LogoGuard: Deep Learning for Fake Logo Recognition

Welcome to the LogoGuard repository! LogoGuard is a deep learning project designed to detect fake or counterfeit logos in images. This tool is valuable in various applications, including brand protection, counterfeit detection, and image forensics.

Table of Contents

• Introduction
• Getting Started
  • Prerequisites
  • Installation
• Usage
• Dataset
• Model
• Training
• Inference
• Results
• Contributing
• License
• Acknowledgments

Introduction

Counterfeit logos can harm businesses and consumers. LogoGuard employs deep learning techniques to automatically identify counterfeit logos in images. This repository contains code and resources for building, training, and using the LogoGuard model.

Getting Started

Prerequisites

• Python 3.6+
• PyTorch
• OpenCV
• NumPy

Installation

1. Clone this repository:

   git clone https://github.com/ADE-17/LogoGuard--Deep-Learning-for-Fake-Logo-Recognition.git