这段代码从视频中提取帧并以.jpg格式保存帧

import cv2
import numpy as np
import os

# set video file path of input video with name and extension
vid = cv2.VideoCapture('VideoPath')


if not os.path.exists('images'):
    os.makedirs('images')

#for frame identity
index = 0
while(True):
    # Extract images
    ret, frame = vid.read()
    # end of frames
    if not ret: 
        break
    # Saves images
    name = './images/frame' + str(index) + '.jpg'
    print ('Creating...' + name)
    cv2.imwrite(name, frame)

    # next frame
    index += 1

在稍微不同的情况下扩展这个问题(@user2700065的回答)，如果有人不想提取每一帧，但想每一秒提取一帧。所以1分钟的视频会有60帧(图像)。

import sys
import argparse

import cv2
print(cv2.__version__)

def extractImages(pathIn, pathOut):
    count = 0
    vidcap = cv2.VideoCapture(pathIn)
    success,image = vidcap.read()
    success = True
    while success:
        vidcap.set(cv2.CAP_PROP_POS_MSEC,(count*1000))    # added this line 
        success,image = vidcap.read()
        print ('Read a new frame: ', success)
        cv2.imwrite( pathOut + "\\frame%d.jpg" % count, image)     # save frame as JPEG file
        count = count + 1

if __name__=="__main__":
    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

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”

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

下面的脚本将提取帧每半秒的所有视频在文件夹。(适用于python 3.7)

import cv2
import os
listing = os.listdir(r'D:/Images/AllVideos')
count=1
for vid in listing:
    vid = r"D:/Images/AllVideos/"+vid
    vidcap = cv2.VideoCapture(vid)
    def getFrame(sec):
        vidcap.set(cv2.CAP_PROP_POS_MSEC,sec*1000)
        hasFrames,image = vidcap.read()
        if hasFrames:
            cv2.imwrite("D:/Images/Frames/image"+str(count)+".jpg", image) # Save frame as JPG file
        return hasFrames
    sec = 0
    frameRate = 0.5 # Change this number to 1 for each 1 second
    
    success = getFrame(sec)
    while success:
        count = count + 1
        sec = sec + frameRate
        sec = round(sec, 2)
        success = getFrame(sec)