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：

<code>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 cv2

import 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 cv2

import 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 os

import sys

import cv2

import numpy

from 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