Our IDP solution helps to validate and process documents (scanned, soft copies, or images) efficiently, detecting forgeries and validating sensitive information. This system offers real-time document validation, OCR, and advanced forgery detection using python technologies.

• Document Validation ✅: Identify if a document is valid or forged.
• OCR (Optical Character Recognition) 🧠: Extract text from images or scanned documents.
• Forgery Detection 🔒: Detect manipulated photos (e.g., fake Aadhar cards).
• Text Extraction 📝: Extract relevant data from structured and unstructured documents.
• Real-Time Processing ⚡: Validate documents instantly.
• Highlight Suspicious Areas 🚨: Identify and highlight forged areas (e.g., modified names).
• Cross-Referencing 🔄: Automatically verify details with external databases (e.g., government APIs).

• MERN Stack: MongoDB, Express.js, React, Node.js

• FastAPI: Fast and efficient API for communication with the frontend.
• Python: Core language for document processing models and libraries.

• OCR: pytesseract, pdfplumber, PyPDF2, python-docx
• Forgery Detection: opencv-python, scikit-image, torch, torchvision
• NLP Models: transformers, huggingface-hub, BERT, GPT-3, tokenizers
• PDF Parsing & Text Extraction: pdfminer.six, PyPDF2, pandas, pdfplumber
• Image Processing: opencv-python, Pillow, scikit-image, tifffile

• Cloud-Based Processing ☁️: Utilize AWS for scalable document processing.
• Distributed Computing 🖥️: Parallel document processing for large batches.
• API Integration 🔌: RESTful APIs for seamless integration with existing systems.
• Automated Pipelines 🔄: Efficient and automated processing pipelines.

1. Upload Document 📑: Upload scanned or image-based documents.
2. OCR & Extraction 🔎: The document is processed using OCR to extract text.
3. Forgery Detection 🕵️‍♂️: Detect manipulated content using AI.
4. Validation ✔️: Check the document against known databases for authenticity.
5. Results 📊: View processed results with highlighted forged sections.

git clone https://github.com/YashChavanWeb/Intelligent_Document_Processing.git
cd Intelligent_Document_Processing

• Frontend: npm install
• Backend: npm install
• Python_Flask_FastApi: pip install -r requirements.txt

• Frontend: npm run dev
• Backend: npm run dev
• Python (Flask/FastAPI): Since this is a monolithic architecture, you need to run the Python backend server (Flask or FastAPI) directly on the server in use. Use the following command to run the server:

  python file_name

  Make sure the backend server is properly configured and running on the appropriate server environment for seamless operation.

1. Fork the repository 🍴
2. Create a new branch 🌱
3. Make changes and test 💻
4. Submit a pull request 🔄

For queries or issues, reach out at:
📧 chikkakrisha@gmail.com