This Emotion Recognition App uses TensorFlow and OpenCV to detect and classify human emotions in real-time. The model identifies various facial expressions and maps them to different emotions such as happiness, sadness, anger, surprise, etc.
- Real-time Emotion Detection: Uses OpenCV to capture video input from a webcam and process it in real-time.
- Emotion Classification: Built using a deep learning model trained on facial expression data, leveraging TensorFlow for training and inference.
- GUI Integration: Simple interface to view emotion predictions directly from live video input.
- TensorFlow: For training the neural network model that classifies emotions.
- OpenCV: For capturing and preprocessing the video feed.
- Python: The core programming language used for developing the app.
- Keras: A high-level API for building and training the neural network.
- Clone the repository:
git clone https://github.com/Akshatbigman/Emotion-recognition.git cd Emotion-recognition