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General information

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 3.11, a utility was added to the Neuro Pack add-ons (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.

Optimizing the operation of neural analytics on GPU

To optimize the operation of the neural analytics on GPU, do the following:

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 root superuser:

   1. Execute In the following command in prompt, run the terminalcommand:

      Code Block
      language bash
      sudo -i

   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 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. Execute 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. Execute 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—human—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 Neural Tracker the neurotracker (see Image search).
  

Creating GPU neural network caches using parameters:

1. -p is a parameter to create a cache for a particular neural network.
   Command example:
   

   Code Block
   ./NeuroPackGpuCacheGenerator -p /opt/AxxonSoft/DetectorPack/NeuroSDK/GeneralNMHumanAndVehicle_Nano_v1.0_GPU_onnx.ann

2. -v is a parameter to output the procedure log to the console during cache generation.
   Command example to automatically create caches of four neural networks included in the Neuro Pack add-ons with log output:
   

   Code Block
   ./NeuroPackGpuCacheGenerator -v

3. --int8=1 is a parameter to create a quantized version of the cache for those neural networks for which quantization is available. By default, the --int8=0 parameter is disabled.
   Command example:
   

   Code Block
   ./NeuroPackGpuCacheGenerator -p /opt/AxxonSoft/DetectorPack/NeuroSDK/GeneralNMHumanAndVehicle_Nano_v1.0_GPU_onnx.ann --int8=1

   Note
   title Attention!
   The neural networks for which the quantization mode is available are included in the Neuro Pack add-ons together with the *.info file.

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

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

   Starting with DetectorPack 3.11, the following neural networks were added:
   

   • GeneralNMHumanAndVehicle_Nano_v1.0_GPU_onnx.ann

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1. • —Person and vehicle (Nano).
   • GeneralNMHumanAndVehicle_Medium_v1.0_GPU_onnx.ann

...

1. • —Person and vehicle (Medium).
   • GeneralNMHumanAndVehicle_Large_v1.0_GPU_onnx.ann

...

1. • —Person and vehicle (Large).

   Starting with DetectorPack 3.12, the following neural networks were added:

   • GeneralNMHumanAndVehicle_Nano_v1.0_GPU_onnx.ann—Person (top-down view Nano).
   • GeneralNMHumanAndVehicle_Medium_v1.0_GPU_onnx.ann—Person (top-down view Medium).
   • GeneralNMHumanAndVehicle_Large_v1.0_GPU_onnx.ann—Person (top-down view Large).