name)
        #print(os.getcwd())
        with open(logo_name,'wb') as f:
            f.write(content)
        return logo_name
    except:
        #logger.info(traceback.format_exc())
        print(traceback.format_exc())
        # return dict(code=10099, data='系统未能获得有效结果，请稍后重试')



def merge_logo2First_page(uid, logoUrl):
    """
       Merge a logo onto the first page image, preserving transparency if present.

       Args:
       - uid (str): Unique identifier for the image.
       - logoUrl (str): URL of the logo image.

       Returns:
       - str: File path where the merged image is saved.
       """
    folder = 'imgs/'

    # 获取 logo 图片
    logo_name = get_logoUrl(logoUrl, uid)
    obj = cv2.imread(logo_name, cv2.IMREAD_UNCHANGED)

    if obj is None:
        raise ValueError(f"Image at path {logo_name} could not be read.")

    (h, w, z) = obj.shape

    # 固定 logo 图片的大小
    obj_fixed_size = cv2.resize(obj, (round(200 * (w / h)), 200))
    (h, w, z) = obj_fixed_size.shape

    # 检查是否存在 Alpha 通道，如果没有则创建一个全白的 Alpha 通道
    if obj_fixed_size.shape[2] == 4:
        alpha_channel = obj_fixed_size[:, :, 3] / 255.0
        obj_rgb = obj_fixed_size[:, :, :3]
    else:
        alpha_channel = np.ones((obj_fixed_size.shape[0], obj_fixed_size.shape[1]), dtype=np.float32)
        obj_rgb = obj_fixed_size

    # 读取主图片
    im = cv2.imread(folder + "auto_first_page.jpg")
    (height, width, channels) = im.shape

    # 计算 logo 的放置位置（右上角）
    top_left_h = 100  # 距离顶部的距离
    top_left_w = width - w - 222  # 距离右侧的距离

    # 边界检查，确保放置位置在主图片内
    if top_left_h < 0:
        top_left_h = 0
    if top_left_w < 0:
        top_left_w = 0
    if top_left_h + h > height:
        top_left_h = height - h
    if top_left_w + w > width:
        top_left_w = width - w

    # 处理透明度，将有颜色的部分覆盖到主图片上
    # for c in range(0, 3):
    #     im[top_left_h:top_left_h + h, top_left_w:top_left_w + w, c] = (
    #             alpha_channel * obj_rgb[:, :, c] +
    #             (1 - alpha_channel) * im[top_left_h:top_left_h + h, top_left_w:top_left_w + w, c]
    #     )
    # 矩阵计算替代显式循环：使用 NumPy 的广播功能，将显式循环转换为矩阵计算，从而提高效率。
    im[top_left_h:top_left_h + h, top_left_w:top_left_w + w, :3] = (
            (alpha_channel[..., np.newaxis] * obj_rgb) +
            ((1 - alpha_channel[..., np.newaxis]) * im[top_left_h:top_left_h + h, top_left_w:top_left_w + w, :3])
    )
    # 保存处理后的图片
    save_path = 'first_page_merged_logo/'
    if not os.path.exists(save_path):
        os.makedirs(save_path)

    output_path = os.path.join(save_path, f"merged_{uid}.jpg")
    cv2.imwrite(output_path, im)

    return output_path, logo_name