THE LITTER COACH

The Litter Coach is an AI-powered project utilizing YOLOv8 object detection

to clarify the type of litter, as biodegradable and non-biodegradable to promote environmental cleanliness and aid waste management.

Key Features

**AI-Powered Object Detection:** Utilizes machine learning to accurately identify various types of litter.
**YOLOv8 Model Integration:** Employs the high-performance YOLOv8 architecture for efficient and robust detection.
**Real-time Webcam Inference:** Capable of live object detection directly from a webcam feed.
**Litter Type Classification:** Identifies specific items like plastic bottles, banana peels, soda cans, and notebooks.
**Biodegradability Classification:** Categorizes detected litter as either "Biodegradable" or "Non-Biodegradable" based on its type.
**Environmental Contribution:** Aims to promote cleanliness, assist in waste segregation, and raise awareness about proper waste disposal.

**Python:** The primary programming language.
**YOLOv8 (You Only Look Once v8):** The cutting-edge machine learning model architecture for real-time object detection.
**Ultralytics Library:** The official Python library that provides the implementation and tools for using YOLOv8.
**OpenCV (cv2):** Used for handling webcam input, displaying the live video feed, drawing bounding boxes, and other image processing tasks.
**Git & GitHub:** For version control and hosting the project's codebase.

View on GitHub

To set up and run The Litter Coach project on your local machine, follow these steps:

Clone the repository:

git clone https://github.com/garimaa001/The-Litter-Coach.git

Navigate to the project directory:
```
cd The-Litter-Coach
```
Python Environment and Dependencies Setup:
- Create a Virtual Environment (Recommended):
```
python -m venv venv
```
- Activate the Virtual Environment:
  - On Windows (PowerShell/CMD):
```
.\venv\Scripts\activate
```
  - On macOS/Linux:
```
source venv/bin/activate
```
- Install Required Python Packages:
  Ensure you have a requirements.txt file in your project root.
  
  If not, you might need to create it (e.g., by running pip freeze > requirements.txt or manually list them).
```
pip install -r requirements.txt
```
  Alternatively, if you prefer to install directly (without a requirements.txt):
```
pip install ultralytics opencv-python
```
Model Weights Setup:
Ensure your trained YOLOv8 model weights (best.pt)
```
runs/detect/litter_coach_detection_v13/weights/best.pt
```
If your model is elsewhere, update the model_path variable in webcam_predict.py accordingly.
Run Real-time Litter Detection:
With your virtual environment activated, execute the main script:
```
python webcam_predict.py
```
Press q to quit the webcam feed.