Garbage-Classification

This project is focused on classifying garbage into different categories using a YOLOv8 model. The dataset used for training, validation, and testing is provided by Roboflow.

Dataset

The dataset is organized into three main folders: train, val, and test, each containing subfolders for different classes of garbage:

• cardboard
• glass
• metal
• paper
• plastic
• trash

The dataset configuration is specified in dataset/data.yaml.

Model

The project uses the YOLOv8 model for classification. Pretrained weights are fine-tuned on the provided dataset.

Files

• yolov8_fine_tuning.py: Script to fine-tune the YOLOv8 model on the dataset.
• Models/: Directory containing the best models after training.
• dataset/: Directory containing the dataset and related files.
  • data.yaml: Configuration file for the dataset.
  • README.dataset.txt: Information about the dataset.
  • README.roboflow.txt: Information about the dataset export from Roboflow.
• .gitignore: Specifies files and directories to be ignored by git.
• LICENSE: MIT License for the project.

Usage

To fine-tune the YOLOv8 model on the dataset, run the following command:

python yolov8_fine_tuning.py