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You can configure the The Sweethearting at checkout detection module is configured module on the settings panel of 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 boxwindow.
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Basic settings of the detection tool
To configure the The Sweethearting at checkout detection module is configured as follows module, do the following:
- 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:
Image Added - By default, standard (default) neural networks of hand and goods recognition in the frame are initialized according to the device selected at step 3. If you want to use custom neural networks, click the
Image Added button to the left 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. - From the Device drop-down list, select the device on which the neural network will operate: CPU, one of NVIDIA GPUs, or one of Intel GPUs. Auto (default)—the device is selected automatically: NVIDIA GPU gets the highest priority, followed by Intel GPU, then CPU.
Selecting area of interest
- Click the Settings button. The Detection settings window opens.
Image Added - Go to the Select area tab (1).Click and click the Stop video (2) to capture the video image.
- Click Area of interest (3).
button to pause the playback and capture a video frame.- Click the Area of interest button to specify an area of interest. The button is highlighted in blue color.
Image Added - On the captured frame, use the mouse to set anchor points of the area where objects are detected. The rest of the frame is grayed out. The selected area must meet the requirements described in Camera requirements for the Sweethearting at checkout detection module. If you don't specify the area of interest, the entire frame is analyzedSpecify 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 .
Only - You can add only one area
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can be specified the - you try to add a second area
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is specified then - the first area will be deleted.
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remove a selected the
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next - to the right of the Area of interest button.
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Configuring the detection tool parameters
- Go to the Parameters tab (5) and perform the following actions:
Image Removedof the Detection settings window.
Image Added 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. The default value is 0
- 1.0) parameter (6).65.
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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 - In the Frames processed per second (0.016-100) field (7), set specify the number of frames per second that will be processed by the detection tool . Default processes in the range from 0.016 до 100. The default value is 12.
- Click OK (8)
Click the OK button to save the changes and return to the settings panel of the Sweethearting at checkout detection object.
control settings panel of the Sweethearting at checkout detection |
without without saving the changes, click the Cancel |
.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.ann | Neural network file with the hand recognition in the frame tracking model |
dpe_224_2cl_product_v6_122_5k.ann | Neural network file with the goods recognition in the frame tracking model |
- In the Device drop-down list (4) select the device where the neural network will operate.
- Click the Apply button to save the changesClick the Apply button (5).
The Sweethearting at checkout detection module is now configured.