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visionguard

VisionGuard (real-time object detection and monitoring system)

https://github.com/bishwa-cyber/visionguard

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (5.7%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

VisionGuard (real-time object detection and monitoring system)

Basic Info
  • Host: GitHub
  • Owner: Bishwa-cyber
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 12.3 MB
Statistics
  • Stars: 2
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created about 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme Contributing License Citation

README.dataset.txt 

# Construction Site Safety > raw-images_latestversion
https://universe.roboflow.com/roboflow-universe-projects/construction-site-safety

Provided by a Roboflow user
License: CC BY 4.0

Here are a few use cases for this project:

1. Compliance Monitoring: The Construction Site Safety model can be used by construction site managers, safety officers, or regulatory agencies to monitor and ensure that workers are adhering to safety protocols, such as wearing appropriate personal protective equipment (PPE).

2. Accident Detection and Prevention: The model can be integrated with surveillance or monitoring systems on construction sites to detect potentially hazardous situations, such as a person not wearing a hardhat or safety vest near heavy machinery, allowing for real-time intervention and accident prevention.

3. Construction Site Access Control: The model can be employed at entry and exit points of construction sites to identify and grant access only to authorized personnel wearing the proper safety gear, helping to maintain a safe working environment and prevent unauthorized access.

4. Equipment and Vehicle Tracking: The Construction Site Safety model can be used to automatically track the movement and usage of construction vehicles and machinery within the construction site, enabling better project management, fleet optimization, and maintenance scheduling.

5. Job Site Documentation and Reporting: The model can be employed in generating documentation and reports on the compliance, safety measures, and progress of construction projects. It can automatically label photos taken of the construction site, providing valuable metadata for site inspections, progress tracking, and safety audits.

Owner

  • Name: Bishwa Bhushan Palar
  • Login: Bishwa-cyber
  • Kind: user

Citation (CITATION.cff) 

# This CITATION.cff file was generated with https://bit.ly/cffinit

cff-version: 1.2.0
title: Ultralytics YOLO
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Glenn
    family-names: Jocher
    affiliation: Ultralytics
    orcid: 'https://orcid.org/0000-0001-5950-6979'
  - family-names: Qiu
    given-names: Jing
    affiliation: Ultralytics
    orcid: 'https://orcid.org/0000-0003-3783-7069'
  - given-names: Ayush
    family-names: Chaurasia
    affiliation: Ultralytics
    orcid: 'https://orcid.org/0000-0002-7603-6750'
repository-code: 'https://github.com/ultralytics/ultralytics'
url: 'https://ultralytics.com'
license: AGPL-3.0
version: 8.0.0
date-released: '2023-01-10'

GitHub Events

Total
  • Watch event: 3
  • Member event: 2
  • Push event: 9
  • Fork event: 1
  • Create event: 1
Last Year
  • Watch event: 3
  • Member event: 2
  • Push event: 9
  • Fork event: 1
  • Create event: 1

Dependencies

.github/workflows/python-package-conda.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v3 composite
package-lock.json npm
  • 124 dependencies
package.json npm
  • connect-flash ^0.1.1
  • ejs ^3.1.10
  • ejs-mate ^4.0.0
  • express ^4.21.2
  • express-session ^1.18.1
  • ffmpeg ^0.0.4
  • fluent-ffmpeg ^2.1.3
  • mongoose ^8.11.0
  • passport ^0.7.0
  • passport-local ^1.0.0
  • passport-local-mongoose ^8.0.0
pyproject.toml pypi
  • matplotlib >=3.3.0
  • numpy >=1.23.0,<=2.1.1
  • 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
  • torch >=1.8.0
  • torch >=1.8.0,!=2.4.0; sys_platform == 'win32'
  • torchvision >=0.9.0
  • tqdm >=4.64.0
  • ultralytics-thop >=2.0.0