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Interactive Retrieval System

Introduction

An information retrieval system is built to provide users with the most relevant information in a timely and efficient manner and it consists of many stages: data collection, data preprocessing, indexing, data retrieving, ranking, and presentation. In this report, we use a machine learning-based information retrieval system designed for video event retrieval. The system uses the combination of CNNs, ViT, and CLIP in feature extraction, and the ScaNN method in ranking proved effective in providing accurate and efficient search results.

Enviroment

Ubuntu 18.04.6

Instruction

Step 1 - Data collecting

Open CLI, run

cd backend
python3 datacollecting.py

Step 2 - Installing package and running web system

Excute

pip install -r requirements.txt
uvicorn main:app

Open new CLI (still open the remaining CLI), excute

cd frontend
npm install
npm start

Web system displays on port 4000

Usage

Retrieve Video by Vietnamese description or English description. Detail can be used to view all extracted keyframes with the video. KNN to find the keyframes with the closest distance to the selected keyframe.