implementation ":play-services-vision:12.0.1" To save bandwidth, we trigger face recognition if the “isSmiling” confidence value is above 95%. One of the features is a confidence value of whether the person is smiling. The detector also provides certain features of the detected face(s). The Mobile Vision library has a face detector that we’ll use as a face recognition trigger. If the face is recognized, speak the name of the person.If a face is detected, pass the image to AWS Rekognition.Pass the image to Google’s Mobile Vision library.The top of Wallace is getting a bit crowded with the microphone in the back almost falling off. The speaker (panda) with the USB camera mounted on top. Microphone connected via a 3.5mm on the USB sound card.Panda head speaker connected via a 3.5mm jack on the USB sound card.Raspberry Pi Camera Module V2 (Android Things Dev Preview 6 and beyond).Microsoft LifeCam USB camera (Android Things Dev Preview 5.1).We also discovered that the USB camera would be detected as an audio source/destination by the AudioManager, which would cause the USB sound card to not be detected. This is the setup we would prefer, as we’re using a USB sound card with both a microphone and a speaker. On Dev Preview 6 and beyond, the roles were reversed and we switched to using the Pi Camera. However, we discovered that a USB camera worked perfectly, even though USB cameras were not officially supported. We experienced issues with the Pi Camera Module V2 on that version, where the platform failed to open a stream from the camera. When we started working on adding vision capabilities to Wallace, the latest Android Things version was Dev Preview 5.1. The smart mirror was trained on a set of pictures of all employees, and we decided to use that as our data source. As it turned out, a couple of our colleagues, David Tran and Jonathan Böcker had already built a smart mirror, which was Electron based but utilized Amazon’s object and face recognition service called Amazon Rekognition. One of the goals we had with Wallace was that he should be able to recognize a person’s face and greet by saying the name of that person. In our quest to extend the capabilities of Wallace, we turn our focus to face recognition. You can find the first part of the series here. This blog post is part 2 in our series about Wallace, our four wheeled, Android Things on an RPi3 powered company house robot.
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