This project focuses on developing an online hand gesture recognition system. Utilizing advanced deep learning techniques, it aims to accurately recognize and interpret hand gestures in real-time. The system employs a sophisticated CNN-Transformer architecture to process and analyze video data, making it capable of understanding complex hand gestures.

• Real-Time Gesture Recognition: Detects and interprets hand gestures in real-time.
• Advanced CNN-Transformer Model: Leverages the strengths of both CNNs for spatial feature extraction and Transformers for capturing temporal dynamics.
• Variable-Length Sequence Handling: Accommodates gestures of varying durations with effective padding and masking strategies.
• High Accuracy and Efficiency: Optimized for both high accuracy in gesture recognition and operational efficiency in online settings.

• Python 3.8 or above
• PyTorch
• Torchvision
• CUDA (for GPU acceleration)
• Other dependencies listed in requirements.txt

Clone the repository and install the required dependencies:

git clone https://github.com/KenanKhauto/online-gesture-recognition-project.git
cd online-gesture-recognition-project
pip install -r requirements.txt