Integrate Emotion Recognition Feature into Jarvis Assistan

[RumaniSadhukhan170204]

This PR introduces a new Emotion Recognition feature into the Jarvis Assistant project. The integration leverages deep learning techniques to recognize emotions from facial expressions in real-time using a webcam. The following changes were made:

Added Emotion Recognition Logic:

Implemented the emotion recognition pipeline using a pre-trained model (emotion_model.h5) stored in the assets/ folder.
Added facial expression detection functionality using OpenCV and TensorFlow/Keras for real-time emotion classification.
New emotion_recognition.py File:

Contains the core logic for emotion detection, including face detection, preprocessing, and emotion classification.
Streamlit Interface:

Created a streamlit_app.py file to allow users to interact with the emotion recognition system through a simple web interface.
Jarvis Integration:

Integrated the emotion recognition system with the main Jarvis Assistant. The system is triggered after user login, allowing Jarvis to detect emotions using the webcam in real-time.
User Session Management:

Integrated with existing Jarvis user authentication and session management for smooth user experience.

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[Avdhesh-Varshney]

Follow guidelines.

• PR closed due to commit in main branch.
• Integrate your model with Jarvis properly. You have to create a single code file not multiple files.
• For your understanding, review other merged prs of different models.