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Documentation for Intellect 4.11.0-4.11.3. Documentation for other versions of Intellect is available too.
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There are 3 types of object classification by the smart detectors in Intellect.
- Standard. The following objects can be classified: a human, a vehicle, an other object (see Cross line detector configuration and Motion in the Area detector configuration).
- Advanced. The following objects can be classified: a human, a group of humans, a vehicle, noise, an object carried into the area, an object carried out of the area, an other object (see the CAM_VMDA_DETECTOR section of the Programming Guide).
- Neural filter — a neural network-based classification. Any objects can be classified to a high precision. The neural network is trained individually for each use case.
Prior to configuring the neural filter, it is recommended to contact the AxxonSoft technical support and request the trained neural networks model files. Technical support specialists will request from you the data needed to prepare the models, and then provide you with the files. These files should be distributed among all the servers where the neural filter will be used.
In most cases, one neural networks model is enough for the standard objects classification (e.g. a human / a vehicle). However, for the non-standard tasks with multiple object classes, more than one model may be required:
- if there are different classification tasks: for example, for some cameras the human/vehicle object classification is required, and for other cameras, the vehicle type (passenger car/freight vehicle) classification is required;
- if different conditions apply to different cameras, and the tracker will work better if each neural network is trained to work under different conditions: for example, the task is to protect the factory perimeter (only the human and vehicle detection is required) and the factory workshop (only the people in special work clothes detection is required).
The neural filter is configured in the following way:
- Install the Detector Pack subsystem (if not already installed). The Detector Pack subsystem installation guide is available in the corresponding documentation section, the most current version of the documentation is in the AxxonSoft documentation repository.
- For the the VMDAEXT key, specify the 1 value (for details on the key, see Registry keys reference guide).
- For the the VMDAEXT.RAM key, specify the value greater than 2000. It is recommended to specify a much more value, for example 16000, depending on the computer hardware resources.
- On the Tracker object settings panel, open the Neurofilter tab (1).
- Set the Use neurofiltering (2) checkbox.
- In the Tracking model field (3), enter the full path to the tracker model file received from the AxxonSoft technical support, or click the ... button and select the file in the standard Windows dialog box.
- In the Tracking device name field (4), enter the name of the device that should be used by the tracker for the objects classification:
- CPU — use the CPU.
GPU0, GPU1, GPU2 ... — use the NVIDIA GPU. Usually GPUs are recognized in the system in the order of their physical installation: the first (usually the upper one) GPU is number 0, the middle one is number 1, and the last (usually the lower one) is number 2.
Note
If there are NVIDIA GPUs in the system, it is recommended to use them. If there are no NVIDIA GPUs in the system, th CPU resources should be used. GPUs from other manufacturers are not supported.
Note
In the 64-bit version of Intellect (Intellect64.exe), the name of the tracking device is selected from the drop-down list of the processors and GPUs available on the computer.
- In the Unattended objects model field (5), enter the full path to the abandoned objects detection model file received from the AxxonSoft technical support, or click the ... button and select the file in the standard Windows dialog box.
In the Unattended objects device name field (6), enter the name of the device that should be used by the tracker for the abandoned objects classification:
Note
For the abandoned objects neural filter operation, it is necessary that the abandoned objects detector of the Tracker object is enabled, and the VMDA detectors are configured appropriately (see Creating and Configuring the Tracker Object and Creating and Configuring VMDA Detection).
Note
In the 64-bit version of Intellect (Intellect64.exe), the name of the abandoned objects device is selected from the drop-down list of the processors and GPUs available on the computer.
- Click the Apply button (7).
The neural filter is configured.