metadata

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.

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:

pip install streamlit torch torchvision datasets huggingface_hub matplotlib

Spaces:

louiecerv
/

asl_model_uploader

Sleeping

American Sign Language Recognition

Table of Contents

Introduction

Installation