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To configure the Human pose detector, do the following:
- Go to the Detection
- Detection Tools tab
- tab.
- Below the required camera, click
- click Create… → Category: Poses → Human pose detector.
By default, the detection tool is enabled and set to detect poses.
If necessary, you can change the detection tool parameters. The list of parameters is given in the table:
| Parameter | Value | Description |
|---|---|---|
| Object features | ||
| Record objects tracking | Yes | The metadata of the video stream is recorded to the database by default. 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 allows reducing the load on the Server |
| Second stream | ||
| Other | ||
| Enable | Yes | The detection tool is enabled by default. To disable the detection tool, select the No |
| value | ||
| No | ||
| Name | Human pose detector | Enter the detection tool 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 NVDEC chips). If there is no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources will be used for decoding |
| CPU | ||
| GPU | ||
| HuaweiNPU | ||
| Number of frames processed per second | 3 | Specify the number of frames that the detection tool will process per second. The value must be in the |
range [0.016; 100]
|
|
| ||
| Type | Human pose detector | Name of the detection tool type (non-editable field) |
Advanced settings If detection of small objects | ||
or objects in areas far away from the camera is ineffective, you can use the scanning mode (see Configuring the scanning mode). |
This mode doesn’t provide absolute detection accuracy, but can improve detection performance | ||
| Neural network file | Select a neural network file. The standard neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory. | |
You don't need to select the standard neural networks in this field, the system will automatically select the required one. If you use a custom neural network, enter a path to the file.
| ||||||||||
| Scanning window | Yes | The scanning mode is disabled by default. To enable the scanning mode, select the Yes value | ||||||||
| No | ||||||||||
| Scanning window height | 540 | The height and width of the scanning window are determined according to the actual size of the frame and the required number of windows. For example, the real frame size is 1920×1080 pixels. To divide the frame into four equal windows, set the width of the scanning window to 960 pixels and the height to 540 pixels | ||||||||
| Scanning window step height | 540 | The scanning step determines the relative offset of the windows. If the step is equal to the height and width of the scanning window respectively, the segments will line up one after another. Reducing the height or width of the scanning step will increase the number of windows due to their overlapping each other with an offset. This will increase the detection accuracy, but will also increase the CPU load
| ||||||||
| Scanning window step width | 480 | The scanning step determines the relative offset of the windows. If the step is equal to the height and width of the scanning window respectively, the segments will line up one after another. Reducing the height or width of the scanning step will increase the number of windows due to their overlapping each other with an offset. This will increase the detection accuracy, but will also increase the CPU load
| ||||||||
| Scanning window width | 480 | The height and width of the scanning window are determined according to the actual size of the frame and the required number of windows. For example, the real frame size is 1920×1080 pixels. To divide the frame into four equal windows, set the width of the scanning window to 960 pixels and the height to 540 pixels | ||||||||
| Basic settings | ||||||||||
| Mode | CPU | Select the operation mode of the detection tool and neural filter (see Hardware requirements for neural analytics operation, Selecting Nvidia GPU when configuring detectors). Neural filter operation mode is used only if you select the Yes value in the Neural filter parameter.
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| ||
| Nvidia GPU 0 | ||
| Nvidia GPU 1 | ||
| Nvidia GPU 2 | ||
| Nvidia GPU 3 | ||
| Intel GPU | ||
| Huawei NPU | ||
| Pose estimation neural network | Pose estimation | Select a pose estimation neural network. The names may indicate the size of the neural network. The size (Nano, Middle, Large) of the neural network indicates the amount of resources consumed. The larger the neural network, the higher the accuracy but the higher the loadon the processor
|
| Pose estimation (Nano) | ||
| Pose estimation (Middle) | ||
| Pose estimation (Large) | ||
| Neural network filter | ||
| Neural filter | Yes | Neural filter is disabled by default. To use the neural filter to filter out parts of tracks, select the Yes value |
| No | ||
| Neural filter file | Select a neural network file | |
By default, the entire frame is a detection area. In the preview window, you can specify the custom detection areas and skip areas. To specify areas, right-click the frame, and select the required area (see Configuring a skip area, Configuring a detection area).
The following logic is used for this:
- if you specify only detection areas, no detection will be performed in all other parts of the frame;
- if you specify only skip areas, detection will be performed in all other parts of the frame.
| Info | ||
|---|---|---|
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To save the parameters of the detection tool, click the Apply 
button. To To cancel the changes, click the Cancel 
button.
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