用Python提取视频中的图片
Python在处理视频方面表现非常优秀，多数都是基于OpenCV库的。为了解决我的需求，因此决定自己写个基于Python+OpenCV的通用函数，来解决以后在提取图片过程中的各种需求。
这个函数就是本文要介绍的video2frames()函数，功能就是从视频中提取图片，名称“video2frames”是我自己取的，还比较形象。现将它分享给大家，感兴趣的小伙伴们可以参考一下，完整代码附在文末。
1. 主要功能
这个函数有以下主要功能：
- 提取特定时间点图片，比如：提取视频第3秒， 第5秒，第9秒图片
- 设定提取的起始时刻，比如：从视频的第10秒开始提取
- 设定提取的终止时刻，比如：100秒后的视频不提取图片
- 设定每隔多少秒提取一张图片，比如：每隔2秒从视频中提取一张图片
2. 函数参数
video2frames()函数的原型为：
video2frames(pathIn='',
pathOut='',
only_output_video_info = False,
extract_time_points = None,
initial_extract_time = 0,
end_extract_time = None,
extract_time_interval = -1,
output_prefix = 'frame',
jpg_quality = 100,
isColor = True)各参数的意义：
pathIn：视频的路径，比如：F:\python_tutorials\test.mp4pathOut：设定提取的图片保存在哪个文件夹下，比如：F:\python_tutorials\frames\。如果该文件夹不存在，函数将自动创建它only_output_video_info：如果为True，只输出视频信息（长度、帧数和帧率），不提取图片extract_time_points：提取的时间点，单位为秒，为元组数据，比如，(2, 3, 5)表示只提取视频第2秒， 第3秒，第5秒图片initial_extract_time：提取的起始时刻，单位为秒，默认为0（即从视频最开始提取）end_extract_time：提取的终止时刻，单位为秒，默认为None（即视频终点）extract_time_interval：提取的时间间隔，单位为秒，默认为-1（即输出时间范围内的所有帧）output_prefix：图片的前缀名，默认为frame，那么图片的名称将为frame_000001.jpg、frame_000002.jpg、frame_000003.jpg......jpg_quality：设置图片质量，范围为0到100，默认为100（质量最佳）isColor：如果为False，输出的将是黑白图片
目前只支持输出
jpg格式图片
3. 例子
下面来测试一下这个函数的功能：
- 设置
only_output_video_info为True，将只输出视频信息，不提取图片
>>> pathIn = 'test.mp4'
>>> video2frames(pathIn, only_output_video_info=True)
only output the video information (without extract frames)::::::
Duration of the video: 5.28 seconds
Number of frames: 132
Frames per second (FPS): 25.0可以看到，视频
test.mp4的长度为5.28秒，共132帧，帧率为25.0
- 提取所有图片，并保存到指定文件夹下
>>> pathIn = 'test.mp4'
>>> pathOut = './frames1/'
>>> video2frames(pathIn, pathOut)
Converting a video into frames......
Write a new frame: True, 1/132
Write a new frame: True, 2/132
..............................
Write a new frame: True, 131/132
Write a new frame: True, 132/132可以看到，视频的132帧图片全部提取到
frames1文件夹下
- 设置
extract_time_points参数，提取特定时间点的图片
>>> pathIn = 'test.mp4'
>>> pathOut = './frames2'
>>> video2frames(pathIn, pathOut, extract_time_points=(1, 2, 5))
Write a new frame: True, 1th
Write a new frame: True, 2th
Write a new frame: True, 3th可以看到，只提取了第1秒，第2秒和第5秒图片
- 每隔一段时间提取图片，并设置初始时刻和终止时刻
>>> pathIn = 'test.mp4'
>>> pathOut = './frames3'
>>> video2frames(pathIn, pathOut,
initial_extract_time=1,
end_extract_time=3,
extract_time_interval = 0.5)
Converting a video into frames......
Write a new frame: True, 1th
Write a new frame: True, 2th
Write a new frame: True, 3th
Write a new frame: True, 4th
Write a new frame: True, 5th可以看到，1到3秒内的视频每隔0.5秒提取图片，共5张图片（分别为1s, 1.5s, 2s, 2.5s, 3s时刻的图片）
- 设置
jpg_quality参数，改变输出图片的质量
>>> pathOut = './frames4'
>>> pathIn = 'test.mp4'
>>> video2frames(pathIn, pathOut, extract_time_points=(0.3, 2), jpg_quality=50)
Write a new frame: True, 1th
Write a new frame: True, 2th- 设置
isColor参数为False，提取的照片将是黑白色
>>> pathOut = './frames5'
>>> pathIn = 'test.mp4'
>>> video2frames(pathIn, pathOut, extract_time_points=(0.3, 2), isColor=False)
Write a new frame: True, 1th
Write a new frame: True, 2thvideo2frames()函数的功能测试到此结束。
4. 完整代码
函数为通用型的，因此代码较长，可能还存在可以优化的地方，仅供参考。
完整代码如下：
# -*- coding: utf-8 -*-
import os
import cv2 ##加载OpenCV模块
def video2frames(pathIn='',
pathOut='',
only_output_video_info = False,
extract_time_points = None,
initial_extract_time = 0,
end_extract_time = None,
extract_time_interval = -1,
output_prefix = 'frame',
jpg_quality = 100,
isColor = True):
'''
pathIn：视频的路径，比如：F:\python_tutorials\test.mp4
pathOut：设定提取的图片保存在哪个文件夹下，比如：F:\python_tutorials\frames1\。如果该文件夹不存在，函数将自动创建它
only_output_video_info：如果为True，只输出视频信息（长度、帧数和帧率），不提取图片
extract_time_points：提取的时间点，单位为秒，为元组数据，比如，(2, 3, 5)表示只提取视频第2秒， 第3秒，第5秒图片
initial_extract_time：提取的起始时刻，单位为秒，默认为0（即从视频最开始提取）
end_extract_time：提取的终止时刻，单位为秒，默认为None（即视频终点）
extract_time_interval：提取的时间间隔，单位为秒，默认为-1（即输出时间范围内的所有帧）
output_prefix：图片的前缀名，默认为frame，图片的名称将为frame_000001.jpg、frame_000002.jpg、frame_000003.jpg......
jpg_quality：设置图片质量，范围为0到100，默认为100（质量最佳）
isColor：如果为False，输出的将是黑白图片
'''
cap = cv2.VideoCapture(pathIn) ##打开视频文件
n_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) ##视频的帧数
fps = cap.get(cv2.CAP_PROP_FPS) ##视频的帧率
dur = n_frames/fps ##视频的时间
##如果only_output_video_info=True, 只输出视频信息，不提取图片
if only_output_video_info:
print('only output the video information (without extract frames)::::::')
print("Duration of the video: {} seconds".format(dur))
print("Number of frames: {}".format(n_frames))
print("Frames per second (FPS): {}".format(fps))
##提取特定时间点图片
elif extract_time_points is not None:
if max(extract_time_points) > dur: ##判断时间点是否符合要求
raise NameError('the max time point is larger than the video duration....')
try:
os.mkdir(pathOut)
except OSError:
pass
success = True
count = 0
while success and count < len(extract_time_points):
cap.set(cv2.CAP_PROP_POS_MSEC, (1000*extract_time_points[count]))
success,image = cap.read()
if success:
if not isColor:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) ##转化为黑白图片
print('Write a new frame: {}, {}th'.format(success, count+1))
cv2.imwrite(os.path.join(pathOut, "{}_{:06d}.jpg".format(output_prefix, count+1)), image, [int(cv2.IMWRITE_JPEG_QUALITY), jpg_quality]) # save frame as JPEG file
count = count + 1
else:
##判断起始时间、终止时间参数是否符合要求
if initial_extract_time > dur:
raise NameError('initial extract time is larger than the video duration....')
if end_extract_time is not None:
if end_extract_time > dur:
raise NameError('end extract time is larger than the video duration....')
if initial_extract_time > end_extract_time:
raise NameError('end extract time is less than the initial extract time....')
##时间范围内的每帧图片都输出
if extract_time_interval == -1:
if initial_extract_time > 0:
cap.set(cv2.CAP_PROP_POS_MSEC, (1000*initial_extract_time))
try:
os.mkdir(pathOut)
except OSError:
pass
print('Converting a video into frames......')
if end_extract_time is not None:
N = (end_extract_time - initial_extract_time)*fps + 1
success = True
count = 0
while success and count < N:
success,image = cap.read()
if success:
if not isColor:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
print('Write a new frame: {}, {}/{}'.format(success, count+1, n_frames))
cv2.imwrite(os.path.join(pathOut, "{}_{:06d}.jpg".format(output_prefix, count+1)), image, [int(cv2.IMWRITE_JPEG_QUALITY), jpg_quality]) # save frame as JPEG file
count = count + 1
else:
success = True
count = 0
while success:
success,image = cap.read()
if success:
if not isColor:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
print('Write a new frame: {}, {}/{}'.format(success, count+1, n_frames))
cv2.imwrite(os.path.join(pathOut, "{}_{:06d}.jpg".format(output_prefix, count+1)), image, [int(cv2.IMWRITE_JPEG_QUALITY), jpg_quality]) # save frame as JPEG file
count = count + 1
##判断提取时间间隔设置是否符合要求
elif extract_time_interval > 0 and extract_time_interval < 1/fps:
raise NameError('extract_time_interval is less than the frame time interval....')
elif extract_time_interval > (n_frames/fps):
raise NameError('extract_time_interval is larger than the duration of the video....')
##时间范围内每隔一段时间输出一张图片
else:
try:
os.mkdir(pathOut)
except OSError:
pass
print('Converting a video into frames......')
if end_extract_time is not None:
N = (end_extract_time - initial_extract_time)/extract_time_interval + 1
success = True
count = 0
while success and count < N:
cap.set(cv2.CAP_PROP_POS_MSEC, (1000*initial_extract_time+count*1000*extract_time_interval))
success,image = cap.read()
if success:
if not isColor:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
print('Write a new frame: {}, {}th'.format(success, count+1))
cv2.imwrite(os.path.join(pathOut, "{}_{:06d}.jpg".format(output_prefix, count+1)), image, [int(cv2.IMWRITE_JPEG_QUALITY), jpg_quality]) # save frame as JPEG file
count = count + 1
else:
success = True
count = 0
while success:
cap.set(cv2.CAP_PROP_POS_MSEC, (1000*initial_extract_time+count*1000*extract_time_interval))
success,image = cap.read()
if success:
if not isColor:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
print('Write a new frame: {}, {}th'.format(success, count+1))
cv2.imwrite(os.path.join(pathOut, "{}_{:06d}.jpg".format(output_prefix, count+1)), image, [int(cv2.IMWRITE_JPEG_QUALITY), jpg_quality]) # save frame as JPEG file
count = count + 1
##### 测试
pathIn = 'test.mp4'
video2frames(pathIn, only_output_video_info = True)
pathOut = './frames1/'
video2frames(pathIn, pathOut)
pathOut = './frames2'
video2frames(pathIn, pathOut, extract_time_points=(1, 2, 5))
pathOut = './frames3'
video2frames(pathIn, pathOut,
initial_extract_time=1,
end_extract_time=3,
extract_time_interval = 0.5)
pathOut = './frames4/'
video2frames(pathIn, pathOut, extract_time_points=(0.3, 2), isColor = False)
pathOut = './frames5/'
video2frames(pathIn, pathOut, extract_time_points=(0.3, 2), jpg_quality=50)本文章为转载内容，我们尊重原作者对文章享有的著作权。如有内容错误或侵权问题，欢迎原作者联系我们进行内容更正或删除文章。
