content-based-image-retrieval

Welcome to our web application designed to implement a robust Content-Based Image Retrieval (CBIR) system that enables efficient image search and management through visual features and relevance feedback mechanisms. Users can upload, download, delete, and categorize images into predefined classes, as well as generate new images by applying transformations like cropping and scaling. The system computes and displays visual descriptors for images, including color histograms, dominant colors, Gabor texture filters, Hu moments, and additional custom descriptors. It supports both basic search to retrieve visually similar images and an advanced Bayesian relevance feedback mechanism to iteratively refine results, providing an intuitive and dynamic way to explore the RSSCN7 dataset, which consists of 2,800 images categorized into seven scene types such as Residential, Forest, and Industry.

Installation

To start off, clone this branch of the repo into your local:

git clone https://github.com/Samashi47/content-based-image-retrieval.git

cd content-based-image-retrieval

Backend

After cloning the project, if you are using Python 3.12.z with shared libraries enabled, you can checkout to the edge branch, using the latest pymc version:

git checkout edge

If not, you can stay on the main branch.

Then, create a virtual environment:

cd apps/api

Windows

py -3 -m venv .venv

MacOS/Linus

python3 -m venv .venv

Then, activate the env:

Windows

.venv\Scripts\activate

MacOS/Linus

. .venv/bin/activate

You can run the following command to install the dependencies:

pip3 install -r requirements.txt

After installing the dependencies, you should specify the mongodb connection string in the .env file:

touch .env

MONGO_URL=<url>

Then, you can run the following command to start the backend:

python server.py

Frontend

Open another terminal:

cd apps/app

Then, run the following command to install the dependencies:

pnpm install

then, run the following command to start the frontend, if you have angular cli installed globally:

ng serve

if not, you can run the following command:

pnpm run ng serve

Then, open your browser and navigate to http://localhost:4200/ to see the app running.