medpaf / cbir

Content-based image retrieval system (Intelligent Systems Design course).

CBIR system

Dependecies used in this project are:

• OpenCV
• NumPy
• Imutils

Contents

• Introduction
• Installation
  • Linux
  • Windows
  • macOS
• How to use

Introduction

Content-based image retrieval system developed with Python and OpenCV. An image retrieval system is a computer system for browsing, searching and retrieving images from a large database. The purpose of the database is to store and retrieve an image or image sequences that are relevant to a query. This systems uses the images histogram as descriptor.

Installation

You'll need to install the necessary packages so that the script can run withouth any problems.

Linux

Before installing the dependencies, please make sure you have python3 installed on your machine. But since almost all Linux distros come with Python pre-installed you probably won't need to perform this step. After that, on the Linux terminal, type the following commands as root:

sudo pip3 install opencv-contrib-python
sudo pip3 install numpy
sudo pip3 install imutils

Windows

Since Windows doesn't come with Python pre-installed, you'll need to install Python if you haven't already. It is recommended to install the stable release.

After that, install the following dependecies by typing the following commands on the Command Prompt (CMD):

python -m pip install opencv-contrib-python
python -m pip install numpy
python -m pip install imutils

macOS

macOS comes with Python, but is a deprecated version that is no longer supported. So, you should install a newer version of Python. It is recommended to install the stable release.

Then, type the following command on the terminal to install the necessary packages:

pip install opencv-contrib-python
pip install numpy
pip install imutils

How to use

To use the system to make a search, it's needed to open up the terminal inside the root folder where the code lives. After that, issue one of the following commands depending on the system you're using. For example, on a Linux machines, type:

python3 search.py --index index.csv --query queries/108100.png --result-path dataset

If you're using Windows or macOS, type:

python search.py --index index.csv --query queries/108100.png --result-path dataset

Where index.csv is the index that contains all the features of the images inside the dataset, queries/108100.png is the path of the query image and dataset is the path that contains the photos from the dataset.