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YOLO Object Detection on the Raspberry Pi AI HAT | Writing Python Scripts
🔗 *The full guide* : _https://core-electronics.com.au/guides/raspberry-pi/yolo-object-detection-on-the-raspberry-pi-ai-hat-writing-custom-python/_
In this guide, we will be exploring how to set up *YOLO object detection* with the *Raspberry Pi AI HAT*, and more importantly, learning how to apply this in your *Python projects*. We will be taking a look at how to *install* the required *hardware and firmware* as well as how to set up and use the object detection *Python pipelines*. The result of this guide will have you equipped with an understanding of this whole setup, as well as three different *example scripts* we have written. One will "do something" when an object is detected, another when a certain number of objects are detected, and the last when an object is detected in a certain location.
🔧🔨🧰 Hardware featured in this guide:
*13 TOPS AI HAT+:*
_https://core-electronics.com.au/catalog/product/view/sku/CE09993_
*26 TOPS AI HAT+:*
_https://core-electronics.com.au/catalog/product/view/sku/CE09994_
*Raspberry Pi 5:*
_https://core-electronics.com.au/raspberry-pi/boards.html#category_1392_
💡❓ If you have any questions about this content or want to share a project you're working on head over to our *maker forum:* _http://coreelec.io/forum_
0:00 What we will be doing
0:30 What you will need
1:00 Installing the AI HAT
1:54 Installing firmware and Python pipelines
3:37 Looking at the file structure and pipeline
4:49 Running object recognition demo
6:29 Exploring the Python demo script
8:23 Project code 1: detecting objects
13:19 Disabling FPS shell reading
13:58 Project code 2: counting objects
16:03 Project code 3: object position
18:08 Wrap up
🌏🦘 *Core Electronics* is located in the heart of Newcastle, Australia. We're powered by makers, for makers. Drop by if you are looking for:
• *Raspberry Pi* _https://core-electronics.com.au/raspberry-pi.html_
• *Arduino* _https://core-electronics.com.au/arduino.html_
• *Sparkfun* _https://core-electronics.com.au/brands/sparkfun-australia_
• *Adafruit* _https://core-electronics.com.au/brands/adafruit-australia_
• *Pololu* _https://core-electronics.com.au/brands/pololu-australia_
• *DFRobot* _https://core-electronics.com.au/brands/dfrobot-australia_
The following trademarks are owned by *Core Electronics Pty Ltd:*
"Core Electronics" and the Core Electronics logo
"Makerverse" and the Makerverse logo
"PiicoDev" and the PiicoDev logo
"GlowBit" and the GlowBit logo
Видео YOLO Object Detection on the Raspberry Pi AI HAT | Writing Python Scripts канала Core Electronics
In this guide, we will be exploring how to set up *YOLO object detection* with the *Raspberry Pi AI HAT*, and more importantly, learning how to apply this in your *Python projects*. We will be taking a look at how to *install* the required *hardware and firmware* as well as how to set up and use the object detection *Python pipelines*. The result of this guide will have you equipped with an understanding of this whole setup, as well as three different *example scripts* we have written. One will "do something" when an object is detected, another when a certain number of objects are detected, and the last when an object is detected in a certain location.
🔧🔨🧰 Hardware featured in this guide:
*13 TOPS AI HAT+:*
_https://core-electronics.com.au/catalog/product/view/sku/CE09993_
*26 TOPS AI HAT+:*
_https://core-electronics.com.au/catalog/product/view/sku/CE09994_
*Raspberry Pi 5:*
_https://core-electronics.com.au/raspberry-pi/boards.html#category_1392_
💡❓ If you have any questions about this content or want to share a project you're working on head over to our *maker forum:* _http://coreelec.io/forum_
0:00 What we will be doing
0:30 What you will need
1:00 Installing the AI HAT
1:54 Installing firmware and Python pipelines
3:37 Looking at the file structure and pipeline
4:49 Running object recognition demo
6:29 Exploring the Python demo script
8:23 Project code 1: detecting objects
13:19 Disabling FPS shell reading
13:58 Project code 2: counting objects
16:03 Project code 3: object position
18:08 Wrap up
🌏🦘 *Core Electronics* is located in the heart of Newcastle, Australia. We're powered by makers, for makers. Drop by if you are looking for:
• *Raspberry Pi* _https://core-electronics.com.au/raspberry-pi.html_
• *Arduino* _https://core-electronics.com.au/arduino.html_
• *Sparkfun* _https://core-electronics.com.au/brands/sparkfun-australia_
• *Adafruit* _https://core-electronics.com.au/brands/adafruit-australia_
• *Pololu* _https://core-electronics.com.au/brands/pololu-australia_
• *DFRobot* _https://core-electronics.com.au/brands/dfrobot-australia_
The following trademarks are owned by *Core Electronics Pty Ltd:*
"Core Electronics" and the Core Electronics logo
"Makerverse" and the Makerverse logo
"PiicoDev" and the PiicoDev logo
"GlowBit" and the GlowBit logo
Видео YOLO Object Detection on the Raspberry Pi AI HAT | Writing Python Scripts канала Core Electronics
AI HAT Raspberry Pi AI HAT Raspberry Pi AI KIT Raspberry Pi AI HAT tutorial Python Guide Learn How to identify objects raspberry pi object detection object detection raspberry pi YOLOv8 raspberry pi yolo electronics maker education technology opencv YOLO computer vision raspberry pi AI AI machine vision pi camera AI pi 5 Raspberry pi HAILO Yolo11 Raspberry pi AI HAT guide
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29 ноября 2024 г. 10:00:23
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