---
title: Asl Model Uploader
emoji: 💻
colorFrom: red
colorTo: pink
sdk: streamlit
sdk_version: 1.42.0
app_file: app.py
pinned: false
license: mit
short_description: App the uploads the ASL Model Trained Using Torch
---

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

# American Sign Language Recognition

This project demonstrates a Convolutional Neural Network (CNN) model for recognizing American Sign Language (ASL) using the Hugging Face Hub and Streamlit for the user interface. The model is trained on a dataset of ASL images and includes data augmentation techniques to improve generalization.

## Table of Contents
- Introduction
- Installation
- Usage
- Model Architecture
- Data Augmentation
- Training
- Results
- Acknowledgements

## Introduction
This project aims to build a robust ASL recognition system using deep learning techniques. The model is implemented in PyTorch and utilizes the Hugging Face Hub for dataset management. The Streamlit app provides an interactive interface for training and visualizing the model's performance.

## Installation
To run this project, you need to have Python installed along with the following libraries:
- `streamlit`
- `torch`
- `torchvision`
- `datasets`
- `huggingface_hub`
- `matplotlib`

You can install the required libraries using:
```bash
pip install streamlit torch torchvision datasets huggingface_hub matplotlib