To configure the Neural classifier, do the following:
- Go to the Detectors tab.
- Below the required camera, click Create… → Category: Production Safety → Neural classifier.
By default, the detector is enabled and set to detect objects in the frame.
If necessary, you can change the detector parameters. The list of parameters is given in the table:
| Parameter | Value | Description |
|---|
| Object features |
| Record mask to archive | Yes | By default, the sensitivity scale of the detector is recorded to the archive (see Displaying information from a detector (mask)). To disable the parameter, select the No value |
| No |
| Video stream | Main stream | If the camera supports multistreaming, select the stream for which detection is needed. Selecting a low-quality video stream reduces the load on the |
Server| server |
| Other |
| Enable | Yes | The detector is enabled by default. To disable the detector, select the No value |
| No |
| Name | Neural classifier | Enter the detector name or leave the default name |
| Decoder mode | Auto | Select a processing resource for decoding video streams. When you select a GPU, a stand-alone graphics card takes priority (when decoding with |
NVIDIA Nvidia NVDEC chips). If there is no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources |
will be are used for decoding |
| CPU |
| GPU |
| HuaweiNPU |
| Number of frames processed per second | 0.1 | Specify the number of frames that the detector will process per second. The value must be in the range [0.016 |
; | , 100] |
| Selected object classes | | If necessary, specify the class of the detected object. If you want to display tracks of several classes, specify them separated by a comma with a space. For example, 1, 10.
- If you leave the field blank, the tracks of all available classes from the neural network
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will be - are displayed (Neural network file).
- If you specify a class/classes from the neural network, the tracks of the specified class/classes
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will be - are displayed (Neural network file).
- If you specify a class/classes from the neural network and a class/classes missing from the neural network, the tracks of a class/classes from the neural network
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will be - are displayed (Neural network file).
If you specify a class/classes missing from the neural network, the tracks
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won’t be aren't displayed (Neural network file)
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| Type | Neural classifier | Name of the detector type (non-editable field) |
| Advanced settings |
| Neural network file |
| |
the the network To ensure the correct operation of the neural network - You cannot specify the network file in Windows OS. You must place the neural network file locally, that is, on the same server where you install Axxon One.
- For correct neural network operation on Linux OS, place the corresponding file
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must be located - locally in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory
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. - or in the network folder with the corresponding access rights.
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| Number of measurements in a row to trigger detection | 5 | Specify the minimum number of frames on which the detector must detect an object to generate an event. The value must be in the range [5 |
; , 20] |
| Scanning mode | Yes | The parameter is disabled by default. To detect objects without changing the frame size, select the Yes value. To work in the scanning mode, the neural network must support the scanning mode |
| No |
| Basic settings |
| Mode | CPU | |
other - another processing resource than the CPU, this device
|
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will carry the - carries most of the computing load. However, the CPU
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will be - used to run the detector.
- Starting with Detector Pack 3.11, Intel HDDL and Intel NCS aren’t supported.
- Starting with Detector Pack 3.14, Intel Multi-GPU and Intel GPU 0-3 are supported.
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|
| Nvidia GPU 0 |
| Nvidia GPU 1 |
| Nvidia GPU 2 |
| Nvidia GPU 3 |
| Intel GPU |
| Intel NCS (not supported) |
| Intel Multi-GPU |
| Intel GPU 0 |
| Intel GPU 1 |
| Intel GPU 2 |
| Intel GPU 3 |
| Intel HDDL (not supported) |
| Huawei NPU |
| Sensitivity | 33 | Specify the sensitivity of the detector empirically. The value must be in the range [1 |
; , 99]. The preview window displays the sensitivity scale of the detector that relates to the sensitivity parameter. If the scale is green, the object isn't detected. If the scale is yellow, an object is detected, but not enough to generate an event. If the scale is red, an object is detected, and the detector will generate an event |
, Example. if the scale is red through the sampling period (50 seconds by default). |
The sensitivity parameter value of 40 means that the detector will generate an event when the scale has at least four divisions full over the entire detection period. An event will |
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stop end when the scale has less than two divisions full over the detection period. The detector will generate an event again if the scale has at least four divisions full over the entire detection period. |
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By default, the entire frame is a detection area. In the preview window, you can specify the detection areas using the anchor points points 
Image Modified (see Configuring a detection area):
- Right-click in the preview window.
- If you want to specify the detection area by one or more rectangles, select Detection area (rectangle). If you specify a rectangular area, the detector will analyze only this area. The rest of the frame
will be - is ignored.
Image Modified - If you want to specify the detection area by one or more polygons, select Detection area (polygon). If you specify one or several polygonal areas, the detector will analyze the entire frame. The part of the frame not included in the specified polygons
will be - is blacked out.
Image Modified
| Note |
|---|
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You must select the detection area (polygon or rectangle) experimentally. |
For For some neural networks, the quality of detection will be better with a rectangle, for others—with a polygon. |
| Info |
|---|
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- For convenience of configuration, you can "freeze" the frame. Click the
 Image Modified button. To cancel the action, click this button again. - To hide the detection area, click the
 Image Modified button. To cancel the action, click this button again. - To delete the selected area, click the
 Image Modified button.
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To save the parameters of the detector, click the Apply 
Image Modified button. To cancel the changes, click the Cancel 
Image Modified button.
Configuration of the Configuring the Neural classifier is complete.
