Raspberry Pi AI Kit | First Project: A Computer Vision Gatekeeper aka Peeper Pam
TLDRThe Raspberry Pi AI Kit, designed for the Raspberry Pi 5, includes a Raspberry Pi M.2 HAT+ and a Hailo 8L AI accelerator. This kit enables the creation of 'Peeper Pam,' a modern twist on the 2002 CHIMP mirror, using computer vision to detect people behind you. The setup includes a server with a camera and a detector with an LED and analog voltmeter, alerting you when a person is detected. The project's code and instructions are available on GitHub.
Takeaways
- 📦 The Raspberry Pi AI Kit includes the Raspberry Pi M.2 HAT+ and a Hailo 8L AI accelerator module, designed for the Raspberry Pi 5.
- 📷 The kit integrates with the Raspberry Pi camera software stack, enhancing its capabilities with computer vision models.
- 👾 The project, named 'Peeper Pam,' is inspired by the CHIMP mirror from ThinkGeek in 2002, updated with AI for modern use.
- 👀 Peeper Pam uses computer vision to detect people behind the desk, alerting the user to potential 'boss' appearances during important calls.
- 🔍 The server component utilizes a Raspberry Pi 5 and the AI Kit to process video feed and detect human presence.
- 🚨 The detector component, built around a Pi Pico W, uses an LED and an analog voltmeter to indicate the presence and certainty of a person.
- 💡 The LED brightness and needle position on the voltmeter represent the model's confidence in detecting a person.
- 🛠️ Assembly requires additional components like a MOSFET, LED, and resistors for controlling the detector's response.
- 🔗 The project's code and instructions are available on GitHub, allowing others to replicate Peeper Pam.
- 🎥 The device serves as a modern, AI-enhanced early warning system to prevent workplace interruptions.
Q & A
What is the new AI kit for Raspberry Pi 5 announced in the script?
-The new AI kit for Raspberry Pi 5 consists of two pieces of hardware: the Raspberry Pi M.2 HAT+ and a Hailo 8L module, which is an AI accelerator. Additionally, the Raspberry Pi camera software stack now has full integration with the Hailo module.
What is the purpose of the Raspberry Pi M.2 HAT+ in the AI kit?
-The Raspberry Pi M.2 HAT+ is a hardware component of the AI kit that is only compatible with the Raspberry Pi 5 and works in conjunction with the Hailo 8L module to provide AI acceleration capabilities.
What does the Hailo 8L module do in the context of the Raspberry Pi AI kit?
-The Hailo 8L module serves as an AI accelerator, enhancing the AI capabilities of the Raspberry Pi 5 by providing additional processing power for AI-related tasks.
What is the name of the device built using the Raspberry Pi AI kit in the script?
-The device built using the Raspberry Pi AI kit is called 'Peeper Pam', which is a modern take on the CHIMP mirror from 2002, designed to alert users when someone is behind them using computer vision.
How does Peeper Pam utilize computer vision to alert users?
-Peeper Pam uses a camera to monitor an area, such as behind a desk, and computer vision models to detect if a person is in the frame. If a person is detected, an alert is triggered.
What is the function of the analogue voltmeter in Peeper Pam?
-The analogue voltmeter in Peeper Pam serves as a visual measure of model certainty, indicating the probability of a person being detected by lighting up an LED and moving a needle closer to 1 as the certainty increases.
What components are needed to build the server part of Peeper Pam?
-To build the server part of Peeper Pam, one needs a Raspberry Pi 5, the new Raspberry Pi AI Kit, a camera, and a mounting device for the camera.
What components are required for the detector part of Peeper Pam?
-The detector part of Peeper Pam requires a Pi Pico W, a MOSFET for controlling the LED brightness and needle movement, an LED, and resistors of 220 ohms and 1000 ohms.
How does the LED and needle in Peeper Pam indicate the detection of a person?
-When a person is detected by the server, the LED lights up and the needle moves closer to 1 on the voltmeter, with the brightness of the LED and the position of the needle indicating the level of certainty of the detection.
Where can one find the code and instructions to build Peeper Pam?
-The code and instructions for building Peeper Pam can be found in the GitHub repository mentioned in the script.
What is the practical use of Peeper Pam in a modern work environment?
-Peeper Pam can be used as an early warning system in a work environment to alert users when someone, such as a boss, is approaching, which can be helpful during important video calls or while focusing on tasks that require privacy or concentration.
Outlines
💻 Introduction to Raspberry Pi 5 AI Kit
The script introduces a new AI kit for the Raspberry Pi 5, which includes a Raspberry Pi M.2 HAT+ and a Hailo 8L module for AI acceleration. The kit is designed to integrate with the Raspberry Pi camera software stack, enabling users to build AI-powered devices. The host shares their experience with the kit and outlines a project to create a modern version of the 'CHIMP mirror' from 2002, a device that alerts users when someone is behind them.
🐒 The Peeper Pam Project
The project, named 'Peeper Pam,' aims to update the concept of the CHIMP mirror by using computer vision to detect people behind the user. The script describes how the Raspberry Pi server uses the camera and computer vision models to spot a person and sends a signal to an alarm system. This system is intended to warn users of approaching individuals, such as a boss, during important meetings.
🔍 Components and Assembly
The script lists the components required for the server and detector parts of the Peeper Pam project. For the server, a Raspberry Pi 5, the AI kit, a camera, and a mounting device are needed. The detector requires a Pi Pico W, a MOSFET for controlling the LED and needle, an LED, and two resistors. The assembly involves connecting these components to create a system that visually indicates the presence of a person through an LED and a dial.
📡 Functionality and Alert System
The script explains the functionality of the Peeper Pam device. When a person is detected by the server's camera, the detector receives an alert. The LED lights up, and the dial moves closer to 1, indicating the probability of a person being detected. The brightness of the LED and the position of the needle on the dial are proportional to the server's certainty about the presence of a person.
🛠️ Building and Accessing the Project
The script concludes by directing viewers to the GitHub repository where they can find all the code and instructions to build their own Peeper Pam. It encourages viewers to utilize the new Raspberry Pi AI kit to create a device that monitors a video feed and alerts them to significant events, such as the presence of a person.
Mindmap
Keywords
💡Raspberry Pi AI Kit
💡Raspberry Pi 5
💡Hailo 8L module
💡Computer Vision
💡Peeper Pam
💡Analogue Voltmeter
💡Server
💡Detector
💡M.2 HAT+
💡Github Repository
Highlights
Raspberry Pi announces a new AI kit for the Raspberry Pi 5.
The AI kit includes the Raspberry Pi M.2 HAT+ and a Hailo 8L module.
The Raspberry Pi camera software stack now integrates the Hailo module.
The project is a modern take on the CHIMP mirror from 2002.
Peeper Pam is a device that uses computer vision to monitor an area behind your desk.
The camera uses computer vision models to detect people in the frame.
An alert is sent to Peeper Pam if a person is detected.
Peeper Pam acts as an early warning system to avoid surprises during important calls.
An analogue voltmeter is used as a visual measure of model certainty.
The server setup includes a Raspberry Pi 5, the AI kit, a camera, and a mounting device.
The detector setup requires a Pi Pico W, a mosfet, an LED, and resistors.
When a person is detected, the LED lights up and the dial indicates the probability.
The LED brightness and needle position correlate with the server's certainty.
The project demonstrates the use of computer vision with the Raspberry Pi AI kit.
All the code and instructions are available on the GitHub repository.
The project is a practical application of AI for monitoring video feeds and alerting users.