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You can configure the The Sweethearting at checkout detection module is configured program module on the settings panel of the the Sweethearting at checkout detection object created under object created on the basis of the Camera object on the Hardware tab of the System settings dialog box window.

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Basic settings of the detector

To configure the The Sweethearting at checkout detection module is configured as follows program module, do the following:

1. Go to the settings panel of the Sweethearting at checkout detection module object.Click the Settings button (1).
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   The Detection settings window will open.
   Image RemovedSpecify the area of interest of the detection:
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2. By default, the standard (default) neural networks of hand and goods recognition in the frame are initialized according to the device selected at step 3. You must not select manually the standard neural networks for the different processor types since it is performed automatically. If you want to use custom neural networks, click the Image Added button to the right of the Tracking model (Hand recognition in the frame) and Tracking model (Goods recognition in the frame) fields, and in the standard Windows Explorer window that opens, specify the file of the corresponding neural network.
3. From the Device drop-down list, select the device on which the neural network will operate: CPU, one of the NVIDIA GPUs, or one of the Intel GPUs. Auto (default)—the device is selected automatically: The NVIDIA GPU gets the highest priority, followed by the Intel GPU, then the CPU.
   

   Note
   title Attention!
   We recommend using the GPU. It can take several minutes to launch the algorithm on the NVIDIA GPU after you apply the settings. You can use caching to speed up future launches (see Configuring the speedup of neural analytics launch on GPU).

Selecting area of interest

1. Click the Settings button. The Detection settings window opens.
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2. On the Select area tab, click the Stop video button to pause the playback and capture the frame of the video image.
3. Click the Area of interest button to specify the area of interest. The button is highlighted in blue color.
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4. On the captured video frame, sequentially set the anchor points of the area using the mouse in which objects are detected, and the remaining part of the frame is darkened. This area must meet the requirements described in the Camera requirements for the Sweethearting at checkout detection module section. If you don't specify the area of interest, the entire frame is analyzed
5. Go to the Select area tab (1).
6. Click Stop video (2) to capture the video image.
7. Click Area of interest (3).
Specify the area of interest in the captured video image to be analyzed (4). The selected area must comply with Camera and camera settings requirements for the Sweethearting detection module .


Info
title Note

Only

You can add only one area

can be specified

. If you try to add the second area

is specified

,

then

the first area

will be

is deleted. To

remove a selected

delete an area, click

the Image Removed

the Image Added button

next

to the right of the Area of interest button.

Configuring the detector parameters

1. Go to the Parameters tab (5) and perform the following actions:
   Image Removedof the Detection settings window.
   
   Image Added 

2. In the Detection sensitivity [0.0, 1.0] field, specify

   Specify

   the detection sensitivity in the range from 0.0 to 1.0

   in the Detection sensitivity (0.0 - 1.0) parameter (6)

   . The default value is 0.65.

   Info
   title Note
   The detection sensitivity value is selected experimentally. The lower the sensitivity, the greater the probability of false positives. The higher the sensitivity, the less chance of false alarms, however, some useful tracks

   may

   can be skipped.

3. In the Frames processed per second (second [0.016-, 100)] field (7), set specify the number of frames per second that will be processed by the detection tool. Default the detector processes in the range from 0.016 to 100. The default value is 12.
4. Click OK (8)

   Click the OK button to save the changes and return to the settings panel of the Sweethearting at checkout detection object.

   Info
   title Note
   To return to the

   control

   settings panel of the Sweethearting at checkout detection

    without

   object without saving the changes, click the Cancel button.

   If you use a unique neural network, select a neural network file with the hand recognition in the frame (2) and goods recognition in the frame (3) tracking model. It is not necessary to select standard neural networks in this field, the system will automatically select the required one. Standard neural networks are located in the C:\Program Files (x86)\Intellect\Modules64\caffewrapper\Networks directory:

   dpe_224_2cl_hands_v6_50k.annNeural network file with the hand recognition in the frame tracking modeldpe_224_2cl_product_v6_122_5k.annNeural network file with the goods recognition in the frame tracking model
5. In the Device drop-down list (4) select the device where the neural network will operate.
6. Click the Apply button (5).
7. Click the Apply button to save the changes.

Configuring the Sweethearting at checkout detection module is completeThe Sweethearting at checkout detection module is now configured.