Requirements and recommendations for the Tracking module🔗
Hardware and software
It is required to install a neural-networks to track people, vehicles, and animals (if Filter by categories is enabled). In this case, the following equipment is required:
Warning
install the Eocortex Neural Networks package package must be installed before it will be possible to use neural networks-based features of the module.
The following equipment is required to use this neural network-based module:
A processor that supports AVX instructions is required;
Swap file at least half of the total RAM size.
It is also possible (optional) to use a video card. In this case, an NVIDIA video card (GPU) with a computing capability index of at least 6.5 and a memory size of at least 4GB is required, and the characteristics and performance of the graphics card must be at least as good as the NVIDIA GTX 1650 Super.
If the package will be installed on a virtual machine, it may additionally be required to:
Enable support for AVX instructions in the guest machine settings;
Use GRID drivers for GPU virtualization.
Warning
Eocortex must use video cards selected for running neural networks in monopoly mode. It is not allowed to use such card for other applications or tasks that consume GPU resources, including for displaying video. Simultaneous use of a video card for several tasks may lead to incorrect system operation: from analytics performance degradation to server instability.
Warning
The neural network works with the 64-bit version of Eocortex only.
Warning
When upgrading Eocortex to another version, it is necessary to also upgrade the install the Eocortex Neural Networks package package to the corresponding version.
Warning
When using a video card, the stable operation of the module is guaranteed on operating systems Windows 10, Windows Server 2016, Ubuntu 20.04, as well as on the newer versions of these operating systems.
On other operating systems (Windows versions 7 and 8, Windows Server versions 2008 and 2012, Debian), issues may arise when trying to use NVIDIA graphics cards. On Windows 8, this is due to the cessation of support for NVIDIA graphics card drivers. On Debian, the problem is due to the high complexity of installing workable versions of video card drivers.
Video stream
Frame frequency: no lower than 10 frames per second;
Image resolution: no lower than HD (1280x720).
Image
Lighting in the frame should be uniform and constant.
If the camera is installed in front of a bright light source (the sun behind the entrance door, etc.), it is necessary to adjust the exposure (or brightness) so that the objects in the frame have a natural color (not overexposed or too dark). In this case, an overexposed background is acceptable.
The image must be in color.
Image quality should be at least average. There should be no significant compression artifacts.
Scene and camera position
The object should be seen from a suitable angle so that it is positively distinguishable from the background and clearly visible to the human eye.
The frame must not contain reflective surfaces: glass, mirrors, etc.
It is permitted to place the camera overhead. In this case, the angle of inclination of the camera in relation to the horizontal must not exceed 45°.
Recognition of vehicles
Minimum requirements to ensure the identification of vehicles are as follows:
The resolution must be at least HD (1280x720).
Detection of vehicles must be performed during daylight hours in good weather.
Exposure and contrast on the camera must be set so that the color of the object can be unambiguously detected by the human eye.
The body of a vehicle must not be light-struck by headlights or other light sources. There must not be any bright glare on the body.
The angle of view must provide correct identification of the type of vehicle (e.g., it is sometimes difficult to distinguish a bus from a truck when viewed from behind).
Installing the camera at an angle to the axis of movement of vehicles provides the most favorable perspective.
Examples
Below are the examples of angles for determining the mode of transport.
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