Configuring equipment detection tool (PPE)

To configure the Equipment detection tool (PPE), do the following:

To record mask (body-based segmentation) to the archive (see Extra information overlay (Masks)), select Yes in the corresponding parameter (1).
By default, metadata is not recorded to the database. To enable metadata recording, select Yes in the Record objects tracking parameter (2).
If the camera supports multistreaming, select the stream for which detection is needed (3).

By default, the following neural networks are used according to the selected processing device (9): Classification neural network (head) and Classification neural network (body). To initialize only one item of equipment, select the required classification neural network file (4). There should be a separate classification neural network to recognize equipment on each body segment. The following classification neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:

ppeHelmet(head)General_movidius.ann	Classification neural network (head) / IntelNCS
ppeHelmet(head)General_openvino.ann	Classification neural network (head) / CPU
ppeHelmet(head)General_origin.ann	Classification neural network (head) / GPU
ppeSafetyVest(body)General_movidius.ann	Classification neural network (body) / IntelNCS
ppeSafetyVest(body)General_openvino.ann	Classification neural network (body) / CPU
ppeSafetyVest(body)General_origin.ann	Classification neural network (body) / GPU

If you use a custom neural network, it is necessary to specify the path to the file (3).

Note

To ensure the correct operation of the neural network on Linux OS, the corresponding file should be located in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory.

Select a processing resource for decoding video streams (5). 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 (see General Information on Configuring Detection).
Set the frame rate value for the detection tool to process per second (6). This value should be in the range [0,016; 100].
Attention!
To apply detection in gateway mode (see Examples of configuring Equipment detection tool (PPE) for solving typical tasks), we recommend that you use the detection tool standard settings: 1 fps and 3 frames for output (see i.10).
To apply detection in continuous mode for busy scenes, set the delay to no less than 4 FPS, and the number of frames for output to no less than 6.
Set the minimum height and width of a person (7, 8) in the frame as a percentage of the frame height/width (0,15 = 15%). Objects which are smaller than the specified size will not be detected. The value should be in the range [0; 1].
Select the processor for the neural network − CPU, one of GPUs, or Intel processors (9, see Hardware requirements for neural analytics operation).
Attention!
If you specify other processing resource than the CPU, this device will carry the most of computing load. However, the CPU will also be used to run the detection tool.
If you have Intel HDDL selected, it can process only the segmenting neural networks. The CPU will process the classifying networks.
Attention!
It may take several minutes to launch the algorithm on NVIDIA GPU after you apply the settings. You can use caching to speed up future launches (see Configuring the acceleration of GPU-based neuroanalytics).

By default, the Segmenting neural network (head, body) is used according to the selected processing device (9). The following segmenting neural networks for different processor types are located in the C:\Program Files\Common Files\AxxonSoft\DetectorPack\NeuroSDK directory:

ppeSegmentationByPose_movidius.ann	Segmenting neural network (head, body) / IntelNCS
ppeSegmentationByPose_openvino.ann	Segmenting neural network (head, body) / CPU
ppeSegmentationByPose_origin_onnx.ann	Segmenting neural network (head, body) / GPU

If you use a custom neural network, it is necessary to specify the path to the file (10).

Note

To ensure the correct operation of the neural network in Linux OS, the corresponding file should be located in the /opt/AxxonSoft/DetectorPack/NeuroSDK directory.

Enable the Mask parameter to display body segments in the preview window (11).
Set the minimum number of frames containing people with no PPE for the tool to trigger (12). The value should be in the range [1; 20].
By default, each equipment element triggering occurs once during a continuous tracking of a person. You can set triggering to multiple by setting the One event per PPE element parameter to No (13).
Note
Example. An individual not wearing a helmet appears in the FOV, 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.
In the preview window, you can set the detection zones with the help of anchor points much like privacy masks in Scene Analytics detection tools (see Setting General Zones for Scene analytics detection tools). By default, the entire FOV is a detection area.
Click the Apply button.

The Equipment detection tool (PPE) is now configured.

The Equipment detection tool (PPE) triggers an alarm when a person not wearing required equipment (PPE) on specified body parts, or wearing inappropriate equipment, appears in the FOV.

The Equipment detection tool (PPE) recognizes equipment of the following colors:

Helmets:
1. Yellow.
2. White.
3. Blue.
4. Green.
5. Orange.
6. Black.
7. Red.
Vests:
1. Yellow.
2. Orange.

Attention!

To ensure the correct reception of the E-mail notifications (see E-mail notification) after the Equipment detection tool (PPE) is triggered, it is necessary to set up a separate macro command with an E-mail message for each item of equipment.

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Documentation for Axxon One 1.0.