The fork() architecture from the previous commit is also deemed a
failure. Reverted back to v1.5.t19 code. I'll start from scratch, using
this commit as the new base.
The app was still cutting out last command line arg of my test setup.
Later found out it was the run script limiting the command line arg
count to 3. I extended it out to 8 but I'll need to find a better option
to make it limitless.
Added another debug clause for opencv videoio so it will provide even
more debug information. Going back to implicitly defining FFMPEG as the
videoio for opencv, turns out FFMPEG is the only real stable option to
use when it comes to reading video files with opencv. Any other option
would just severely limit codec and container support.
Added the ability change the video codec via the config file.
Changed the install script to now install the application in the /opt
directory and then symm link to /usr/bin. Doing this allowed me to
create a run script to start the application and enable the
OPENCV_VIDEOIO_DEBUG parameter for opencv. This should make it easier to
diagnose video-io issues with opencv.
Updated the README documentation with all of the changes done to the
application since v1.5.
AI object detection via yolov5 didn't work out too well, in fact it was
crashing the detection threads for whatever reason. I could deep dive
why it was crashing but I think the better solution is to bring back
optical flow detection at the block level. the advantage of this over
object detection is the fact that a block doesn't need to have a whole
object in it.
added object detection code base on yolov5 machine vision model. also
added a stat file so motion and object detection values can be monitored
in real time if used with the 'watch' command.
created setup, build and install scripts to make it easier and
convenient to compile and install the application from source. no plans
distribute pre-compiled binaries because it's just so much easier to
guarantee the application will actually work in the target machine when
compiled by the target machine.
