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https://github.com/tushar2704/fintext-analyzer
https://github.com/tushar2704/fintext-analyzer
streamlit-tushar2704
Last synced: 19 days ago
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- Host: GitHub
- URL: https://github.com/tushar2704/fintext-analyzer
- Owner: tushar2704
- License: mit
- Created: 2023-09-03T15:05:32.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-09-06T16:56:46.000Z (over 1 year ago)
- Last Synced: 2024-05-11T05:53:46.321Z (8 months ago)
- Topics: streamlit-tushar2704
- Homepage: https://tushar-aggarwal.com
- Size: 6.84 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# FinText Analyzer: OCR for Financial Documents -Comin Soon
## Overview
FinText Analyzer is an Optical Character Recognition (OCR) tool designed specifically for financial documents. It allows you to extract text and data from financial statements, invoices, receipts, and other financial documents with ease. This Streamlit web application serves as an interface to interact with the OCR model.
### Features
- Accurate OCR for financial documents.
- User-friendly web interface powered by Streamlit.
- Supports multiple document formats (PDF, scanned images, etc.).
- Extracts key financial data like dates, amounts, and descriptions.
- Export OCR results to various formats (CSV, Excel, etc.).
## Demo
Include a link to a live demo of your application (if available).
## Getting Started
Follow these instructions to set up and run the FinText Analyzer locally:
### Prerequisites
- Python 3.x
- Dependencies listed in `requirements.txt`
### Installation
1. Clone this repository:
```shell
git clone https://github.com/your-username/fintext-analyzer.git
```
2. Navigate to the project directory:
```shell
cd fintext-analyzer
```
3. Install the required dependencies:
```shell
pip install -r requirements.txt
```
### Usage
1. Start the Streamlit web application:
```shell
streamlit run app.py
```
2. Open your web browser and navigate to the URL provided by Streamlit.
3. Upload your financial documents and let FinText Analyzer perform OCR.
### Customization
You can customize the application by modifying the `config.yaml` file to change settings such as OCR model, language, and output format.
## Contributing
We welcome contributions from the community! If you'd like to contribute to the project, please follow our [Contribution Guidelines](CONTRIBUTING.md).
## License
This project is licensed under the [MIT License](LICENSE.md).
## Acknowledgments
- Thanks to the open-source OCR community for their valuable contributions.
- Inspired by [List of contributors or resources you used as inspiration].
## Contact
If you have any questions or suggestions, feel free to reach out to us at [[email protected]].
---
Customize this README.md file to include specific details about your project, such as the installation process, usage instructions, customization options, and any other relevant information. Additionally, make sure to include your logo, licensing information, and contact details.