/OCR_Inventory_Management

Primary LanguagePython

OCR Inventory Manager

This project demonstrates how to manage inventory and create bills using an OCR-based system integrated with Flask. The app automates the process of reading product details from images, extracting text using OCR, and matching those details against a product inventory stored in an Excel file. Additionally, it can count the number of items present in an image, and for counting particular items, the item_count.py file can be used.

Overview

Manually feeding product details into a system can be time-consuming and error-prone. This project provides an automated solution to manage inventory using OCR (Optical Character Recognition) technology. By uploading product images, the app extracts text data and matches it against a pre-existing inventory, helping businesses generate bills and track inventory automatically. If there are multiple items in a single image, the YOLOv8 model can be used for detection, and the detected parts can be sent for OCR detection for product identification purposes, which can be run using the ocr_with_detection.py file.

Features

  • OCR Integration: Extracts text from product images.
  • Product Matching: Matches OCR output with product inventory using fuzzy matching and FAISS search for fast and accurate results.
  • Multi-Image Upload: Supports uploading multiple images for batch processing.
  • Flask Web Interface: Provides a simple web interface to upload images and view detected products.
  • Item Counting: Counts the number of items present in an image using the item_count.py file.
  • YOLOv8 Detection: Detects multiple items in a single image for accurate OCR processing.

How to Set Up the Application

  1. Clone the Repository:

    git clone https://github.com/Utkarsh-Shivhare/OCR_Inventory_Management.git
cd OCR_INVENTORY_MANAGER

  2. Install Python and Virtual Environment (Optional):

    • On macOS/Linux: 
      python3 -m venv venv
source venv/bin/activate
    • On Windows: 
      python -m venv venv
.\venv\Scripts\activate

  3. Install Dependencies: Install the required Python packages by running:

    pip install -r requirements.txt

  4. Prepare the Inventory: The app requires a product inventory in the form of an Excel file (Product_Inventory.xlsx). Ensure your Excel file has the following structure:

    • Brand: The brand of the product.
    • Product Name: The name of the product.

    You can either use the provided Product_Inventory.xlsx or create your own file with the same format.

  5. Run the Application: Start the Flask server by running:

    python app.py

    The server will start at http://localhost:5000/. Open this link in your browser.

Using the App

  • Upload product images via the web interface.
  • The app will extract text from the images using OCR and attempt to match the extracted text with products in the inventory.
  • You will see the detected products on the result page.