MicroSense: The Micro Expression Detector is a deep learning-based project designed to detect micro-expressions in video uploads. Micro-expressions are brief, involuntary facial expressions that reveal true emotions. This tool can be used for various applications, including psychological studies, security, and improving human-computer interaction.
- Detects micro-expressions in uploaded videos.
- Trained using the YOLO object detection algorithm.
- Model trained on over 10,000 examples and more than 10 different micro-expressions.
- High accuracy in detecting subtle facial expressions.
- User-friendly interface for video upload and analysis.
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Clone the repository
git clone https://github.com/yogeshsumman/Micro-Expression-Detector.git
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Make sure you have python 3.11 and pip installed in your machine.
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Install the required dependencies using pip:
pip install -r requirements.txt
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Run the flask application:
python app.py
- Real-time Processing: Explore the implementation of real-time micro-expression detection from video streams to enhance usability in live scenarios.
- Cross-Dataset Evaluation: Validate the model's performance across different datasets to ensure robustness and generalizability.
- Multi-Modal Analysis: Integrate additional data modalities, such as audio or text, to provide a more comprehensive analysis of micro-expressions in context.
- User Customization: Allow users to customize detection thresholds and settings based on specific use cases or environments.
- Mobile Deployment: Investigate options for deploying the model on mobile devices to make micro-expression detection accessible on-the-go.
These enhancements aim to improve the utility, accessibility, and accuracy of the MicroSense project, making it a valuable resource for various fields.
If you have any questions or need further assistance, please contact our support team at yogeshsumman2001@gmail.com.
Client: HTML, CSS, JavaScript
Server: Flask, Sqlalchemy, Python
Object Detection: YOLO