opencv-python读写视频

缺乏、安全感 2022-12-12 02:10 114阅读 0赞

### 文章目录 ###

*  读视频，提取帧
 *   *  接口函数：cv2.VideoCapture()
     *  获取视频信息
     *  使用set(cv2.CAP\_PROP\_POS\_FRAMES)读取指定帧
     *  读取函数（重点）
 *  将图像写为视频
 *   *  示例
     *  fourcc

# 读视频，提取帧 #

## 接口函数：cv2.VideoCapture() ##

通过`video_capture = cv2.VideoCapture(video_path)`可以获取读取视频的句柄。而后再通过`flag, frame = video_capture.read()`可以读取当前帧，`flag`表示读取是否成功，读取成功后，句柄会自动移动到下一帧的位置。读取结束后使用`video_capture.release()`释放句柄。

一个简单的逐帧读取的程序如下：

import cv2
    
    video_capture = cv2.VideoCapture(video_path)
    while True:
        flag, frame = video_capture.read()
        if not flag:
            break
        # do something with frame
    video_capture.release()

## 获取视频信息 ##

为了能更好更灵活地了解并读取视频，我们有时候需要获取视频的一些信息，比如帧率，总帧数等等。获取这些信息的方法是调用`video_capture.get(PROP_ID)`方法，其中`PROP_ID`是OpenCV定义的一些常量。

常用的信息及示例如下：

import cv2
    
    video_path = r'D:\peppa\Muddy_Puddles.mp4'
    video_capture = cv2.VideoCapture(video_path)
    
    frame_num = video_capture.get(cv2.CAP_PROP_FRAME_COUNT) # ==> 总帧数
    fps = video_capture.get(cv2.CAP_PROP_FPS)               # ==> 帧率
    width = video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)     # ==> 视频宽度
    height = video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)   # ==> 视频高度
    pos = video_capture.get(cv2.CAP_PROP_POS_FRAMES)        # ==> 句柄位置
    
    video_capture.set(cv2.CAP_PROP_POS_FRAMES, 1000)        # ==> 设置句柄位置
    pos = video_capture.get(cv2.CAP_PROP_POS_FRAMES)        # ==> 此时 pos = 1000.0
    
    video_capture.release()

`句柄位置`指的是下一次调用`read()`方法读取到的帧号，`帧号索引从0开始`。

## 使用set(cv2.CAP\_PROP\_POS\_FRAMES)读取指定帧 ##

从上面代码中可以看到我们使用了`set`方法来设置句柄的位置，这个功能在读取指定帧时很有用，这样我们不必非要使用`read()`遍历到指定位置。

但问题来了，这种方式读取到的内容和`read()`遍历读取到的内容是否完全相同？

做个简单的实验，下面用两种方法分别读取同一个视频的\[100, 200)帧，然后检查读取的内容是否完全相同，结果是True。

import cv2
    import numpy as np
    
    video_path = r'D:\peppa\Muddy_Puddles.mp4'
    video_capture = cv2.VideoCapture(video_path)
    cnt = -1
    frames1 = []
    while True:
        cnt += 1
        flag, frame = video_capture.read()
        assert flag
        if 100 <= cnt < 200:
            frames1.append(frame)
        if cnt >= 200:
            break
    video_capture.release()
    
    video_capture = cv2.VideoCapture(video_path)
    frames2 = []
    for i in range(100, 200):
        video_capture.set(cv2.CAP_PROP_POS_FRAMES, i)
        flag, frame = video_capture.read()
        assert flag
        frames2.append(frame)
    video_capture.release()
    
    frames1 = np.array(frames1)
    frames2 = np.array(frames2)
    print(np.all(frames1 == frames2))  # ==> check whether frames1 is same as frames2, result is True

接下来看看利用set读取的效率。还是利用小猪佩奇第一集做实验，这个视频共7788帧，下面分别用两种方法遍历读取视频中所有帧。第二种方法明显比第一种慢得多，所以这就很苦逼了。。。如果帧间隔比较小的话，单纯用read()进行遍历效率高；如果帧间隔比较大的话，用set()设置位置，然后read()读取效率高。  
（如果给第二种方法加个判断，每隔n帧读取一次，那么效率确实会提高n倍，可以自行尝试）

import cv2
    import numpy as np
    import time
    
    video_path = r'D:\peppa\Muddy_Puddles.mp4'
    video_capture = cv2.VideoCapture(video_path)
    t0 = time.time()
    while True:
        flag, frame = video_capture.read()
        if not flag:
            break
    t1 = time.time()
    video_capture.release()
    
    video_capture = cv2.VideoCapture(video_path)
    t2 = time.time()
    frame_num = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT))
    for i in range(frame_num):
        video_capture.set(cv2.CAP_PROP_POS_FRAMES, i)
        flag, frame = video_capture.read()
        assert flag
    t3 = time.time()
    video_capture.release()
    
    print(t1 - t0)  # ==> 76.3 s
    print(t3 - t2)  # ==> 345.1 s

## 读取函数（重点） ##

上面我们使用了两种方法读取视频帧，第一种是使用read()进行暴力遍历，第二种是使用set()设置帧号，再使用read()读取。两种方法读取到的结果完全一样，但是效率在不同的情况下各有优势，所以为了最大化发挥两者的优势，在写读取帧函数时，就要把两种方式都写进去，由参数来决定使用哪种模式，这样用户可以针对电脑的硬件做一些简单实验后自行决定。

# -*- coding: utf-8 -*-
    import os
    import cv2
    
    
    def _extract_frame_mode_1(video_capture, frame_list, root_folder, ext='png'):
        """ extract video frames and save them to disk. this method will go through all the frames using video_capture.read() Parameters: ----------- video_capture: obtained by cv2.VideoCapture() frame_list: list list of frame numbers root_folder: str root folder to save frames ext: str extension of filename """
        frame_list = sorted(frame_list)
        video_capture.set(cv2.CAP_PROP_POS_FRAMES, 0)
        cnt = -1
        index = 0
        while True:
            cnt += 1
            flag, frame = video_capture.read()
            if not flag:
                break
            if cnt == frame_list[index]:
                filename = os.path.join(root_folder, str(cnt) + '.' + ext)
                cv2.imwrite(filename, frame)
                index += 1
    
    
    def _extract_frame_mode_2(video_capture, frame_list, root_folder, ext='png'):
        """ extract video frames and save them to disk. this method will use video_capture.set() to locate the frame position and then use video_capture.read() to read Parameters: ----------- video_capture: obtained by cv2.VideoCapture() frame_list: list list of frame numbers root_folder: str root folder to save frames ext: str extension of image filename """
        for i in frame_list:
            video_capture.set(cv2.CAP_PROP_POS_FRAMES, i)
            flag, frame = video_capture.read()
            assert flag
            filename = os.path.join(root_folder, str(i) + '.' + ext)
            cv2.imwrite(filename, frame)
    
    
    def extract_frame(video_path, increment=None, frame_list=None,
                      mode=1, ext='png'):
        """ extract video frames and save them to disk. the root folder to save frames is same as video_path (without extension) Parameters: ----------- video_path: str video path increment: int of 'fps' increment of frame indexes frame_list: list list of frame numbers mode: int, 1 or 2 1: go through all the frames using video_capture.read() 2: use video_capture.set() to locate the frame position and then use video_capture.read() to read ext: str extension of image filename """
        video_capture = cv2.VideoCapture(video_path)
        frame_num = int(video_capture.get(cv2.CAP_PROP_FRAME_COUNT))
    
        if increment is None:
            increment = 1
        elif increment == 'fps':
            fps = video_capture.get(cv2.CAP_PROP_FPS)
            increment = round(fps)
    
        if frame_list is None:
            frame_list = [i for i in range(0, frame_num, increment)]
    
        if frame_num // len(frame_list) > 5 and mode == 1:
            print("the frames to be extracted is too sparse, "
                  "please consider setting mode = 2 to accelerate")
    
        root_folder = os.path.splitext(video_path)[0]
        os.makedirs(root_folder, exist_ok=True)
        if mode == 1:
            _extract_frame_mode_1(video_capture, frame_list, root_folder, ext)
        elif mode == 2:
            _extract_frame_mode_2(video_capture, frame_list, root_folder, ext)
        video_capture.release()
    
    
    if __name__ == '__main__':
        video_path = r'D:\peppa\Muddy_Puddles.mp4'
        extract_frame(video_path, increment=30, mode=2)

# 将图像写为视频 #

写视频没有那么多需要注意的地方，主要使用的接口函数是`cv2.VideoWriter(video_path, fourcc, fps, size)`，该函数的主要注意点是入参的设置，`video_path`是输出视频的文件名，`fps`是帧率，`size`是视频的宽高，**待写入视频的图像的尺寸必需与size一致**。其中不太容易理解的是与视频编码相关的`fourcc`，该参数的设置需要使用另外一个接口函数：`cv2.VideoWriter_fourcc(c1, c2, c3, c4)`，c1-c4分别是四个字符。

## 示例 ##

因为获取图像的方式多种多样，而写视频又比较简单，所以不太适合将这部分写成函数，下面以一个例子呈现。

video_path = r'D:\peppa\Muddy_Puddles.avi'
    root_folder = r'D:\peppa\Muddy_Puddles'
    
    fourcc = cv2.VideoWriter_fourcc('X', 'V', 'I', 'D')
    fps = 25
    size = (1920, 1080)
    
    video_writer = cv2.VideoWriter(video_path, fourcc, fps, size)
    for i in range(0, 7788, 30):
        filename = os.path.join(root_folder, str(i) + '.png')
        image = cv2.imread(filename)
        video_writer.write(image)
    video_writer.release()

## fourcc ##

`fourcc`有时候需要多尝试一下，因为不同电脑里安装的编解码器可能不太一样，不见得随便设置一个参数就一定能成功，fourcc有非常多，比如：

<table> 
 <thead> 
  <tr> 
   <th>paramters</th> 
   <th>codec</th> 
   <th>extension</th> 
  </tr> 
 </thead> 
 <tbody> 
  <tr> 
   <td>(‘P’,‘I’,‘M’,‘1’)</td> 
   <td>MPEG-1</td> 
   <td>avi</td> 
  </tr> 
  <tr> 
   <td>(‘M’,‘J’,‘P’,‘G’)</td> 
   <td>motion-jpeg</td> 
   <td>mp4</td> 
  </tr> 
  <tr> 
   <td>(‘M’,‘P’,‘4’,‘V’)</td> 
   <td>MPEG-4</td> 
   <td>mp4</td> 
  </tr> 
  <tr> 
   <td>(‘X’,‘2’,‘6’,‘4’)</td> 
   <td>H.264</td> 
   <td>mp4</td> 
  </tr> 
  <tr> 
   <td>(‘M’, ‘P’, ‘4’, ‘2’)</td> 
   <td>MPEG-4.2</td> 
   <td></td> 
  </tr> 
  <tr> 
   <td>(‘D’, ‘I’, ‘V’, ‘3’)</td> 
   <td>MPEG-4.3</td> 
   <td></td> 
  </tr> 
  <tr> 
   <td>(‘D’, ‘I’, ‘V’, ‘X’)</td> 
   <td>MPEG-4</td> 
   <td>avi</td> 
  </tr> 
  <tr> 
   <td>(‘U’, ‘2’, ‘6’, ‘3’)</td> 
   <td>H263</td> 
   <td></td> 
  </tr> 
  <tr> 
   <td>(‘I’, ‘2’, ‘6’, ‘3’)</td> 
   <td>H263I</td> 
   <td></td> 
  </tr> 
  <tr> 
   <td>(‘F’, ‘L’, ‘V’, ‘1’)</td> 
   <td>FLV1</td> 
   <td>flv</td> 
  </tr> 
  <tr> 
   <td>(‘X’,‘V’,‘I’,‘D’)</td> 
   <td>MPEG-4</td> 
   <td>avi</td> 
  </tr> 
  <tr> 
   <td>(‘I’,‘4’,‘2’,‘0’)</td> 
   <td>YUV</td> 
   <td>avi</td> 
  </tr> 
 </tbody> 
</table>

上表中的后缀名似乎并不需要严格遵守。

fourcc的参考资料：  
https://www.fourcc.org/codecs.php （这个比较完整）  
https://blog.csdn.net/tionsu/article/details/81356006  
https://blog.csdn.net/weixin\_43609992/article/details/106782527  
https://www.cnblogs.com/zhangzhihui/p/12503152.html