Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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○Scientific vocabulary similarity
Low similarity (10.9%) to scientific vocabulary
Repository
kuch bho
Basic Info
- Host: GitHub
- Owner: blastre
- Language: Python
- Default Branch: main
- Size: 58.5 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Sign Language Detector
Technologies Used: Python, YOLOv5, OpenCV, Google Colab
Date: August 2024
Overview
This project implements a real-time sign language detection system using a fine-tuned YOLOv5 model. It captures live input from a webcam and recognizes various sign language gestures.
Features
Real-Time Detection:
- Developed a system that uses a fine-tuned YOLOv5 model for accurate gesture recognition.
- Integrated OpenCV for seamless handling of webcam input.
Custom Dataset Builder:
- Built and annotated a custom dataset using a Python script to ensure high-quality data for model training.
- Captured images for specific sign language labels such as 'hello', 'thanks', 'yes', and 'no'.
Installation
- Clone the repository:
```bash git clone https://github.com/blastre/yolo-sign.git cd sign-language-detector Install the required packages:
```bash pip install -r requirements.txt Ensure you have the YOLOv5 weights file (e.g., signlang.pt) in the correct directory.
Usage
To run the sign language detection with webcam input, use the following command:
```bash python detect.py --weights signlang.pt --source 0
Custom Image Dataset Builder
This feature includes a Python script that automatically captures and labels images for building a custom dataset. Images are saved in an organized directory structure, facilitating efficient dataset preparation.
Acknowledgments
Thanks to the developers of YOLOv5 and OpenCV for their contributions to the field of computer vision. Special thanks to any collaborators or mentors who assisted in the development of this project.
Owner
- Login: blastre
- Kind: user
- Repositories: 1
- Profile: https://github.com/blastre
Citation (CITATION.cff)
cff-version: 1.2.0
preferred-citation:
type: software
message: If you use YOLOv5, please cite it as below.
authors:
- family-names: Jocher
given-names: Glenn
orcid: "https://orcid.org/0000-0001-5950-6979"
title: "YOLOv5 by Ultralytics"
version: 7.0
doi: 10.5281/zenodo.3908559
date-released: 2020-5-29
license: AGPL-3.0
url: "https://github.com/ultralytics/yolov5"
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Dependencies
- pytorch/pytorch 2.0.0-cuda11.7-cudnn8-runtime build
- gcr.io/google-appengine/python latest build
- matplotlib >=3.3.0
- numpy >=1.22.2
- opencv-python >=4.6.0
- pandas >=1.1.4
- pillow >=7.1.2
- psutil *
- py-cpuinfo *
- pyyaml >=5.3.1
- requests >=2.23.0
- scipy >=1.4.1
- seaborn >=0.11.0
- thop >=0.1.1
- torch >=1.8.0
- torchvision >=0.9.0
- tqdm >=4.64.0
- ultralytics >=8.1.47
- PyYAML >=5.3.1
- gitpython >=3.1.30
- matplotlib >=3.3
- numpy >=1.23.5
- opencv-python >=4.1.1
- pandas >=1.1.4
- pillow >=10.3.0
- psutil *
- requests >=2.32.0
- scipy >=1.4.1
- seaborn >=0.11.0
- setuptools >=70.0.0
- thop >=0.1.1
- torchvision >=0.9.0
- tqdm >=4.64.0
- Flask ==2.3.2
- gunicorn ==22.0.0
- pip ==23.3
- werkzeug >=3.0.1
- zipp >=3.19.1