mlogger (history_image) now supports rtsp cameras, in ALPHA we have
acquisitioned several new network connected cameras. Unfortunately they dont
have a way of just capturing a single frame using libcurl
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Motivation to link to OpenCV libraries
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After looking at the ffmpeg libraries, it seemed non trivial to use them to
listen to a rtsp stream and write a series of jpgs.
OpenCV became an obvious choice (it is itself linked to ffmpeg and
gstreamer), its a popular, multiplatform, open source library that's easy to
use. It is available in the default package managers in centos 7 and ubuntu
(an is installed by default on lxplus).
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How it works:
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The framework laid out in history_image.cxx is great. A separate thread is
dedicated for each camera. This is continued with the rtsp support, using
the same periodicity:
if (ss_time() >= o["Last fetch"] + o["Period"]) {
An rtsp camera is detected by its URL, if the URL starts with ‘rtsp://’ its
obvious its using the rtsp protocol and the cv::VideoCapture object is
created (line 147).
If the connection fails, it will continue to retry, but only send an error
message on the first 10 attempts (line 150). This counter is reset on
successful connection
If MIDAS has been built without OpenCV, mlogger will send an error message
that OpenCV is required if a rtsp URL is given (line 166)
The VideoCapture ‘stays live' and will grab frames from the camera based on
the sleep, saving to file based on the Period set in the ODB.
If the VideoCapture object is unable to grab a frame, it will release() the
camera, send an error message to MIDAS, then destroy itself, and create a
new version (this destroy and create fully resets the connection to a
camera, required if its on flaky wifi)
If the VideoCapture gets an empty frame, it also follows the same reset
steps.
If the VideoCaption fills a cv::Frame object successfully, the image is
saved to disk in the same way as the curl tools.
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Concerns for the future:
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VideoCapture is decoding the video stream in the background, allowing us to
grab frames at will. This is nice as we can be pretty agnostic to the video
format in the stream (I tested with h264 from a TP-LINK TAPO C100, but the
CPU usage is not negligible.
I noticed that this used ~2% of the CPU time on an intel i7-4770 CPU, given
enough cameras this is considerable. In ALPHA, I have been testing with 10
cameras:
elog:2220/1
My suggestion / request would be to move the camera management out of
mlogger and into a new program (mcamera?), so that users can choose to off
load the CPU load to another system (I understand the OpenCV will use GPU
decoders if available also, which can also lighten the CPU load). |