【python】去除水印的几种方式

1、python调用FFMEPG的delogo函数去除水印

要使用Python调用FFmpeg的delogo filter去除视频水印，你需要使用subprocess模块运行FFmpeg命令。以下是一个简单的Python脚本示例：

import subprocess def remove_watermark(input_video, output_video, logo_x, logo_y, logo_width, logo_height):    # 构建FFmpeg命令    command = [        'ffmpeg',        '-i', input_video,        '-vf', f'delogo=x={logo_x}:y={logo_y}:w={logo_width}:h={logo_height}',        output_video    ]        # 运行FFmpeg命令    subprocess.run(command) # 使用函数去除水印remove_watermark('input.mp4', 'output.mp4', 10, 10, 100, 100)

使用说明视频：https://www.bilibili.com/video/BV1Jg4y1e7JJ/?spm_id_from=pageDriver

2、使用opencv-python库来处理视频帧

要在Python中去除视频水印，可以使用opencv-python库来处理视频帧，并结合图像处理技术，如图像修复或者图层混合。以下是一个简单的示例，演示如何使用OpenCV去除静态图像水印：

import cv2import numpy as np def remove_watermark(video_path, watermark_path, output_path):    # 读取视频和水印图像    cap = cv2.VideoCapture(video_path)    watermark = cv2.imread(watermark_path, cv2.IMREAD_UNCHANGED)    watermark = cv2.cvtColor(watermark, cv2.COLOR_BGR2GRAY)    watermark = cv2.GaussianBlur(watermark, (5, 5), 0)     # 获取水印的mask    _, mask = cv2.threshold(watermark, 1, 255, cv2.THRESH_BINARY_INV)     while True:        ret, frame = cap.read()        if not ret:            break         # 将水印区域替换为视频帧的背景        frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)        seamless_clone = cv2.seamlessClone(watermark, frame, mask, center, cv2.NORMAL_CLONE)         # 写入去水印后的视频帧        output_video.write(seamless_clone)     cap.release()    output_video.release() # 使用函数去除视频中的水印remove_watermark('input_video.mp4', 'watermark.png', 'output_video.mp4')

请注意，这个示例使用了seamlessClone函数，它要求水印区域的中心与背景相匹配，并且假设水印背景是纯色或者与视频背景融合得当。如果这些条件不满足，可能需要更复杂的图像处理技术，例如图像修复或深度学习去水印方法。

示例2

下面是使用OpenCV去除水印的Python代码示例：

import cv2import numpy as np # 读取视频和水印图像video_path = 'video_with_watermark.mp4'watermark_path = 'watermark.png'cap = cv2.VideoCapture(video_path) # 读取视频的宽、高和帧数frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))fps = cap.get(cv2.CAP_PROP_FPS) # 读取水印图像watermark = cv2.imread(watermark_path, cv2.IMREAD_UNCHANGED)watermark_gray = cv2.cvtColor(watermark, cv2.COLOR_BGR2GRAY) # 创建输出视频out = cv2.VideoWriter('video_without_watermark.mp4', cv2.VideoWriter_fourcc(*'XVID'), fps, (frame_width, frame_height)) while(cap.isOpened()):    ret, frame = cap.read()    if ret:        # 转换为灰度图像        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)                # 使用cv2.matchTemplate()寻找水印的位置        res = cv2.matchTemplate(gray_frame, watermark_gray, cv2.TM_CCOEFF_NORMED)        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)                # 计算水印的位置        top_left = max_loc        bottom_right = (top_left[0] + watermark_gray.shape[1], top_left[1] + watermark_gray.shape[0])                # 绘制矩形框覆盖水印        cv2.rectangle(frame, top_left, bottom_right, (0, 0, 0), thickness=watermark_gray.shape[0])                # 写入去水印后的帧        out.write(frame)                cv2.imshow('Video', frame)        if cv2.waitKey(1) & 0xFF == ord('q'):            break    else:        break cap.release()out.release()cv2.destroyAllWindows()

3、python实战之去除视频水印&字幕，完整代码

import osimport sysimport cv2import numpyfrom moviepy import editor VIDEO_PATH = 'video'OUTPUT_PATH = 'output'TEMP_VIDEO = 'temp.mp4'  class WatermarkRemover():     def __init__(self, threshold: int, kernel_size: int):        self.threshold = threshold  # 阈值分割所用阈值        self.kernel_size = kernel_size  # 膨胀运算核尺寸      #根据用户手动选择的ROI（Region of Interest，感兴趣区域）框选水印或字幕位置。    def select_roi(self, img: numpy.ndarray, hint: str) -> list:        '''    框选水印或字幕位置，SPACE或ENTER键退出    :param img: 显示图片    :return: 框选区域坐标    '''        COFF = 0.7        w, h = int(COFF * img.shape[1]), int(COFF * img.shape[0])        resize_img = cv2.resize(img, (w, h))        roi = cv2.selectROI(hint, resize_img, False, False)        cv2.destroyAllWindows()        watermark_roi = [int(roi[0] / COFF), int(roi[1] / COFF), int(roi[2] / COFF), int(roi[3] / COFF)]        return watermark_roi      #对输入的蒙版进行膨胀运算，扩大蒙版的范围    def dilate_mask(self, mask: numpy.ndarray) -> numpy.ndarray:         '''    对蒙版进行膨胀运算    :param mask: 蒙版图片    :return: 膨胀处理后蒙版    '''        kernel = numpy.ones((self.kernel_size, self.kernel_size), numpy.uint8)        mask = cv2.dilate(mask, kernel)        return mask        #根据手动选择的ROI区域，在单帧图像中生成水印或字幕的蒙版。    def generate_single_mask(self, img: numpy.ndarray, roi: list, threshold: int) -> numpy.ndarray:        '''    通过手动选择的ROI区域生成单帧图像的水印蒙版    :param img: 单帧图像    :param roi: 手动选择区域坐标    :param threshold: 二值化阈值    :return: 水印蒙版    '''        # 区域无效，程序退出        if len(roi) != 4:            print('NULL ROI!')            sys.exit()         # 复制单帧灰度图像ROI内像素点        roi_img = numpy.zeros((img.shape[0], img.shape[1]), numpy.uint8)        start_x, end_x = int(roi[1]), int(roi[1] + roi[3])        start_y, end_y = int(roi[0]), int(roi[0] + roi[2])        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)        roi_img[start_x:end_x, start_y:end_y] = gray[start_x:end_x, start_y:end_y]         # 阈值分割        _, mask = cv2.threshold(roi_img, threshold, 255, cv2.THRESH_BINARY)        return mask     #通过截取视频中多帧图像生成多张水印蒙版，并通过逻辑与计算生成最终的水印蒙版    def generate_watermark_mask(self, video_path: str) -> numpy.ndarray:        '''    截取视频中多帧图像生成多张水印蒙版，通过逻辑与计算生成最终水印蒙版    :param video_path: 视频文件路径    :return: 水印蒙版    '''        video = cv2.VideoCapture(video_path)        success, frame = video.read()        roi = self.select_roi(frame, 'select watermark ROI')        mask = numpy.ones((frame.shape[0], frame.shape[1]), numpy.uint8)        mask.fill(255)         step = video.get(cv2.CAP_PROP_FRAME_COUNT) // 5        index = 0        while success:            if index % step == 0:                mask = cv2.bitwise_and(mask, self.generate_single_mask(frame, roi, self.threshold))            success, frame = video.read()            index += 1        video.release()         return self.dilate_mask(mask)     #根据手动选择的ROI区域，在单帧图像中生成字幕的蒙版。    def generate_subtitle_mask(self, frame: numpy.ndarray, roi: list) -> numpy.ndarray:        '''    通过手动选择ROI区域生成单帧图像字幕蒙版    :param frame: 单帧图像    :param roi: 手动选择区域坐标    :return: 字幕蒙版    '''        mask = self.generate_single_mask(frame, [0, roi[1], frame.shape[1], roi[3]], self.threshold)  # 仅使用ROI横坐标区域        return self.dilate_mask(mask)     def inpaint_image(self, img: numpy.ndarray, mask: numpy.ndarray) -> numpy.ndarray:        '''    修复图像    :param img: 单帧图像    :parma mask: 蒙版    :return: 修复后图像    '''        telea = cv2.inpaint(img, mask, 1, cv2.INPAINT_TELEA)        return telea      def merge_audio(self, input_path: str, output_path: str, temp_path: str):        '''    合并音频与处理后视频    :param input_path: 原视频文件路径    :param output_path: 封装音视频后文件路径    :param temp_path: 无声视频文件路径    '''        with editor.VideoFileClip(input_path) as video:            audio = video.audio            with editor.VideoFileClip(temp_path) as opencv_video:                clip = opencv_video.set_audio(audio)                clip.to_videofile(output_path)     def remove_video_watermark(self):        '''    去除视频水印    '''        if not os.path.exists(OUTPUT_PATH):            os.makedirs(OUTPUT_PATH)         filenames = [os.path.join(VIDEO_PATH, i) for i in os.listdir(VIDEO_PATH)]        mask = None         for i, name in enumerate(filenames):            if i == 0:                # 生成水印蒙版                mask = self.generate_watermark_mask(name)             # 创建待写入文件对象            video = cv2.VideoCapture(name)            fps = video.get(cv2.CAP_PROP_FPS)            size = (int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)))            video_writer = cv2.VideoWriter(TEMP_VIDEO, cv2.VideoWriter_fourcc(*'mp4v'), fps, size)             # 逐帧处理图像            success, frame = video.read()             while success:                frame = self.inpaint_image(frame, mask)                video_writer.write(frame)                success, frame = video.read()             video.release()            video_writer.release()             # 封装视频            (_, filename) = os.path.split(name)            output_path = os.path.join(OUTPUT_PATH, filename.split('.')[0] + '_no_watermark.mp4')  # 输出文件路径            self.merge_audio(name, output_path, TEMP_VIDEO)     if os.path.exists(TEMP_VIDEO):        os.remove(TEMP_VIDEO)     def remove_video_subtitle(self):        '''    去除视频字幕    '''        if not os.path.exists(OUTPUT_PATH):            os.makedirs(OUTPUT_PATH)         filenames = [os.path.join(VIDEO_PATH, i) for i in os.listdir(VIDEO_PATH)]        roi = []         for i, name in enumerate(filenames):            # 创建待写入文件对象            video = cv2.VideoCapture(name)            fps = video.get(cv2.CAP_PROP_FPS)            size = (int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)))            video_writer = cv2.VideoWriter(TEMP_VIDEO, cv2.VideoWriter_fourcc(*'mp4v'), fps, size)             # 逐帧处理图像            success, frame = video.read()            if i == 0:                roi = self.select_roi(frame, 'select subtitle ROI')             while success:                mask = self.generate_subtitle_mask(frame, roi)                frame = self.inpaint_image(frame, mask)                video_writer.write(frame)                success, frame = video.read()             video.release()            video_writer.release()             # 封装视频            (_, filename) = os.path.split(name)            output_path = os.path.join(OUTPUT_PATH, filename.split('.')[0] + '_no_sub.mp4')  # 输出文件路径            self.merge_audio(name, output_path, TEMP_VIDEO)         if os.path.exists(TEMP_VIDEO):            os.remove(TEMP_VIDEO)  if __name__ == '__main__':    sel=input('1：去水印, 2:去字幕\n')    if sel=='1':        remover = WatermarkRemover(threshold=80, kernel_size=5)        remover.remove_video_watermark()    if sel=='2':        remover = WatermarkRemover(threshold=80, kernel_size=5)        remover.remove_video_subtitle()

另外：图片去除水印方法

（一）手机——乐奇爱水印精灵

有点免费去除水印，可以无效其操作，但是每天只能保存一张，好就好在邀请一个人可以活得60此保存机会，那个被邀请的也能获得十次，可以P图。

（二）电脑——quququ.cn

把图片拖到网站，调整画笔大小，抹除文字就可以p图完成，免费下载就可以了。

ps：参考自：https://blog.csdn.net/weixin_63253486/article/details/131421022