This project provides an application for recognizing facial emotions in images using a pre-trained deep-learning model. The application allows users to upload images, processes the images to detect faces, and then classifies the emotion displayed on each detected face.

• Detects faces in images.
• Classifies emotions displayed on detected faces.
• Uses a pre-trained deep learning model for emotion recognition.
• Simple web interface built with Streamlit.
• Supports various image file formats.

1. Clone the repository:

   git clone https://github.com/gauravyadav016-png/Facial-Emotion-Recogination.git
   cd Facial-Emotion-Recogination
   
   

2. Install the required dependencies:

   pip install -r requirements.txt

1. Run the application:

   py run main.py

2. Allow the system to camera permission.

3. The application will detect faces and classify the emotions displayed on the detected faces.

• main.py: The main application file that sets up the interface and handles file uploads and image processing.
• emotion-detection.ipynb: Jupyter notebook containing the logic for emotion detection using a deep learning model.
• model.h5: The pre-trained deep learning model used for emotion recognition.

• numpy: For numerical operations.
• opencv-python: For image processing and face detection.
• tensorflow or keras: For loading and using the pre-trained deep learning model.

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

This project is licensed under the MIT License. See the LICENSE file for more details.