Documentation for C-Werk 2.0.

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The hardware requirements for the neural analytics (see General information on Neural Analytics) are:

  1. Some NVIDIA SDK specific features allow the neural analytics to work only on Windows Server 2019 or Windows 10. 

  2. For neural analytics operation, you may use CPU, GPU NVIDIA, VPU (Intel NCSIntel HDDL).

    Attention!

    • To connect Intel NCS, insert the device into a USB port and make sure that it is recognized by Windows OS as a USB device with one of the following names: Movidius, Myriad X, or VSC Loopback Device. Intel NCS may be used with any PC that meets C-Werk hardware requirements (see Hardware requirements).
    • We do not recommend using more than one Intel NCS device per Server. You can use several Intel HDDL devices on the Server if they have the same revisions.
    • For Intel HDDL to work correctly with AMD processors, pre-install the OpenVINO™ toolkit version 2019.3.379 (see docs.openvino.ai).
  3. If the detection tool uses CPU or Intel GPU resources, the following requirements should be met:

    1. Supported CPUs:
      1. 6th-10th Generation Intel® Core™ processors;

        Attention!

        When using a CPU lower than 6th Generation Intel® Core™ processors, the operation of the detection tool is not guaranteed.

      2. Intel® Xeon® v5 family;
      3. Intel® Xeon® v6 family;
      4. Intel® Movidius™ Neural Compute Stick;
      5. Intel® Neural Compute Stick 2;
      6. Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
    2. OpenVino should support the Intel CPU in use (see https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/system-requirements.html).
    3. CPU should support the AVX2 or AVX512 instruction set (see https://ark.intel.com/content/www/us/en/ark/search/featurefilter.html?productType=873&1_Filter-InstructionSetExtensions=3533&1_Filter-Family=595).
  4. Video card: NVIDIA GeForce 1050 Ti or higher. Requirements:
    1. At least 2 GB of memory;
    2. CUDA 11.1—11.4;
    3. Compute Capability 3.5—8.6.

      Attention!

      • CUDA is compatible with generations of computers with the following architectures: Kepler (partially), Maxwell, Pascal, Volta, Turing, Ampere (partially) (see CUDA).
      • You can check Compute Capability GPU version on the manufacturer's website.
      • If you use NVIDIA graphics cards, make sure to download the latest drivers from the manufacturer's website.

When using a video card, a single neural network requires 500 MB of video memory, except for the neural network for face detection (see Hardware requirements for face detection) and license plate recognition (RR) (see Hardware requirements for License plate recognition (RR)). For example: a neural fire detection tool and a neural smoke detection tool, both with unlimited number of channels, require a 1 GB graphics card or higher. You can use multiple video cards in your system.

Attention!

For correct operation of each detection tool, video image should match a specified set of requirements. The requirements for each detection tool are listed in the corresponding sections (see Configuring detection tools).

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