are you running two chained jevois-daemon instances, one in the camera and then one on your host?
your videomapping is ok. However, when you run jevois-daemon on host, you should disconnect your jevois camera and use a plain webcam that supports 640x480 instead. Otherwise, jevois will run one instance of jevois-daemon in the camera, and then your host will run a second instance on your host computer. If you don't want to see the demo with the baby running in your jevois camera, then you should add a video mapping on the SD card that configures for 640x480 as pass-through (dumb camera):
YUYV 640 480 30.0 YUYV 640 480 30.0 JeVois PassThrough
make sure that one is saved to your microSD card.
Please see here:
http://jevois.org/doc/Concepts.html
this section:
Note that usually one would either:
- Compile and run jevois-daemon in host mode on a host computer: In this case usually a dumb camera will be used (any regular webcam), all machine vision processing runs on the host CPU, and video output is to display; or
- Cross-compile jevois-daemon in platform mode and run it inside the JeVois smart camera: In this case the built-in camera sensor in the JeVois smart camera is used, all machine vision algorithms run on the small processor inside the JeVois smart camera, and video output is streamed over the USB link to a host. The host then runs a dumb video capture software.
But also note that chaining two jevois-daemon processes is possible, with one running inside the camera and a second one running on a host computer. For that to work, you need to make sure that the camera format requested by jevois-daemon running on the host exactly matches an available output format of the jevois-daemon running inside the smart camera. Such scenario may be useful to split image processing tasks between the JeVois smart camera and a host computer. For example, the JeVois smart camera could capture video and detect edges, and then transmit the edge maps over USB to a host computer that would capture them and process them further to detect and identify objects in the edge maps.