Production Links

• Frontend
• Backend

Table of Contents

• Introduction
• Technologies Used
• Project Structure
• Installation
• Running the Project

Introduction

This project, developed for HEINEKEN Vietnam, aims to automate the analysis of promotional materials in images. The tool can detect brand logos (Heineken, Tiger, Bia Viet, Larue, Bivina, Edelweiss, Strongbow), beer products, consumers, and various promotional items (posters, banners, LED signs). By doing so, it helps reduce time and costs for HEINEKEN Vietnam while ensuring effective brand presence in locations like restaurants, bars, and stores.

Technologies Used

• Backend: Node.js, Express
• Frontend: Next.js, React
• AI Service: Python, PyTorch

Project Structure

root/
│
├── backend/
│ ├── src/
│ │ ├── controllers/
│ │ ├── models/
│ │ ├── routes/
│ │ └── app.js
│ ├── uploads/
│ ├── package.json
│ ├── .gitignore
│ └── .env
│
├── frontend/
│ ├── src/
│ │ ├── app/
│ │ ├── components/
│ │ ├── libs/
│ │ └── utils/
│ ├── public/
│ ├── package.json
│ ├── .gitignore
│ └── .env
│
├── main.py
├── run.py
├── requirements.txt
└── README.md

Installation

Prerequisites

• Node.js and npm (yarn)
• Python 3 and pip

Steps

1. Clone the repository:

   git clone https://github.com/LacTQuan/hackhcm-Rambutan.git
   cd hackhcm-Rambutan

2. Set up the backend:

   cd backend
   yarn
   cp .env.example .env
   # Fill in your environment variables in the .env file

3. Set up the frontend:

   cd ../frontend
   yarn
   cp .env.example .env

4. Set up the AI service:

   pip install -r requirements.txt

Running the Project

Backend

To start the backend server:

cd backend
yarn start

Frontend

To start the frontend server:

cd frontend
yarn start

AI Service

To start the Python service:

python main.py