Document-AI--OCR---Data-Extraction-

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Document-AI--OCR---Data-Extraction-

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AI-powered OCR and data extraction system for converting unstructured documents into structured data using computer vision and machine learning.

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# DocuScan AI: Automated Document Processing & Data Extraction

![DocuScan AI Banner](https://raw.githubusercontent.com/iamgooold/Document-AI--OCR---Data-Extraction-/main/document_ai_hero_1774713186627.png)

## Overview
**DocuScan AI** is a professional, AI-powered solution for extracting structured data from business documents. Built with modern OCR technologies and a high-end web interface, it allows users to transform scanned invoices, receipts, and forms into clean, actionable digital data (JSON/Excel) in seconds.

## Key Features
-  **AI-Powered OCR**: High-accuracy text extraction using state-of-the-art models (PaddleOCR).
-  **Field Extraction**: Automatically detects Vendor names, Dates, Total Amounts, and Line Items.
-  **Premium UI**: Modern, responsive glassmorphism design that "wows" clients.
-  **Data Export**: Copy extracted data to the clipboard or export for use in accounting software.
-  **Multi-Format Support**: Works seamlessly with JPEG, PNG, and PDF files.
-  **Fast & Lightweight**: Built with FastAPI and Vanilla JS for maximum efficiency.

## Use Cases
- **Accounting Automation**: Reduce manual data entry for bookkeepers.
- **Inventory Tracking**: Digitizing supplier receipts.
- **Expense Management**: Fast extraction for reimbursement workflows.
- **Digital Archives**: Turning physical paper into searchable databases.

---

## Technical Specifications
- **Backend**: FastAPI (Python 3.8+)
- **OCR Engine**: PaddleOCR (High-accuracy Chinese/English/Multi-lang support)
- **Frontend**: Standard HTML5, CSS3, ES6 JavaScript
- **Deployment Ready**: Modular architecture designed for easy Dockerization or Cloud deployment.

---

## Installation & Setup

1. **Clone the Project**:
   ```bash
   git clone [Your-Repo-Link]
   cd "Document AI (OCR + Data Extraction)"
   ```

2. **Setup Virtual Environment**:
   ```bash
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   ```

3. **Install Dependencies**:
   ```bash
   pip install -r requirements.txt
   ```

4. **Launch the Backend**:
   ```bash
   cd backend
   python main.py
   ```

5. **Open the Frontend**:
   Simply open `frontend/index.html` in your browser or serve it via a local web server.

---

## Author
Au Amores

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