Conversing with people having a hearing disability is a major challenge. Deaf and Mute people use hand gesture sign language to communicate, hence normal people face problems in recognizing their language by signs made. Hence there is a need for systems that recognize the different signs with accuracy.
The aim of the project is to bridge the gap between the speech and hearing impaired people and the normal people. The basic idea of this project is to make a system using which dumb people can significantly communicate with all other people using their normal gestures. The project uses image processing system to identify sign language shown by the user and generates results in the form of training and test accuracy.
Python libraries used
1) Open-cv : OpenCV is a huge open-source library for computer vision, machine learning, and image processing.
2) Matplotlib : It is an amazing visualization library in Python for 2D plots of arrays.
3) Torch : PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
4) Numpy : NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
- Install onx runtime and open-cv
For installing ONNX runtime :
pip install onnxruntime
For open-cv :
pip install opencv-python
Then run,
python3 camera.py
on any platform
- Python - Language
Python libraries:
