MP4如何让去水印？python带你实现~ |
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MP4如何让去水印？python带你实现~
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前言
嗨喽，大家好呀~这里是爱看美女的茜茜呐
解释器版本: python 3.8 代码编辑器: pycharm 2021.2 模块使用:内置模块（无需安装） os —> python系统编程的操作模块,提供了非常丰富的功能去处理文件和目录 sys —> 是与Python解释器交互的桥梁 cv2 —> 流行的开源计算机视觉库,提供了丰富的图像和视频处理功能 第三方模块 numpy —> 用于数值计算的基础模块,支持大量的维度数值与矩阵计算 moviepy —> 用于视频剪辑、合成和处理 第三方模块安装： win + R 输入 cmd 点击确定, 输入安装命令 pip install 模块名 (pip install requests) 回车 在pycharm中点击Terminal(终端) 输入安装命令 模块可能安装失败原因：出现大量报红 (read time out) 解决方法: 因为是网络链接超时, 需要切换镜像源 可使用镜像源例举： 清华：https://pypi.tuna.tsinghua.edu.cn/simple 中国科技大学 https://pypi.mirrors.ustc.edu.cn/simple/ 华中理工大学：https://pypi.hustunique.com/ 山东理工大学：https://pypi.sdutlinux.org/ 例如：pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple/ 模块名 👇 👇 👇 更多精彩机密、教程，尽在下方，赶紧点击了解吧~素材、视频教程、完整代码、插件安装教程我都准备好了，直接在文末名片自取就可 代码展示导入模块 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 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 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 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 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) 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() 尾语感谢你观看我的文章呐~本次航班到这里就结束啦 🛬 希望本篇文章有对你带来帮助 🎉，有学习到一点知识~ 躲起来的星星🍥也在努力发光，你也要努力加油（让我们一起努力叭）。
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