The UV4L installation instructions for Bullseye have been updated. Please read the additional actions listed at the top of the page that you must take in order to install the software properly.
Tag: UV4L
Object detection with depth estimation
As a good example of edge computing, check out this new tutorial about live object detection with depth estimation thanks to stereo vision with a Raspberry Pi Compute Module.
New AI module for UV4L. An example of real-time video tracking working “out-of-the-box”.
As announced in the previous post, a new raspicam driver that adds some AI to UV4L has been released!
Here is a tutorial about how to quickly configure UV4L to make a robot doing real-time object detection, tracking by controlling pan/tilt servos and streaming over the web with WebRTC at the same time.
Below is another example of live object detection where bounding boxes, labels and confidence scores are overlaid real-time on the high-resolution video (tracking has been disabled in this case).
Playing RetroPie games in the browser
This is a tutorial and below is the demo which shows a new way to play RetroPie games with an headless Raspberry Pi 3B+ and an Android “terminal” in the same LAN: traditionally the Raspberry Pi is directly wired to display, speakers (where the game is rendered ) and a gamepad controller. In this case, however, the Raspberry Pi is not connected to any display (except in the first part of the demo for clarity), speakers and controller. On the contrary, the game is played from within Android Chrome on an smartphone with a gamepad controller connected to the smartphone itself. In other words, the game video and audio are rendered onto the smartphone screen and speakers. The great thing is that no special, third-party application on the smartphone is required other than the stock Chrome browser.
UV4L used in Computer Vision!
webrtcH4cKS has recently posted a very interesting article about a computer vision project that makes use of UV4L for real-time streaming of video and data over WebRTC from a Raspberry Pi Zero connected to a AIY Vision board. The board embeds a Vision Processing Unit (VPU) chip that runs Tensor Flow image processing graphs super efficiently.
The article is divided in two parts: