Campeone/Facial_Emotion_Detection_CNN

Facial Emotion Detection with Streamlit Web App

Overview

This project implements facial emotion detection using deep learning techniques and provides a user-friendly interface through a Streamlit web application. Users can upload images containing faces, and the application will detect and classify the emotions present in each face.

Features

• —Upload Image: Users can upload images containing faces.
• —Emotion Detection: The application detects facial expressions and classifies them into different emotions such as happy, sad, angry, etc.
• —Display Results: Detected emotions are displayed alongside the uploaded image for user visualization.
• —User-Friendly Interface: The Flask web app provides a simple and intuitive interface for users to interact with.

Technologies Used

• —Python
• —TensorFlow, Keras: Deep learning frameworks for training and deploying the emotion detection model.
• —OpenCV: Image processing library for face detection and manipulation.
• —Streamlit: Web framework for developing the user interface and Frontend design and layout.

Files in Repository

• —app.py: Streamlit application script containing the backend logic for image processing and emotion detection.
• —FacialEmotionNet01.h5: Pre-trained deep learning model for facial emotion detection.
• —README.md: Readme file providing an overview of the project and instructions for replication.

Usage

1. 1.Clone the repository to your local machine.
2. 2.Install the required dependencies using pip install -r requirements.txt.
3. 3.Run the Streamlit application using 'streamlit run app.py`.
4. 4.Access the web application through your browser at http://localhost:5000.
5. 5.Upload an image containing faces and observe the detected emotions.

Example

[image]

Future Enhancements

• —Improve model accuracy and robustness through further training and fine-tuning.
• —Implement real-time video emotion detection for live webcam feeds.
• —Enhance the user interface with additional features such as image cropping and resizing.

Feel free to reach out with any questions or feedback!

Author: [Ojo Timilehin] Contact: [ojotimilehin01@gmail.com]

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference