PRODIGY_ML_04

Overview

Develop a hand gesture recognition model that can accurately identify and classify different hand gestures from image or video data, enabling intuitive human-computer interaction and gesture-based control systems. All the steps that are required for the experiment such as data preparation, model building, training, evaluation and saving are provided in the IPython notebook: PRODIGY_ML_04.ipynb. The model inference was done on app.py and live_detection.py

How to do inference?

1. Clone this repository.

   git clone https://github.com/surajkarki66/PRODIGY_ML_04

2. Create a Python virtual environment and activate the environment based on your machine(Linux, MacOS, and Windows)

3. Download the trained model from here and put it into the project root directory.

4. Install the requirements

   pip install -r requirements.txt

5. Run the following command To run the normal demo:

   python app.py

   To run the live detection demo:

   python live_detection.py

Demo

Happy coding!