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Object Detection Using YOLO and RTSP Camera on Raspberry Pi 5

OK guys, you spoke, and I listened. You all are asking for a lesson on how to do object detection on a Pi 5 using YOLO and an IP Camera. Well, you are about to get what you asked for. We will make this work, or we will DIE TRYING. Never fear, once you watch the video you will both understand and be able to do it on your own. First, I am assuming you watched our previous lesson where I showed you how to do the basic install and setup of YOLO. If not, never fear, I have the commands below. NOTE: This tutorial is geared towards bookworm OS. I strongly suggest you start with a fresh bookworm SC card, as there are many dependencies, and it is most likely to work if you start exactly where I am starting . . . with a fresh OS. Thes these are the commands I shared last week to get YOLO up and working: (just open a terminal, and paste these commands one at a time)

Now, I will explain this code, and will help you configure it for your cameras, but you will need to open up thonny, and paste in the following code as a start. IMPORTANT, as mentioned above, you need to set interpreter in thonny to the virtual environment set up in the process above. If this is not familiar to you, go back and watch last weeks lesson (click previous at the bottom of this post). Without further adue, here is the code we will work with today:

The video explains everything, please watch it!

 

AI on the Edge: Install and Run YOLO Object Detection on the Raspberry Pi 5

In today’s Lesson we will see just how far we can push things on the Raspberry Pi 5. I will show you how to install YOLO11 on the Pi . I will show you a simple program that will run YOLO11 under Python and openCV. The objective in today’s lesson is to  see if the Pi5, without a Hailo accelerator hat, has sufficient power to do useful object detection. We will not use an accelerator hat, but the work is computationally intensive, so you must use active cooling. This is the low cost cooling fan we are using. It is sufficient to do the job, low cost and is a thin form factor that allows other hats to still fit on the Raspberry Pi 5. You can pick up the fan I am using HERE. Also, we are using an 8GB Pi 5. If you already have a Pi 5, it will probably work. The Pi 5 we are using is available HERE. These appliations are power hungry, so make sure you are using an official Pi Power supply.

In this lesson, I assume you are already familiar with the Pi 5. Note we are using Bookworm OS. Not all the dependencies work yet on Trixie, so I strongly recommend starting by flashing a fresh bookworm SD card.

YOLO11 is a powerful AI object detection model that runs well on the Raspberry Pi 5. The model below:

Now you should be set up to use YOLO11 on the Raspberry Pi 5!

We will start with this program, which is a simple grab a frame and show a frame openCV Program

In the video, we show how to use YOLO11 object detection in this simple program.

 

Arduino IMU Project with Complete Avionics Display for Roll, Pitch and Yaw on a SSD1306 OLED

In this video lesson we wrap up our project to create an Arduino IMU using the GY-87 IMU module, with an MPU6050 chip and a QMC5883L Magnetometer. In this lesson we complete the avionics display, creating an accurate graphical output for Roll, Pitch, and Yaw. This is the schematic we are using for this project:

OLED IMU
This schematic shows how to connect the SSD1306 OLED to our IMU Project.

This is the code we develop in the video. Remember, you have to calibrate your sensors, and put your calibration numbers into the code below. I showed you how to do the calibration in THIS LESSON.

 

Arduino IMU Project with SSD1306 OLED and GY-87 Module with Compass and Roll Avionics Display

OLED IMU
This schematic shows how to connect the SSD1306 OLED to our IMU Project.

For your convenience, this is the code we developed in the video. Remember, you have to edit the program to use the calibration parameters for your IMU module. I showed you how to get those parameters, and calibrate your sensors in THIS LESSON.

 

Arduino Digital Compass With Tilt Compensation and Compass Graphic on SSD1306 OLED

OLED IMU
This schematic shows how to connect the SSD1306 OLED to our IMU Project.

Below for your convenience we include the code developed in this lesson. Remember you must use your own calibration numbers in the code below. I show you how to calibrate your own GY-87 in THIS LESSON.