Face Expression Detection 🎭

This project uses OpenCV and a Convolutional Neural Network (CNN) model (Keras/TensorFlow) to detect human facial expressions in real-time from a webcam feed.

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🚀 Features

• Detects faces using OpenCV’s Haar cascade classifier.
• Classifies emotions into:
  Angry, Disgust, Fear, Happy, Neutral, Sad, Surprise.
• Real-time webcam detection with bounding boxes and emotion labels.
• Includes test scripts to run predictions on single images.

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📂 Project Structure

face_expression_detection/ ├── main.py # Run real-time webcam emotion detection ├── test_predict.py # Test prediction on a single image ├── diagnose_model.py # Debugging script for model input/output ├── model.h5 # Trained CNN model (≈70 MB) ├── requirements.txt # Python dependencies └── README.md # Project description & instructions

yaml Copy code

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⚙️ Setup Instructions

1. Clone the repository

   git clone https://github.com/wickedos/face_expression_detection.git
   cd face_expression_detection

Create and activate a virtual environment

bash Copy code python -m venv .venv

Windows

.venv\Scripts\activate

macOS/Linux

source .venv/bin/activate Install dependencies

bash Copy code pip install -r requirements.txt Ensure model.h5 is present

If you already have it, place it in the project root.

If not, download it from your own link (e.g., Google Drive) and save it as model.h5.

▶️ Run the Application Webcam real-time detection

bash Copy code python main.py Press q in the video window to quit.

Single image test

bash Copy code python test_predict.py path/to/image.jpg Model diagnostics

bash Copy code python diagnose_model.py 📦 Dependencies TensorFlow / Keras

OpenCV

NumPy

Pillow

(Install automatically via requirements.txt)

🙌 Acknowledgements OpenCV for face detection.

Original dataset and CNN inspiration from FER2013.

Repository structure inspired by akmadan/Emotion_Detection_CNN.

📸 Demo Add screenshots or GIFs of the app in action here if you’d like!

======================= requirements.txt tensorflow opencv-python numpy Pillow

======================= .gitignore Ignore Python virtual environment .venv/ pycache/ *.pyc

Ignore debug and log files , debug_face.jpg , run_output.txt

yaml Copy code

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✅ Next step after creating these three files:

git add README.md requirements.txt .gitignore
git commit -m "Add README, requirements, and gitignore"
git push