Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/sour-abh-raj/attendance-monitor-using-flask-and-opencv
AI Attendance Monitor is a cost-efficient AI-powered attendance monitoring system developed using Python Flask. The project utilizes OpenCV-Python, Geocoder, and Geopy libraries to provide a convenient solution for attendance tracking based on face recognition and location verification.
https://github.com/sour-abh-raj/attendance-monitor-using-flask-and-opencv
ai face-recognition flask opencv-python python
Last synced: about 2 months ago
JSON representation
AI Attendance Monitor is a cost-efficient AI-powered attendance monitoring system developed using Python Flask. The project utilizes OpenCV-Python, Geocoder, and Geopy libraries to provide a convenient solution for attendance tracking based on face recognition and location verification.
- Host: GitHub
- URL: https://github.com/sour-abh-raj/attendance-monitor-using-flask-and-opencv
- Owner: Sour-abh-Raj
- License: mit
- Created: 2023-06-07T08:33:00.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-05-13T21:02:11.000Z (8 months ago)
- Last Synced: 2024-05-13T22:24:41.258Z (8 months ago)
- Topics: ai, face-recognition, flask, opencv-python, python
- Language: Python
- Homepage:
- Size: 74.2 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Attendance Monitor using Flask and Opencv
AI Attendance Monitor is a cost-efficient AI-powered attendance monitoring system developed using Python Flask. The project utilizes OpenCV-Python, Geocoder, and Geopy libraries to provide a convenient solution for attendance tracking based on face recognition and location verification.
## Features
- :camera: Face recognition: The system uses face recognition algorithms to compare captured faces with the reference photos in the `attendanceResources` folder. If a match is found, an attendance record is created with a corresponding timestamp.
- :round_pushpin: Geo-tagging: Before running the Flask app, you need to generate a geo tag of your current location using `curr_geo_tag_creator.py`. This geo tag is used by the app to verify if the user is within the specified vicinity of the tagged location (default: 100 meters).
- :moneybag: Cost-efficient: The AI Attendance Monitor eliminates the need for manual attendance tracking and reduces administrative efforts by automating the process using AI technologies.
## Prerequisites
- Python 3.x
- OpenCV-Python library
- Geocoder library
- Geopy library
## Installation
1. Clone the repository:
```bash
git clone https://github.com/your_username/AI-Attendance-Monitor.git
cd AI-Attendance-Monitor
```
2. Install the required dependencies:
```bash
pip install -r requirements.txt
```
## Usage
1. Generate a geo tag of your current location by running:
```bash
python curr_geo_tag_creator.py
```
2. Start the Flask app:
```bash
python app.py
```
3. Access the AI Attendance Monitor web interface by navigating to ` http://localhost:5000 ` in your web browser.
## Customization
- Changing Vicinity Distance: You can modify the vicinity distance in vicinity_checker.py to adjust the range within which a user's location is considered valid.
- Updating Reference Photos: To update the reference photos for face recognition, add the corresponding images to the attendanceResources folder.
## License
This project is licensed under the MIT License.
*Feel free to use and customize this project.*