从Python中读取RTSP流中的帧

时间:2013-07-31 03:54:53

标签: python video video-streaming rtsp

我最近设置了一个Raspberry Pi摄像头,并通过RTSP传输帧。虽然它可能不是完全必要的,但这是我正在使用广播视频的命令:

raspivid -o - -t 0 -w 1280 -h 800 |cvlc -vvv stream:///dev/stdin --sout '#rtp{sdp=rtsp://:8554/output.h264}' :demux=h264

这完美地播放了视频。

我现在要做的是用Python解析这个流并分别读取每个帧。我想做一些运动检测用于监视目的。

我完全迷失在这个任务的起点。谁能指点我一个好的教程?如果这不能通过Python实现,我可以使用哪些工具/语言来实现这一目标?

6 个答案:

答案 0 :(得分:10)

一个hacky解决方案,但你可以使用VLC python bindings(你可以用pip install python-vlc安装它)并播放流:

import vlc
player=vlc.MediaPlayer('rtsp://:8554/output.h264')
player.play()

然后每隔一秒拍一次快照:

while 1:
    time.sleep(1)
    player.video_take_snapshot(0, '.snapshot.tmp.png', 0, 0)

然后您可以使用SimpleCV或其他内容进行处理(只需将图像文件'.snapshot.tmp.png'加载到您的处理库中)。

答案 1 :(得分:4)

使用opencv

video=cv2.VideoCapture("rtsp url")

然后你可以捕获framse。阅读openCV文档访问:https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_gui/py_video_display/py_video_display.html

答案 2 :(得分:3)

使用“ depu”列出的相同方法非常适合我。 我只是用实际摄像机的“ RTSP URL”替换了“视频文件”。 以下示例适用于AXIS IP摄像机。 (这在以前的OpenCV版本中暂时无法使用) 在OpenCV 3.4.1 Windows 10上可以使用

import cv2
cap = cv2.VideoCapture("rtsp://root:pass@192.168.0.91:554/axis-media/media.amp")

while(cap.isOpened()):
    ret, frame = cap.read()
    cv2.imshow('frame', frame)
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

答案 3 :(得分:2)

根据流类型,您可以查看此项目以获取一些想法。

https://code.google.com/p/python-mjpeg-over-rtsp-client/

如果你想成为mega-pro,你可以使用http://opencv.org/(我认为可用的Python模块)来处理运动检测。

答案 4 :(得分:0)

您可以使用python和OpenCV实现视频中的阅读框架。下面是示例代码。适用于python和opencv2版本。

import cv2
import os
#Below code will capture the video frames and will sve it a folder (in current working directory)

dirname = 'myfolder'
#video path
cap = cv2.VideoCapture("TestVideo.mp4")
count = 0
while(cap.isOpened()):
    ret, frame = cap.read()
    if not ret:
        break
    else:
        cv2.imshow('frame', frame)
        #The received "frame" will be saved. Or you can manipulate "frame" as per your needs.
        name = "rec_frame"+str(count)+".jpg"
        cv2.imwrite(os.path.join(dirname,name), frame)
        count += 1
    if cv2.waitKey(20) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

答案 5 :(得分:0)

这里还有一个选择

比其他答案要复杂得多。 :-O

但是,通过这种方式,只需与摄像机建立一个连接,就可以将同一流同时“分叉”到多个多进程,屏幕,将其重播为多播,将其写入磁盘等。

..当然,以防万一,您需要类似的东西(否则,您会更喜欢早先的答案)

我们创建两个独立的python程序:

(1)服务器程序(rtsp连接,解码) server.py

(2)客户端程序(从共享内存中读取帧) client.py

服务器必须在客户端之前启动,即

python3 server.py

然后在另一个终端:

python3 client.py

代码如下:

(1) server.py

import time
from valkka.core import *

# YUV => RGB interpolation to the small size is done each 1000 milliseconds and passed on to the shmem ringbuffer
image_interval=1000  
# define rgb image dimensions
width  =1920//4
height =1080//4
# posix shared memory: identification tag and size of the ring buffer
shmem_name    ="cam_example" 
shmem_buffers =10 

shmem_filter    =RGBShmemFrameFilter(shmem_name, shmem_buffers, width, height)
sws_filter      =SwScaleFrameFilter("sws_filter", width, height, shmem_filter)
interval_filter =TimeIntervalFrameFilter("interval_filter", image_interval, sws_filter)

avthread        =AVThread("avthread",interval_filter)
av_in_filter    =avthread.getFrameFilter()
livethread      =LiveThread("livethread")

ctx =LiveConnectionContext(LiveConnectionType_rtsp, "rtsp://user:password@192.168.x.x", 1, av_in_filter)

avthread.startCall()
livethread.startCall()

avthread.decodingOnCall()
livethread.registerStreamCall(ctx)
livethread.playStreamCall(ctx)

# all those threads are written in cpp and they are running in the
# background.  Sleep for 20 seconds - or do something else while
# the cpp threads are running and streaming video
time.sleep(20)

# stop threads
livethread.stopCall()
avthread.stopCall()

print("bye") 

(2) client.py

import cv2
from valkka.api2 import ShmemRGBClient

width  =1920//4
height =1080//4

# This identifies posix shared memory - must be same as in the server side
shmem_name    ="cam_example"
# Size of the shmem ringbuffer - must be same as in the server side
shmem_buffers =10              

client=ShmemRGBClient(
name          =shmem_name,
n_ringbuffer  =shmem_buffers,
width         =width,
height        =height,
mstimeout     =1000,        # client timeouts if nothing has been received in 1000 milliseconds
verbose       =False
) 

while True:
index, isize = client.pull()
if (index==None):
    print("timeout")
else:
    data =client.shmem_list[index][0:isize]
    img =data.reshape((height,width,3))
    img =cv2.GaussianBlur(img, (21, 21), 0)
    cv2.imshow("valkka_opencv_demo",img)
    cv2.waitKey(1)

如果您有兴趣,请在https://elsampsa.github.io/valkka-examples/中查看更多内容