Connect the other leg, via a resistor, to a GPIO GND pin.

Green LED : Connect the positive leg to GPIO pin 22.

Blue LED : Connect the positive leg to GPIO pin 27.

Yellow LED :Connect the positive (longer) leg to GPIO pin 17.

Connect the other, via a resistor, to a GPIO GND pin.

Pushbutton : Connect one leg of the pushbutton to GPIO pin 2.

Follow the wiring diagram to connect the pushbutton and LEDs to the Pi GPIO pins.

Need more help? Connect with the Lobe Coommunity on Reddit!Ģ.

Need more photos? Check out open-source datasets on Kaggle, including this garbage classification image set!.

This will greatly improve the accuracy of your model!

If possible, take photos from the Pi Camera and import into Lobe.

your hands and arms, the background, etc.)

Include a category for 'not trash' that has photos of whatever else might be in the photo (e.g.

'garbage, ' 'recycle, ' 'compost, ' etc.)Note: Use the same labels as shown in 'Lobe Model Labels' photo above to reduce the amount of code you need to change.

Before importing photos, make a list of all the categories you'll need and how you want to label them (e.g.

Note: Use the same labels as shown in 'Lobe Model Labels' photo above to reduce the amount of code you need to change.'garbage, ' 'recycle, ' 'compost, ' etc.) Introduction to Python with the Raspberry Piīefore importing photos, make a list of all the categories you'll need and how you want to label them (e.g.Also helpful: Getting started with the Pi cameraĢ.Reading and editing Python code (you won't need to write a program from scratch, just edit).It also helps to have some knowledge of the following: Here's a beginner-friendly guide on how to do this. This project assumes you're starting with a fully set-up Raspberry Pi in a headless configuration. This tutorial walks you how to create your own Trash Classifier project on a Raspberry Pi from a Lobe TensorFlow model in Python3.ĭifficulty : Beginner++ (some knowledge w/ circuits and coding is helpful) The model is then loaded onto a Raspberry Pi 4 computer to make it usable wherever you might find rubbish bins! This project uses a Machine Learning (ML) model trained in Lobe, a beginner-friendly (no code!) ML model builder, to identify whether an object goes in the garbage, recycling, compost, or hazardous waste.

The Trash Classifier project, affectionately known as 'Where does it go?!', is designed to make throwing things away faster and more reliable.

How to use cyberduck raspberry pi