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Documentation for Axxon One 2.0. Documentation for other versions of Axxon One is available too.
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Configuring the detection tool
To configure the Equipment detector, do the following:
- Go to the Detection Tools tab.
- Below the required camera, click Create… → Category: Production Safety → Equipment detector.
By default, the detection tool is enabled and set to detect people who enter or stay in the protected area without the necessary equipment and personal protective equipment (PPE).
If necessary, you can change the detection tool parameters. The list of parameters is given in the table:
| Parameter | Value | Description |
|---|---|---|
| Object features | ||
| Record mask to archive | Yes | By default, mask is recorded to the archive (human body segmentation) (see Displaying information from a detector (mask)). To disable the parameter, select the No value |
| No | ||
| Record objects tracking | Yes | The metadata 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 |
| Other | ||
| Enable | Yes | The detection tool is enabled by default. To disable the detection tool, select the No value |
| No | ||
| Name | Equipment 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 | 1 | Specify the number of frames that the detection tool will process per second. The value must be in the range [0.016; 100]. Attention! To operate the detection in a "gateway" (see Examples of configuring the Equipment detector for solving typical tasks), we recommend using the standard settings of the detection tool: 1 FPS and 3 FPS for output. In conditions of dynamically moving people, we recommend setting the delay to at least 4 FPS, and the number of frames for output to at least 6 FPS. |
| Type | Equipment detector | Name of the detection tool type (non-editable field) |
| Advanced settings | ||
| Сlassification network 1 file | By default, the following neural networks are initialized: Classification neural network (equipment and PPE on the head) and Classification neural network (equipment and PPE on the body) according to the selected processing device in the Neural network mode parameter. To initialize only one item of equipment, select the required classification neural network file. Note To ensure the correct operation of the neural network on Linux OS, the corresponding file must be located in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory. Attention! If you use standard classification neural network (training wasn't performed in operating conditions), we guarantee the overall accuracy of 80-95% and the percentage of false positives of 5-20%. | |
| Сlassification network 2 file | ||
| Сlassification network 3 file | ||
| Сlassification network 4 file | ||
| Сlassification network 5 file | ||
| Mask | Yes | The parameter is disabled by default. If you want to display the human body segmentation in the preview window, select the Yes value |
| No | ||
| Number of measurements in a row to trigger detection | 3 | Specify the minimum number of frames with a violation for the detection tool to generate an event. The value must be in the range [1, 20]. Attention! To operate the detection in a "gateway", we recommend using the standard settings of the detection tool: 1 FPS and 3 FPS for output. In conditions of dynamically moving people, we recommend setting the delay to at least 4 FPS, and the number of frames for output to at least 6 FPS. |
| One event per PPE element | Yes | By default, the detection tool event is generated once for each element of equipment within a track of a person. If you want the detection tool to generate an event for each equipment violation, select the No value. Example An individual not wearing a helmet appears in the frame, puts on a helmet, then puts it off. If the One event per PPE element parameter is enabled, you will have one alarm event, otherwise—two. |
| No | ||
| Segmenting network file | By default, the Segmenting neural network is initialized according to the selected processing device in the Neural network mode parameter. The standard segmenting 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, specify the path to the file. Note To ensure the correct operation of the neural network on Linux OS, the corresponding file must be located in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory. Attention! If you use standard segmenting neural network (training wasn't performed in operating conditions), we guarantee the overall accuracy of 80-95% and the percentage of false positives of 5-20%. | |
| Basic settings | ||
| Min person height | 0.01 | Specify the minimum height and width of a person in the frame as a percentage of the frame height/width (0.15 = 15%). Objects that are smaller than the specified size won't be detected. The value must be in the range [0, 1] |
| Min person width | 0.01 | |
| Neural network mode | CPU | Select a processor for the neural network operation (see Hardware requirements for neural analytics operation, Selecting Nvidia GPU when configuring detectors). Attention!
|
| Nvidia GPU 0 | ||
| Nvidia GPU 1 | ||
| Nvidia GPU 2 | ||
| Nvidia GPU 3 | ||
| Intel GPU | ||
| Invert Results | ||
| Invert results of default network | No | The parameter is disabled by default. To receive events about the detection of equipment that are initialized in the Classification network file parameter by default (Classification neural network (equipment and PPE on the head) and Classification neural network (equipment and PPE on the body)), select the required value from the list
|
| OnlyHelmet | ||
| OnlySafetyVest | ||
| AllNet | ||
| Invert results of network 0 | Yes | The parameter is disabled by default. To receive events about the detection of equipment specified in the Classification network file parameters, set the Yes value in the corresponding parameters Invert results of network
|
| No | ||
| Invert results of network 1 | Yes | |
| No | ||
| Invert results of network 2 | Yes | |
| No | ||
| Invert results of network 3 | Yes | |
| No | ||
| Invert results of network 4 | Yes | |
| No | ||
By default, the entire frame is the detection area. In the preview window, you can specify the detection areas using the anchor points 
(see Configuring a detection area).
Note
- For convenience of configuration, you can "freeze" the frame. Click the
button. To cancel the action, click this button again. - To hide detection area, click the
button. To cancel the action, click this button again.
To save the parameters of the detection tool, click the Apply 
button. To discard the changes, click the Cancel 
button.
The Equipment detector is now configured.
The Equipment detector generates an event when a person is in the frame without the necessary equipment and personal protective equipment on the specified parts of the body or when equipment and personal protective equipment is improperly applied.
The Equipment detector recognizes equipment of the following colors:
- Helmets:
- Yellow.
- White.
- Blue.
- Green.
- Orange.
- Black.
- Red.
- Vests:
- Yellow.
- Orange.
Attention!
To ensure the correct reception of the E-mail notifications (see E-mail notification) after the detection tool event is generated, you must configure a separate macro with an E-mail message for each item of equipment.
Examples of configuring the Equipment detector for solving typical tasks
Typical tasks for detecting equipment and personal protective equipment:
- Detection in gateway conditions. A gateway is a border, which can either be a virtual line or a door, a barrier, a turnstile. The algorithm for working in gateway conditions is as follows:
- A person stops in front of an area where equipment or PPE is required.
- A person poses in a way that it is possible to check the presence of all elements of equipment (the element must not be overlapped by the person, other elements of equipment, or items of clothing).
- Screening of a person. There must be no obstacles between the person and the camera, blocking the person for screening.
- Detection in a production conditions: persons move freely in the detection area.
Note
By default, the Equipment detector is configured for detection in gateway conditions.
The recommended settings for solving typical tasks are as follows:
| Parameters | Equipment detection in gateway conditions | Equipment detection in production conditions |
|---|---|---|
| Basic | ||
| Number of frames processed per second | 1 | 7 |
| Min person height | 0.01 | 0.09 |
| Min person width | 0.01 | 0.03 |
| Advanced | ||
| Number of measurements in a row to trigger detection | 3 | 7 |
| Mask | No | No |
| One event per PPE element | Yes | Yes |
Overview
Content Tools