之前的答案已经失去了第一帧。把图片存储在文件夹里会很好。

# create a folder to store extracted images
import os
folder = 'test'  
os.mkdir(folder)
# use opencv to do the job
import cv2
print(cv2.__version__)  # my version is 3.1.0
vidcap = cv2.VideoCapture('test_video.mp4')
count = 0
while True:
    success,image = vidcap.read()
    if not success:
        break
    cv2.imwrite(os.path.join(folder,"frame{:d}.jpg".format(count)), image)     # save frame as JPEG file
    count += 1
print("{} images are extacted in {}.".format(count,folder))

顺便说一下，你可以通过VLC检查帧率。进入“windows ->媒体信息->编解码器详细信息”

从这里下载这个视频，这样我们就有了相同的测试视频文件。确保mp4文件与python代码位于同一目录。然后确保从相同的目录运行python解释器。

然后修改代码，抛弃浪费时间的waitKey，也没有窗口，它不能捕捉键盘事件。同时，我们打印success值以确保它成功读取帧。

import cv2
vidcap = cv2.VideoCapture('big_buck_bunny_720p_5mb.mp4')
success,image = vidcap.read()
count = 0
while success:
  cv2.imwrite("frame%d.jpg" % count, image)     # save frame as JPEG file      
  success,image = vidcap.read()
  print('Read a new frame: ', success)
  count += 1

这是怎么回事?

我可能在这里迟到了，但你可以使用这个PIP包从视频中快速生成图像。你也可以使用特定的fps来获取图像。

pip安装videoToImages

然后在终端中输入以下命令

视频到图像 --视频文件夹 [路径到视频文件夹]

示例:videoToimages——videoofolder "c:/videos"

对于特定的输出FPS，将——FPS 10设置为任何所需的值。-fps 1表示视频中每秒钟一个图像。

完整的命令:

videoToimages—视频文件夹“c:/videos” videoToimages——videoofolder "c:/videos"——fps 10——img_size (512, 512)

这是对python 3之前答案的一个调整。x来自@ gsurprised，我想把它贴在评论里，但是没有足够的声誉

import sys
import argparse

import cv2
print(cv2.__version__)

def extractImages(pathIn, pathOut):
    vidcap = cv2.VideoCapture(pathIn)
    success,image = vidcap.read()
    count = 0
    success = True
    while success:
      success,image = vidcap.read()
      print ('Read a new frame: ', success)
      cv2.imwrite( pathOut + "\\frame%d.jpg" % count, image)     # save frame as JPEG file
      count += 1

if __name__=="__main__":
    print("aba")
    a = argparse.ArgumentParser()
    a.add_argument("--pathIn", help="path to video")
    a.add_argument("--pathOut", help="path to images")
    args = a.parse_args()
    print(args)
    extractImages(args.pathIn, args.pathOut)

这个函数以1帧/秒的速度从视频中提取图像，此外，它还识别最后一帧并停止读取:

import cv2
import numpy as np

def extract_image_one_fps(video_source_path):

    vidcap = cv2.VideoCapture(video_source_path)
    count = 0
    success = True
    while success:
      vidcap.set(cv2.CAP_PROP_POS_MSEC,(count*1000))      
      success,image = vidcap.read()

      ## Stop when last frame is identified
      image_last = cv2.imread("frame{}.png".format(count-1))
      if np.array_equal(image,image_last):
          break

      cv2.imwrite("frame%d.png" % count, image)     # save frame as PNG file
      print '{}.sec reading a new frame: {} '.format(count,success)
      count += 1

在对如何将帧转换为视频进行了大量研究后，我创建了这个函数，希望这能有所帮助。我们需要opencv来实现:

import cv2
import numpy as np
import os

def frames_to_video(inputpath,outputpath,fps):
   image_array = []
   files = [f for f in os.listdir(inputpath) if isfile(join(inputpath, f))]
   files.sort(key = lambda x: int(x[5:-4]))
   for i in range(len(files)):
       img = cv2.imread(inputpath + files[i])
       size =  (img.shape[1],img.shape[0])
       img = cv2.resize(img,size)
       image_array.append(img)
   fourcc = cv2.VideoWriter_fourcc('D', 'I', 'V', 'X')
   out = cv2.VideoWriter(outputpath,fourcc, fps, size)
   for i in range(len(image_array)):
       out.write(image_array[i])
   out.release()


inputpath = 'folder path'
outpath =  'video file path/video.mp4'
fps = 29
frames_to_video(inputpath,outpath,fps)

修改fps(帧/秒)的值，输入文件夹路径和输出文件夹路径根据您自己的本地位置