Python 如何使用线程使一个操作在继续之前等待另一个操作完成？

我正在一个100GB视频数据集上训练一个深度学习模型。我正在尝试将其全部转换为帧，然后在每个帧上应用Haar Cascade来裁剪面。但是我正在努力找到最快的方法

注意： 有5个褶皱，每个褶皱中有2个部分每个部分都有6个文件夹，其中包含3类不同视频格式的数据（0、5、10）（mp4、MOV、MOV）。总共有144个视频文件，每个文件大小约为700MB

编辑： 我遇到了这样一个问题，即视频到帧的处理不是等待其工作完成后再继续下一个文件

错误消息： 它会立即为每个文件抛出一个错误，而不是等待转换当前文件的帧，然后移动到下一个文件

Error!!!
Reading from /Volumes/HDD/Data/Fold4_part2/44/5.mov
Category:5
Writing to /Volumes/HDD/Data/Fold4_part2/44
Number of frames:  7353
Converting video..

Error!!!
Reading from /Volumes/HDD/Data/Fold4_part2/45/0.mp4
Category:0
Writing to /Volumes/HDD/Data/Fold4_part2/45
Number of frames:  7716
Converting video..

代码：

import cv2
import time 
import os
path_HDD = "/Volumes/HDD/Data"

def files(path):
    """
    Function to get the files and add them to a list 
    Args: 
        path: path of the file 
    Not sure what is DS_Store but I do not need it
    """
    for root, directories, files in os.walk(path, topdown=False):
        for name in files:
            file_path = os.path.join(root, name)
            if (name == ".DS_Store"):
                continue 
            else: 
                category = name.split(".")[0]
                # Category returns the video category 
                try: 
                    print("Reading from " + file_path)
                    print("Category:" + category)
                    print("Writing to " + root)
                    video_to_frames(file_path, category, root)
                except:
                    print("Error!!!")

 
        
def video_to_frames(input_loc, label,output_loc):
    """Function to extract frames from input video file
    and save them as separate frames in an output directory.
    Args:
        input_loc: Input video file.
        output_loc: Output directory to save the frames.
    Returns:
        None
    """
    # Log the time
    time_start = time.time()
    # Start capturing the feed
    cap = cv2.VideoCapture(input_loc)
    # Find the number of frames
    video_length = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) - 1
    print ("Number of frames: ", video_length)
    count = 0
    print ("Converting video..\n")
    # Start converting the video
    while cap.isOpened():
        # Extract the frame
        ret, frame = cap.read()
        # Write the results back to output location.
        cv2.imwrite(output_loc +  "/" + label + "/%#05d.jpg" % (count+1), frame)
        
        count = count + 1
        # If there are no more frames left
        if (count > (video_length-1)):
            # Log the time again
            time_end = time.time()
            # Release the feed
            cap.release()
            # Print stats
            print ("Done extracting frames.\n%d frames extracted" % count)
            print ("It took %d seconds forconversion." % (time_end-time_start))
            break

if __name__=="__main__":
    files(path_HDD)

---

这个问题实际上是二合一的

如何在一个视频中提取所有帧

然后如何扩展该过程，以便将其应用于整个目录

您可以通过使用opencvpython和

---

第二个问题应该是可以实现的，只需掌握一点Python的一般知识，并知道如何使用

获取文件路径。通过上面的答案，我们设法解决了这个问题，但可能需要6个小时来处理所有100GB。这不是一个真正的问题，但我可能会找到一种方法，使它更快地使用线程

import cv2
import time 
import os
import argparse
import sys
path_HDD = "/Volumes/HDD/Data"

def files(path):
    """
    Function to get the files and add them to a list 
    Args: 
        path: path of the file 
    Not sure what is DS_Store but I do not need it
    """
    for root, directories, files in os.walk(path, topdown=False):
        for name in files:
            file_path = os.path.join(root, name)
            if (name == ".DS_Store"):
                continue 
            else: 
                category = name.split(".")[0]
                # Category returns the video category 
                try: 
                    print("Reading from " + file_path)
                    print("Category:" + category)
                    print("Writing to " + root)
                    video_to_frames(file_path, category, root)
                except:
                    sys.exit("Unable to extract the frames from the video!")
"""
Root : /Volumes/HDD/Data/Fold1_part1/01/
Category : Label of the video 
File path : 
"""
 
        
def video_to_frames(input_loc, label,output_loc):
    """Function to extract frames from input video file
    and save them as separate frames in an output directory.
    Args:
        input_loc: Input video file.
        output_loc: Output directory to save the frames.
    Returns:
        None
    """
    #Checking if the file exists before creating it 
    pathFrame = os.path.join(output_loc, label) 
    if (os.path.exists(pathFrame)):
        pass
    else:
        try:
            os.mkdir(pathFrame) 
            print("Directory '%s' created" %pathFrame) 
        except IOError:
            print("Unable to create the new directory")
            sys.exit()
        
    # Log the time
    time_start = time.time()
    # Start capturing the feed
    cap = cv2.VideoCapture(input_loc)
    # Find the number of frames
    video_length = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) - 1
    print ("Number of frames: ", video_length)
    count = 0
    print ("Converting video..\n")
    # Start converting the video
    while cap.isOpened():
        # Extract the frame
        ret, frame = cap.read()
        # Write the results back to output location.
        cv2.imwrite(pathFrame + "/%#05d.jpg" % (count+1), frame)
        count = count + 1
        # If there are no more frames left
        if (count > (video_length-1)):
            # Log the time again
            time_end = time.time()
            # Release the feed
            cap.release()
            # Print stats
            print ("Done extracting frames.\n%d frames extracted" % count)
            print ("It took %d seconds forconversion." % (time_end-time_start))
            break

if __name__=="__main__":
    files(path_HDD)

---

好的，我照做了，但我遇到了一个问题。请检查新编辑。