test1 / README.md
supArs's picture
Upload 66 files
4d3c01a verified
|
raw
history blame
3.33 kB
metadata
title: Test1
emoji: 🚀
colorFrom: purple
colorTo: indigo
sdk: docker
pinned: false
license: apache-2.0

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference


Sign Language Image Recognition System + Web App

An image recognition system developed with python and ML libraries to detect sign language gestures. It is connected along with a web application using flask and it was developed for an academic project.
Explore the project »

Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Contributing
  5. Contributors
  6. License
  7. Contact

About The Project

[![Product Name Screen Shot][product-screenshot]]

(back to top)

Built With

  • [Python]
  • [OpenCV]
  • [TensorFlow]
  • [Numpy]
  • [Flask]
  • [HTML]
  • [CSS]
  • [JavaScript]

(back to top)

Getting Started

To get a local copy up and running follow these simple example steps.

Prerequisites

This project is built using Python. You may need to have installed python and pip to install required packages.

Installation

python3 train.py
--bottleneck_dir=logs/bottlenecks
--how_many_training_steps=2000
--model_dir=inception
--summaries_dir=logs/training_summaries/basic
--output_graph=logs/trained_graph.pb
--output_labels=logs/trained_labels.txt
--image_dir=./dataset

5. Run the web application

python3 classify_webcam.py



<p align="right">(<a href="#top">back to top</a>)</p>



<!-- USAGE EXAMPLES -->
## Usage

This project can be used to recognize sign language gestures.

<p align="right">(<a href="#top">back to top</a>)</p>




<!-- CONTRIBUTING -->
## Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request

<p align="right">(<a href="#top">back to top</a>)</p>


<!-- CONTRIBUTORS -->
## Contributors