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It can take several minutes to launch neural analytics algorithms on Nvidia GPU after Server restart. Meanwhile, the neural models are optimized for the current GPU type.

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Starting with DetectorPack 3.9, a utility was added to the Neuro Pack add-ons (see see Installing DetectorPack add-ons), which allows you to create GPU neural network caches without using Axxon One. The presence of the cache speeds up the initialization and optimizes video memory consumption.

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1. Stop the Server (see Starting and stopping the Axxon One Server in Linux OS).
   

   Note
   title Attention!
   If the system has the software running on GPU, it is necessary to stop its operation.

2. Login as ngp superuser:

   1. In the command prompt, run the command:

      Code Block
      language bash
      sudo su ngp

   2. Enter the password for the root superuser.

3. Create a folder with a custom name to store the cache. For example:

   Code Block
   language bash
   mkdir /opt/AxxonSoft/AxxonOne/gpucache

4. Change folder permissions:

   Code Block
   language bash
   chmod -R 777 /opt/AxxonSoft/AxxonOne/gpucache

5. Create the GPU_CACHE_DIR system variable:

   1. Go to the /opt/AxxonSoft/AxxonOne/ folder:

      Code Block
      language bash
      cd /opt/AxxonSoft/AxxonOne

   2. Open the instance.conf file for editing:

      Code Block
      language bash
      nano instance.conf

   3. Add the following line to the file:

      Code Block
      language bash
      export GPU_CACHE_DIR="/opt/AxxonSoft/AxxonOne/gpucache"

   4. Save the file using the Ctrl+O keyboard shortcut.

   5. Exit file editing mode using the Ctrl+X keyboard shortcut.

   6. Run the following command in the terminal:

      Code Block
      language bash
      export GPU_CACHE_DIR="/opt/AxxonSoft/AxxonOne/gpucache"

6. Go to the /opt/AxxonSoft/DetectorPack/ folder:

   Code Block
   language bash
   cd /opt/AxxonSoft/DetectorPack

7. Run the following command:

   Code Block
   language bash
   ./NeuroPackGpuCacheGenerator

   Note
   title Attention!
   If more than one Nvidia GPU is available, you will be able to select one. To do this, specify a number from 0 to 3 which corresponds to the required device in the list.

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• GeneralNMHuman_v1.0GPU_onnx.ann—person;
• smokeScanned_v1_onnx.ann—smoke detection;
• fireScanned_v1_onnx.ann—fire detection;
• reid_15_0_256__osnetfpn_segmentation_noise_20_common_29_onnx.ann—search for the similar in the neurotracker Neural tracker (see Image Similitude search).
  

Creating GPU neural network caches using parameters

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The neural networks for which the quantization mode is available (see Neurotrackersee Neural tracker, Stopped object detector, Neurocounter Neural counter):

• GeneralNMCar_v1.0GPU_onnx.ann—Vehicle.
• GeneralNMHuman_v1.0GPU_onnx.ann—Person.
• GeneralNMHumanTopView_v0.8GPU_onnx.ann—Person (top-down view).

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