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Configuring the
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detector
To configure the Equipment detection (PPE)the Equipment detector, do the following:
- Go to
the Detection Tools tab- the Detectors tab.
- Below the required camera, click click Create… → Category: Production Safety → Equipment detection (PPE)detector.
By default, the detection tool detector 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 detector 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 |
detection tool | 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 | detector is enabled by default. To disable |
the detection tool| , select the No value |
| No |
| Name | Equipment |
detection (PPE) detection tool | 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 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 | 1 | Specify the number of frames that the |
detection tool detector will process per second. The value must be in the range [0.016 |
; detection detector in a "gateway" ( |
|
see see Examples of configuring |
|
Equipment detection (PPE) the detector for solving typical tasks), we recommend using the standard settings of the |
|
detection tooldetector: 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. |
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| Type | Equipment |
detection (PPE) detection tool | detector 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.
|
There must be a separate Each classification neural network |
to recognize each the specific body segment. The standard classification 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. |
infoNote | 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
|
|
must be located - locally in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory or in the network folder with the corresponding access rights.
- If you use a standard 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% (see Data collection requirements for neural network training).
|
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| Сlassification network 2 file |
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| Сlassification network 3 file |
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| Сlassification network 4 file |
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| Сlassification network 5 file |
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| 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 on which the detector must detect a violation |
for the detection tool to generate an event. The value must be in the range [1, 20]. | Note |
|---|
| To operate the detection in a "gateway" |
|
(see Examples of configuring Equipment detection (PPE) for solving typical tasks), we recommend using the standard settings of the |
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detection tooldetector: 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. |
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| One event per PPE element | Yes | |
detection tool detector's event is generated once for each element of equipment within a track of a person. If you want the |
detection tool detector to generate an event for each equipment violation, select the No value. | Info |
|---|
| 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. |
infoNote | 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
|
|
must be located - locally in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory or in the network folder with the corresponding access rights.
- If you use a standard 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% (see Data collection requirements for neural network training).
|
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| Track lifespan (starting with Detector Pack 3.14) | Yes | By default, the parameter is disabled. If you want to display the track lifespan for an object in seconds, select the Yes value |
| No |
| Basic settings |
| Min person height | 0.01 | Specify the minimum height and width of a |
person in person in the frame as a percentage of the frame height/width (0.15 = 15%). Objects that are smaller than the specified size |
won be detected. The value must be in the range [0, 1] |
| Min person width | 0.01 |
Neural network mode
| CPU | |
detection tools other - another processing resource than the CPU, this device
|
|
will carry the - carries most of the computing load. However, the CPU
|
|
will be detection tool.If you select Intel HDDL, due to the features of the device, only the segmenting neural network will be processed on it, the CPU will be used to run the classification neural networks.- 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 HDDL (not supported) |
| Intel Multi-GPU |
| Intel GPU 0 |
| Intel GPU 1 |
| Intel GPU 2 |
| Intel GPU 3 |
| Huawei NPU |
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
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OnlySafetyVest
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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 parameters |
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 the Detection Zonea detection area).
| Info |
|---|
|
- 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
 Image Modified button. To cancel the action, click this button again.
|
To save the parameters of the detection tooldetector, click the Apply 
button. To discard cancel the changes, click the the Cancel 
button.
The Equipment detection (PPE) is now configured.
Configuring the Equipment detector is complete. If necessary, you can create and configure the required sub-detectors on the basis of the Equipment detector (see Standard sub-detectors).
The Equipment detectorThe Equipment detection (PPE) 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 detection (PPE)detector recognizes equipment of the following colors:
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| Note |
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To ensure the correct reception of the E-mail Email notifications (see E-mail Email notification) after the detection tool detector's event is generated, you must configure a separate macro with an E-mail Email message for each item of equipment. |
Examples of configuring the Equipment
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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 followsthe following:
- 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.
| Info |
|---|
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By default, the Equipment detection (PPE)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| Other |
| Number of frames processed per second | 1 | 7 |
Basic settings
|
| 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 |
