CheckMate-Automated-Cheque-Data-Extractor

📝 Description

CheckMate is a Python-based project designed to simplify the process of cheque data extraction and management. Leveraging advanced AI and robust database integration, it provides an efficient, secure, and user-friendly solution for handling cheque-related tasks.

With its ability to extract critical cheque data, ensure secure user authentication, and centralize management, CheckMate aims to reduce human error and increase productivity in cheque processing.

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🚀 Features

• Cheque Data Extraction: Automatically extract key details such as bank name, IFSC code, cheque number, payee name, date, amount (in words and numbers), and account number from scanned cheque images or PDFs.
• PDF Image Extraction: Handles PDF uploads, extracts images from pages, and processes them for data extraction.
• AI-Powered: Uses Google Gemini AI for precise and automated data extraction.
• Data Management: Save extracted cheque details in MongoDB, download them as CSV, JSON, or PDF files.
• Secure User Authentication: Ensures data privacy using bcrypt for hashing and secure login/signup flows.
• Streamlit UI: A clean and interactive web interface for uploading cheques and viewing extracted data.
• Environment Configurations: Handles sensitive data using .env files.

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🛠️ Technologies Used

• Python: Core programming language.
• Streamlit: For building an interactive and user-friendly UI.
• MongoDB: For centralized data management and storage.
• PyMuPDF: For extracting images from PDF files.
• FPDF: For generating downloadable PDF reports.
• Google Gemini AI: For AI-powered data extraction.
• bcrypt: For secure password management.
• dotenv: For managing environment variables.
• pandas: For tabular data management and visualization.

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⚙️ Installation

Follow these steps to set up and run the project locally:

Step 1: Clone the Repository

git clone https://github.com/GAURAV142004/CheckMate-Cheque-Processor.git cd CheckMate-Cheque-Processor

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Step 2: Set Up a Virtual Environment

python -m venv venv source venv/bin/activate

Step 3: Install Dependencies pip install -r requirements.txt

Step 4: Set Up Environment Variables

• Create a .env file in the root directory.
• Add the required variables: GOOGLE_API_KEY=your-google-api-key SECRET_KEY=your-secret-key MONGO_URI=your-mongo-db-connection-string

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step 5: Run the application python main.py