Mirasys VCA Deep Learning
Requirements
Nvidia GPU with CUDA cores
A NVIDIA GPU with CUDA Compute Capability 7.5 or higher
Depending on GPU CUDA cores, how many Deep Learning channels you can use on the system
The latest NVIDIA graphics drivers (at least 460.73 or higher).
CUDA Toolkit
Mirasys VMS 9.4 or newer
Deep Learning object files
Installation
Install latest Nvidia drivers to the system
Download Mirasys VCA Deep Learning package from Mirasys Extranet
Extract the package
Browse to folder CUDA Toolkit
Install CUDA Toolkit with all features
You can find detailed installation guide here.
Some features are not installed because Microsoft Visual Studio is not needed to install but the toolkit is providing example files
If you have installed already Mirasys VMS, before copying files VMS services need to stop
Stop services: WDServer, DVRServer and SMServer
This is not needed to do if you are using V9.6 or newer
Copy the content of the VCA Deep Learning files folder to C:\Program Files\DVMS\DVR\vca\bin location
This is not needed to do if you are using V9.6 or newer
This path is the default installation location of Mirasys VMS
If you have installed Mirasys VMS to another location, copy files there
Start WDServer, DVRServer and SMServer services
This is not needed to do if you are using V9.6 or newer
Now you have installed and are ready to go with Deep Learning tracking.
Licensing is done via local VCA Deep Learning licensing or using License Server (Virtual Environment or if you want to handle licenses in one place).
Some cases detection may not work correctly. Please try to increase image quality or move/zoom camera image to closer wanted detection area.
Models are trained using clear images and some cases when using black/white image or thermal camera image this may cause that detection is working correctly. For this you can try use Deep Learning Filter with Object Tracker.