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Home Page

📸 Ga-Reela: Image Retrieval System Program

🌐 Image Retrieval using cosine similarity

🎓 Project Background: I created the CBIR website named "Ga-Reela" as part of my Linear Algebra and Geometry assignment during my third semester in the Computer Science program at ITB.

📝 Description

Content-Based Image Retrieval (CBIR) is a process for searching and retrieving images based on their visual content. This project, developed for the Linear Algebra and Geometry course assignment, starts by extracting essential features from images, such as color, texture, and shape. These features are then represented as vectors or numerical descriptors for comparison with other images. CBIR uses matching algorithms to compare feature vectors, enabling image retrieval within a dataset.

📁 Project Structure

Algeo02-22124
├── back-end
│   ├── app
│   │   └── api.py
│   ├── feature
│   │   ├── color_descriptor.py
│   │   ├── color_runner.py
│   │   ├── color_searcher.py
│   │   ├── database_init.py
│   │   ├── texture_descriptor.py
│   │   ├── texture_runner.py
│   │   └── texture_searcher.py
│   └── main.py
├── src (front-end)
│   ├── assets, components, conf, database, fonts, uploads
│   └── img (aboutus-preview.jpg, cbir-preview.jpg, home-preview.jpg)
├── App.js, index.css, index.js, logo.svg, reportWebVitals, setupTests.js

Configuration Guide

Front-End Setup:

  1. Clone the repository to your local files. Access the repository here.
  2. Open the terminal and ensure that the directory is set to Ga-Reela-Content-Based-Image-Retrieval.
  3. Run npm install to activate the React-JS framework locally.
  4. Execute npm install react-router-dom to enable routing to different paths.

Back-End Configuration:

  1. Run pip install opencv-python for image processing library activation.
  2. Run pip install numpy for mathematical calculations in Python.
  3. Run pip install joblib to facilitate parallel processing.
  4. Run npm install -g concurrently to run both frontend and backend on the same localhost.
  5. Run 'npm install axios' to handle sending and receiving responses.

How to Run

  1. Change the terminal directory to Ga-Reela-Content-Based-Image-Retrieval.
  2. Execute npm start.
  3. Navigate to the CBIR page via the website's Navigation Bar and upload the dataset using the upload dataset button.
  4. Alternatively, use a website to access the dataset with the switch to image scraper button.
  5. Select an image for searching within the dataset by clicking the upload image button.
  6. Choose the real-time camera input option by pressing the switch to camera button.

Screenshots

Home Page

Home Page

About Us

About Us Page

CBIR

CBIR Page