GesturifAI is a computer vision-based gesture recognition and control system that allows users to interact with their devices using hand gestures. The system uses a camera to capture images of the user's hand movements and applies computer vision algorithms to recognize and interpret these movements. This project is designed to be highly efficient and user-friendly for gesture control.
- Contactless control:
GesturifAI allows for contactless control of equipment using hand gestures, which minimizes the risk of infection in public places or shared equipment.
- High accuracy:
With an average detection accuracy of 90%+ at a speed of 0.4 seconds, GesturifAI can detect hand gestures accurately and quickly.
- Customized dataset:
The system uses a customized dataset of over 3300 images for gesture training, ensuring that it is trained on a diverse range of gestures and hand positions.
- Secure access:
GesturifAI only grants access to gesture control to a person who has confirmed their identity using face ID, ensuring that only authorized users can control the equipment.
- Optimized algorithm:
The system has an optimized algorithm that only recognizes the user's right hand and face, ignoring any other body parts or people in the vicinity. This speeds up the program and minimizes the risk of accidental activation.
GesturifAI computer vision models were trained on the basis of a dataset of 3300+ images. Note: We have manually created a high-quality dataset for gesture training.
Link to the dataset: >>>GesturifAI_DataSet<<<
- Python 3.7 or above
- OpenCV (cv2)
- Tensorflow
- Keras
- CVzone
- Automotive Industry:
In-car gesture control is becoming increasingly popular, allowing drivers to use hand gestures to control features such as the radio, air conditioning, and navigation system without taking their hands off the steering wheel.
- Healthcare:
Computer vision gesture control can be used in the healthcare industry for hands-free operation of medical equipment. Surgeons can use hand gestures to control medical devices and perform procedures, reducing the risk of contamination and improving patient safety.
- Retail:
Gesture control can be used in retail stores to create interactive displays that allow customers to browse products and make purchases using hand gestures. This technology can also be used to track customer behavior and provide personalized recommendations.
- Gaming:
Gesture control can be used in gaming to create more immersive and interactive experiences. Players can use hand gestures to control game characters, interact with virtual objects, and perform actions such as shooting or throwing.
- Home Automation:
Gesture control can be used in home automation systems to allow users to control lighting, temperature, and other features using hand gestures. This technology can also be used to create a more personalized and intuitive user experience, making it easier for users to interact with their smart homes.
🧐 Author: Arman Zhalgasbayev - @grembim
📬 Email: [email protected]
📦 Project Link (Github Repository): https://github.com/silvermete0r/GesturifAI