😄 Mood-Detection

Mood-Detection is a simple image classification web app that detects human emotions from images using a lightweight convolutional neural network.

It uses:

• 🧠 PyTorch and Torchvision for building and loading the model (currently a TinyVGG architecture)
• 🎛️ Streamlit for a clean and interactive web UI

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App Preview

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🧠 Supported Moods

The model currently classifies input images into one of the following moods:

• 😠 Angry
• 😢 Sad
• 😐 Neutral
• 😄 Happy

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🚀 How to Run the App

1. Clone the repository

git clone https://github.com/your-username/Mood-Detection.git
cd Mood-Detection

2. Create and activate virtual environment

python -m virtualenv venv               # For Windows (or)
python3 -m venv venv                    # For macOS/Linux

3. Activate virtual environment

venv\Scripts\activate                   # For Windows
source venv/bin/activate                # For macOS/Linux

4. Install dependencies

pip install -r requirements.txt

5. Run the streamlit app

cd src
streamlit run app.py