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.
- Upload Document 📑: Upload scanned or image-based documents.
- OCR & Extraction 🔎: The document is processed using OCR to extract text.
- Forgery Detection 🕵️♂️: Detect manipulated content using AI.
- Validation ✔️: Check the document against known databases for authenticity.
- 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:
Make sure the backend server is properly configured and running on the appropriate server environment for seamless operation.
python file_name
4. Upload a document 📥: Start uploading documents for validation via the frontend and also from Python_Flask_FastApi.
- Fork the repository 🍴
- Create a new branch 🌱
- Make changes and test 💻
- Submit a pull request 🔄
For queries or issues, reach out at:
📧 [email protected]