This is a implementation of Yolov5 model in solving the problem of billing of non-barcoded items

Complete Information (Google slides)

Get this project Up and running

Backend Setup (in the root folder):

pip install -r requirements.txt

Frontend Setup (in Frontend UI /smart_invoicing/):

npm i
npm run build

*npm run build ensures there are no breaking changes

Start the Backend (in the root folder):

flask --app server run

All the logic and code are in the server.py file (detection , API, excel management). One can improve it by making separate files, functions.

Start the Frontend (in Frontend UI /smart_invoicing/):

npm run dev

Object Recognition System Documentation

Overview

The Object Recognition System is designed to detect and manage various fruits and vegetables using a camera interface. The system is trained on a dataset consisting of 20 different fruits and vegetables. For detailed information on the training process, refer to the run/train folder.

Getting Started

1. Initialization
   • Press the "Start" button to initiate the object recognition process.
2. Object Detection
   • Place a vegetable or fruit, such as a tomato, in front of the camera.
   • The system will detect the item, and the interface will update from "No Detection" to "Detected".
3. Item Addition
   • Click the "Detect" button to add the detected item to the item list on the front end.

Workflow

1. Detect Item
   • Bring an item in front of the camera.
   • Confirm the detection as indicated by the interface.
2. Add to List
   • After detection, click "Detect" to add the item to the list.
   • The item will appear in the front-end list, where you can view and manage it.
3. Editing and Adding Items
   • You can manually edit and add other items through the front-end interface as needed.
4. Generating Invoice
   • Once all items are added and confirmed, click the "Pay" button.
   • An invoice will be generated, including a payment address and a QR code for convenience.
5. Printing Invoice
   • To print the invoice, click the "Print Invoice" button.

Additional Information

For a comprehensive understanding of the system's logic and workflow, refer to the Google Slides presentation provided.

Ensure to check the run/train folder for in-depth details on the training data and process.