【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 subprocessdef 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 npdef 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_locbottom_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'):breakelse:breakcap.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 editorVIDEO_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 = 0.7w, 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) // 5index = 0while success:if index % step == 0:mask = cv2.bitwise_and(mask, self.generate_single_mask(frame, roi, self.threshold))success, frame = video.read()index += 1video.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 teleadef 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.audiowith 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 = Nonefor 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()