https://github.com/devanshu-17/odin
Attendance Management with Signature Recognition
https://github.com/devanshu-17/odin
cnn-for-visual-recognition machine-learning python signature-verification tensorflow
Last synced: 2 months ago
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Attendance Management with Signature Recognition
- Host: GitHub
- URL: https://github.com/devanshu-17/odin
- Owner: Devanshu-17
- Created: 2023-02-23T19:24:03.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-01-24T17:49:23.000Z (over 2 years ago)
- Last Synced: 2025-05-16T17:44:42.988Z (about 1 year ago)
- Topics: cnn-for-visual-recognition, machine-learning, python, signature-verification, tensorflow
- Language: Python
- Homepage:
- Size: 1.47 MB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Odin: Revolutionising Attendance Management with Signature Recognition
Odin is an attendance management system that utilises signature recognition technology to streamline the attendance taking process. Developed by using a combination of Tensorflow, Keras, Numpy, OpenCV, pandas, and Streamlit, Odin is designed to be efficient, accurate, and user-friendly.
## Key Features:
- Signature recognition technology for attendance management
- Integration with existing databases and systems
- User-friendly interface with real-time feedback
- Customisable settings for enhanced security
- Compatible with a wide range of devices and operating systems
## Usage:
To use Odin, follow these steps:
- Open the Odin application in your browser
- Upload a signature sample for each user in your attendance database
- Select the desired settings for your attendance session
- Begin the attendance session and watch as Odin recognises each user's signature in real-time
## Installation:
To install Odin, follow these steps:
- Clone the repository to your local machine
- Go to the working directory.
```bash
cd Odin/src/
```
- Install the required dependencies using pip
```bash
pip install -r requirements.txt
```
- Run the Odin application using the following command:
```bash
streamlit run Homepage.py
```
## Implementation:
### HOMEPAGE:
### LOGIN PAGE:
### USER PROFILE:
### UPLOAD ATTENDANCE SHEET FOR CROPPING EACH SIGNATURES:
### CROPPED SIGNATURES:
### SAVING CROPPED SIGNATURES:
### PREDICTING SIGNATURES:
### CSV FILES:
### USER DASHBOARD AFTER PREDICTION:
## Contributing:
If you wish to contribute to Odin, please submit a pull request with your proposed changes. We welcome contributions from the community and will do our best to review and incorporate them into the project.
## Authors
- [@Devanshu-17](https://github.com/Devanshu-17)
## License
[](https://opensource.org/licenses/)