Sample Software Introduction
最終更新
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2.1.1-English
最終更新
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Face recognition: 1:1 verification, 1:N identification, server identification, QR code identification, temperature measurement + identification
Operate hardware peripherals
Access SenseLink
The running result is shown below:
It includes 1:1 face verification, 1:N face identification, server-side identification, QR code identification, and temperature measurement + identification, as shown below:
The “1:1 Face verification" is a process of proving "you are you", which means that you already have someone's identity information to determine whether the person's face information in the camera view matches the existing identity information.
You need to add a photo of the target person before using it, as shown below:
Then enter the 1:1 matching
The “1:N Face identification” refers to registering the set of face images to be recognized into the local face feature library, and comparing them with the set of face features in the face feature library when the camera acquires the face information to derive the identification result.
Build a facial feature database before using it, as shown below:
Then enter the 1:N identification
Server identification is also a 1:N recognition mode, which only replaces the local execution with the remote execution in the "face comparison" link. Since face features are stored on the server, you do not need to build the face feature library at this point, but just enter it directly, as shown below:
Please note that you, as a user, need to implement your own server comparison logic. Please refer to link-api-dev-manual-en .md for details.
It features parsing of QR code content, placing the QR code in the preview screen to ensure clear imaging of the QR code, and if identification is successful, the QR code content will be displayed on the screen, as shown below:
Through the Face recognition function and temperature measurement module, the face and thermodynamic diagram data are processed by the algorithm to get the final face temperature. Currently, the temperature measurement modules supported are Arrow module, Guide 120 module, and Guide 256 module. It should be noted that the final face temperature value may deviate depending on the ambient temperature, module model, and usage strategy.
The "Temperature Measurement+Identification" is equipped with a 1:N face feature library. So before using it, you need to go to 1:N Face Identification to set the face features, and then enter the "Temperature Measurement + Identification" function after the setting is completed.
It’s compatible with some peripherals of Pass and Thunder series. The peripherals supported are shown in the following figure:
If newDeviceKey is true, it means the current device has not logged into SenseLink. Input the server address, account name, and password, then click login. If the following graph is shown, the login is successful.
Upload the record obtained from face recognition, QR code, and etc. to SenseLink. Upload TSL model to SenseLink. Please check the following graph for detail.
