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Seekr

1. Aim

A platform that allows users to ask natural language questions about the content of a video and receive accurate, relevant results.

2. Problem Statement

With the increasing popularity of video-based learning, students are using videos more frequently as a primary source of information. However, searching for specific information within a video can be time-consuming and frustrating, as traditional video search methods are often not very efficient.Also, traditional content search methods often rely on manual tagging or transcription, which can be prone to errors.

Thus, there is a need for a more efficient and user-friendly method of searching inside videos using natural language, which can provide accurate and relevant results to the users.

3. Abstract

The solution takes the link of a youtube video / a video file as input which is fed into the webpage which applies Machine Learning Algorithms to get timestamps of the search query provided by the user.

Untitled Diagram

4. Architecture

I - SeekR (Video Frame Based)

Screenshot from 2023-04-09 19 27 53

A - SeekR (Audio Based)

Untitled Diagram drawio

5. Deployment Code:

  In Frontend and Server Folder

  npm install
  npm start

  In Model folder

  flask --app server run

6. Screenshots

Main Page

WhatsApp Image 2023-04-09 at 7 15 52 PM (4)

Problem Statement

WhatsApp Image 2023-04-09 at 7 15 52 PM (3)

Option between I-SeekR and V-SeekR

WhatsApp Image 2023-04-09 at 7 15 52 PM (1)

Video Upload Page

WhatsApp Image 2023-04-09 at 7 18 06 PM

Timestamped Output

WhatsApp Image 2023-04-09 at 7 17 02 PM

History

WhatsApp Image 2023-04-09 at 7 15 52 PM (2)

Highlighted History

WhatsApp Image 2023-04-09 at 7 15 49 PM

Contact Info

WhatsApp Image 2023-04-09 at 7 15 52 PM

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