EmotionRecognition is a Python-based deep learning project that aims to recognize facial expressions and classify them into different emotions using Convolutional Neural Networks (CNNs). The project provides an end-to-end solution for emotion recognition from images or real-time video streams.
- Pre-trained CNN models for emotion recognition
- Real-time emotion recognition from webcam or video files
- Image-based emotion recognition
- Easy-to-use API for integrating into other projects
- Modular and extensible architecture
- Supports multiple emotions classification, including but not limited to: happy, sad, angry, surprise, disgust, fear, neutral
To use EmotionRecognition, please follow these steps:
- Clone the repository:
git clone https://github.com/SryNext/EmotionRecognition.git
- Install the required dependencies:
pip install -r requirements.txt
- Download the pre-trained model weights:
Download Model Weights and place it in the models directory.
To recognize emotions from an image, run the following command:
python image_emotion_recognition.py --image_path /path/to/image.jpg
To perform real-time emotion recognition from webcam, run the following command:
python webcam_emotion_recognition.py
To perform real-time emotion recognition from a video file, run the following command:
python video_emotion_recognition.py --video_path /path/to/video.mp4
You can also use the EmotionRecognition API to integrate emotion recognition into your own projects. See api.py for more details.
Contributions to EmotionRecognition are welcome! Please refer to the Contributing Guidelines for more information.
EmotionRecognition is released under the MIT License.