https://github.com/adithya-s-k/advance-attendance-system
Attendance tracking is a very tedious process so we came up with a solution which will allow teachers to take attendance in a fast and easy manner
https://github.com/adithya-s-k/advance-attendance-system
algorithms face-detection face-recognition machine-learning python
Last synced: 2 months ago
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Attendance tracking is a very tedious process so we came up with a solution which will allow teachers to take attendance in a fast and easy manner
- Host: GitHub
- URL: https://github.com/adithya-s-k/advance-attendance-system
- Owner: adithya-s-k
- Created: 2022-04-09T05:24:39.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-05-20T18:15:42.000Z (over 3 years ago)
- Last Synced: 2025-04-08T17:31:12.221Z (6 months ago)
- Topics: algorithms, face-detection, face-recognition, machine-learning, python
- Language: Python
- Homepage:
- Size: 15.7 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Advanced Attendance Tracking for Smart Class Rooms
Current methods of taking Attendance in schools and colleges are inefficient and time consuming.
We have come up with a solution which uses facial detection and recognition in order to give Attendance to the student or employee
We built this project for DotSlash 3.0 Hackathon, [PES University](https://pes.edu)
## Installation
Download the zip file or clone the reposiotry
```bash
git clone https://github.com/adithya-s-k/Advance-Attendance-System.git
```
Go to the repository where you have cloned and run app.py
```bash
python app.py
```
## How it works
The project is built using Python and Flask.
We are using a [face_recognition](https://face-recognition.readthedocs.io/en/latest/readme.html) library to detect faces and compare faces.
The teacher will have to take a photo of the class and upload it to the website at the beginning of the class.She should take the photo in such a
way that everyones face is properly visible.
We now will use facial detection to detect the faces and put a box around them as shown below.
After the teacher verifies that everyone's face is visible she will upload the photos on the website.
In the backend each isolated face is stored and compared with a pre-existing data base of student faces.
Here we will be using the face comparison feature and we will be giving attendance to all the students whose faces match.
We will show the absentees list to the teacher where she can call out and verify.
After the face matches the matched face will be added to the database for future comparison and thus the accuracy of the model will keep on increasing.
Here is the [flow chart](https://www.figma.com/file/ssy2MQrWiOkHtrcbPdV7mg/Attendace-Tracking-workflow?node-id=0%3A1)
Here is the [Project Video](https://youtu.be/mRgZdZOKjTk)
## Advantage over existing solutions.
- Quicker and Faster.
- Less error prone.
- No need for external hardware like a camera display.
- The student will have to be physically present in the class in order to get attendance. Faking attendance will become difficult.
- The accuracy increases day by day.
## Tech Stack
**Client:** HTML ,CSS ,Bootstrap
**Server:** Flask(Python)
## Authors
- [@adithya-s-k](https://github.com/adithya-s-k)
- [@senju-hashirama](https://github.com/senju-hashirama)
- [@aaryanhb](https://github.com/aaryanhb)
## 🔗 Links
[]()
[](https://www.linkedin.com/in/adithya-s-kolavi-127a561a8/)
[](https://twitter.com/adithya_s_k)
## Contributing
Contributions are always welcome!
You can fork the repository and create a pullrequest for contributing.
Please adhere to this project's `code of conduct`.