This project provides tools to detect and analyze facial emotions in images and videos using the DeepFace library with MTCNN for face detection. It supports batch processing of images and efficient video analysis by skipping frames, enabling faster processing while maintaining smooth emotion transitions. The results are visualized with bounding boxes and emotion labels overlaid on the media.
- Face detection using MTCNN backend for accuracy
- Emotion recognition with dominant emotion and optional full emotion breakdown
- Batch processing of multiple images
- Video processing with adjustable frame skipping for performance