In todays news, we are going to be talking about the ,insane update from Neuralink — With a ,monkey that can play pong with his mind, that’s right a monkey, Apples ,3D Voxel for Autonomous Driving, State of the art Multi-object tracking, Protein GANs, and a computer vision bot for ,grocery inventory management. So lets get into it. So AI-CV news is a brand new segment here on Augmented Startups to keep you guys updated with the ,latest in AI and Computer Vision. I’d really appreciate if you guys could comment down below if you’d like more of this…
I am going to show you multiple ways to train models to detect Bernie Sanders on both static images as well as in real time.
We will be demonstrating the building, annotating, and augmenting the dataset, then I we will use Google Colab to initiate the training of YOLOv4/YOLOv5.
Finally if you stay till the end of the video, I will show you how to also run your model on Android ;)
What you’ll need, you’ll only need YOLO v4 or v5:
Today we are going to build our own real-time Social Distancing Monitoring Alarm using a Raspberry Pi and the OpenCV AI kit with Depth Capability. This Raspberry Pi social distance camera will be able detect a people using either a MobileNet SSD or YOLOv3 tiny model at 30 FPS to sound an Alert, to politely remind people to maintain their social distance.
Our Requirements are:
Today we are going to build our own Real-Time AI Surveillance Camera using a Raspberry Pi!
The Problem that we are trying to solve is, that there are not many real time Raspberry Pi CCTV camera solutions online and if they are real-time, then the processing is not an embedded solution, its done on a server, PC or cloud . Another option is to use something like a Neural Compute Stick or Google Coral, which is great but their form factors are slightly bulky especially when we are trying to minimize our security camera size.
Instead we are going…
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So Im going to show you how you can build your own Real-time Mask Detector Access controller using a Raspberry Pi, OpenCV AI Kit camera connected to Stepper Motor. So if the mask is on it will grant access otherwise it will close and stay closed if the if a person takes off their masks. Simple!
You will need the following:
Today we are going to build our own real-time AI surveillance camera using a Raspberry Pi and the OpenCV AI kit. This Raspberry Pi CCTV camera will be able detect a person using a MobileNet SSD at an astonishing 30 FPS as well as sound an Alarm to stop any impending theft.
The Problem that we are trying to solve is, that there are not much real time raspberry pi CCTV camera solutions online and if they are real-time, then the processing is not an embedded solution, its done on a server, PC or cloud.
Okay right here right now I am going to show you how you can build your own Facial Recognition Attendance GUI using PyQt.
The reason for building a GUI is obvious, if you want to roll your application, for example, it needs to be presented well and therefore you will need a user interface or UI. So this video is actually Part 2 of 2 of the facial recognition attendance project as Augmented startups have collaborated with the channel Murtaza’s Workshop.
So Murtaza has part 1 which will show you how build your own facial recognition attendance system and…
python3 -m pip install -U pip
python3 -m pip install -r requirements.txt
3. To install OpenCV manually follow instructions here https://www.raspberrypi.org/forums/viewtopic.php?t=232294 or execute the following commands.
sudo pip3 install opencv-python
sudo apt-get install libcblas-dev
sudo apt-get install libhdf5-dev
sudo apt-get install libhdf5-serial-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install libjasper-dev
sudo apt-get install libqtgui4
sudo apt-get install libqt4-test
4. Connect your device and try
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