😃 Facial Emotion Detection using Deep Learning and OpenCV This project is a real-time facial emotion recognition system that uses a trained deep learning model (CNN) to detect and classify human emotions from webcam video feed. It identifies emotions such as Happy, Sad, Angry, Fear, Surprise, Disgust, and Neutral using OpenCV and Keras.
🧠 Internship Experience Summary This project was part of a hands-on internship where I learned and implemented:
🔹 AI & ML Basics – Algorithms, model training & evaluation
🔹 AI + Cloud Integration – Leveraged Azure AI Services
🔹 Generative AI – Explored Microsoft Copilot, NLP, and Computer Vision tools
🔹 AI for Sustainability – Applied AI for real-world impact and leadership development
🛠 Technologies Used Python OpenCV Keras / TensorFlow NumPy Haar Cascades
🔍 Features Real-time emotion detection from webcam
Deep learning-based facial expression recognition
Uses Haar Cascade for face detection
Pre-trained Keras model (.json + .h5)
Labels emotions on faces in live video stream
face-emotion-detection/ │ ├── emotiondetector.json # Model architecture ├── emotiondetector.h5 # Model weights ├── emotion_detection.py # Main Python script └── README.md # Project documentation
pip install opencv-python keras numpy 🧠 Emotions Recognized 😠 Angry
🤢 Disgust
😨 Fear
😀 Happy
😐 Neutral
😢 Sad
😲 Surprise
📌 Notes The face detection is handled by OpenCV's Haar cascade classifier.
The model is trained on grayscale 48x48 facial expression images.
Model files are not included due to size — you can train your own or contact me for the files([email protected]).
This project was completed as part of a 4-week internship under the "Foundations of Artificial Intelligence" program organized by Edunet Foundation in collaboration with AICTE and Microsoft.
🔗 Download Internship Offer Letter (PDF)
- Learned AI, ML, and DL concepts
- Worked with Azure AI & Microsoft Copilot
- Completed hands-on projects with real-world problem solving
- Attended mentor-led sessions and masterclasses
🙋♂️ Author Shubham B.Tech CSE (AI & ML) 📜 License This project is open-source and available under the MIT License.