Microplastic detection

200.00

Total downloads: 17

This product uses yolov8 model to detect and classify microplastics in an image. The code is written in google colab to train the model. The trained model is tested and deployed on a raspberry pi with a microscopic camera. This product also provides the raspberry pi code written in python.

This repository contains:

Google colab code to train a yolov8 model

python code on raspberry pi

dataset containing microplastic images

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Description

Here’s the corrected version of your instructions:


How to Run:

Step 1: Download the provided dataset and upload it to your Google Drive.

Step 2: Download the Colab file and open it in Google Colab.

Step 3: Navigate to the directory where your code is stored by executing:

%cd /content/drive/MyDrive/datasets

Step 4: Run the code.

Step 5: Save the model and send it via Gmail.

Step 6: On the Raspberry Pi, install the Debian Bookworm 64-bit OS.

Raspberry Pi Imager link to download the OS: https://www.raspberrypi.com/software/

Step 7: Set up your Raspberry Pi and install YOLOv8 on it.

YouTube link for reference to set up your Raspberry Pi:

YouTube link for reference to download YOLOv8:

Step 8: Set up a webcam with the Raspberry Pi and test it.

YouTube link for reference to set up the webcam:

Step 9: Download the Python code and run it in Thonny IDE.

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