♻️ Waste Classification Project

⚙️ Features

• ✨ Automatically classifies images of waste into Degradable 🪴 and Non-Degradable 🧱 categories. -⚡ Fast and accurate predictions using a trained Deep Learning model. -🧠 Includes image preprocessing for improved accuracy. -🔧 Easily extendable to support more waste categories.

🧰Technologies Used

-🐍 Python – programming language for scripts and model implementation.
-🧩 TensorFlow / Keras – building and training the classification model.
-🔢 NumPy & Matplotlib – data handling and visualization.
-💻 Jupyter Notebook / VS Code – for development and testing.

🚀Usage

🪜1. Clone the repository:

git clone https://github.com/dhivya-shreetha-s/Waste_Classification.git

⚙️2. Install dependencies:

pip install -r requirements.txt

🧠3. Run the prediction script:

python predict.py --image path_to_image

✅4. The model will output the waste category of the given image.

📂 File Structure

WASTE_CLASSIFICATION_MAIN/
│
├── waste_dataset/          # Training & validation images
│   ├── train/
│   └── val/
│
├── app.py                  # Streamlit UI
├── image classification.py # Model training script
├── requirements.txt        # Dependencies
├── README.md               # Project documentation
└── .gitignore              # Git ignore rules

📝Notes

🖼️1. Ensure your images are clear for better prediction accuracy.

♻️2. The current model classifies only degradable and non-degradable waste.

🤝3. For updates or contributions, please create a new branch and raise a pull request.

💡This version:

• Fixes all markdown formatting issues.
• Properly closes code blocks.
• Uses consistent headings, numbering, and indentation.🌱