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To configure Water level detection, do the following:
To record water level detection readings to the archive, set Yes for the Record mask to archive parameter (1).
Analyzed framed are scaled down to a specified resolution (4, 1920 pixels on the longer side). This is how it works:
If the longer side of the source image exceeds the value specified in the Frame size change field, it is divided by two.
If the resulting resolution falls below the specified value, it is used further.
If the resulting resolution still exceeds the specified limit, it is divided by two, etc.
Note
For example, the source image resolution is 2048*1536, and the specified value is set to 1000. In this case, the source resolution will be halved two times (512*384), as after the first division, the number of pixels on the longer side exceeds the limit (1024 > 1000). If detection is performed on a higher resolution stream and detection errors occur, it is recommended to reduce the compression.
If the water in the frame is transparent and the detection tool cannot correctly identify its level, use Neural network (6):
If No is selected, the detection tool will work based on the algorithm without using the neural network on the CPU, ignoring the value specified in the Neural network file field.
If Yes is selected:
If a custom neural network is selected in the Neural network file field that corresponds to the device specified in the Neural network mode field and is a water level neural network, a detection tool with a neural network algorithm based on this network will be created.
Attention!
If the neural network file is not specified correctly, the detection tool will not work. The neural network algorithm will recreate itself every 20 seconds.
Select the neural network file (7). The standard neural networks for different processor types are located in the C:\Program Files\Common Files\Grundig\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.
Note
For correct neural network operation on Linux, place the corresponding file in the /opt/Grundig/DetectorPack/NeuroSDK directory.
Select the processor for the neural network—CPU, one of GPUs, or one of Intel processors (8) (see Hardware requirements for neural analytics operation, General information on configuring detection).
Attention!
Set the measurement scale in the frame.
Attention!
Top and bottom values of the measurement scale should match the actual settings (see step 9).
Note
Water level sensor is shown in the lower left corner. If the sensor is green, the water level is below high and critical marks. If the sensor is orange, the water level is at high mark, but below critical mark. A red sensor means that water level is above critical mark.
Configuring Water level detection tool is complete.
When you have created a detection tool, you can see a sensor on the layout in the video surveillance window.
If the sensor icon is green , the water level is lower than both critical and high marks. If the icon is orange , the water level is above the high mark, but below the critical mark. A red icon means that the water level is above the critical mark.
You can also add a numerical value of the water level to the video surveillance window (see Configuring display of water level detection).