georgia-tech-db / sketchql-demo

SketchQL Demonstration

Description

Sketch-QL is a video database management system for retrieving video moments with a sketch-based query interface.This interface allows users to specify object trajectory events with simple mouse drag-and-drop operations. Using a pre-trained model that encodes trajectory similarity, Sketch-QL achieves zero-shot video moments retrieval by performing similarity searches over the video to identify clips that are the most similar to the visual query.

How to Run

Terminal window 1:

1. cd sketchql-backend

2. Install requirements
   pip install -r requirements.txt

3. Download dataset
   Please download the traffic dataset from https://www.dropbox.com/scl/fi/qormqlzuijb8133um0wa7/VIRAT_S_050300_01_000148_000396.mp4?rlkey=if1vmf14md7nynjuepv9s903j&dl=0 and put it in the data/videos/ folder

4. Download model checkpoint
   Download from https://www.dropbox.com/scl/fi/5jnqj57idzhpm68sjyfb8/model_cp.pt?rlkey=sbz0ix15ofbz0x12d6714v5wu&dl=0 and put it in the data/model_checkpoint folder

5. Run server
   Run the script server.py
   python3 server.py

Terminal window 2:

1. install yarn
   npm install -g yarn

2. install plotly
   pip install plotly

3. Run code
   cd tldraw-v1
   yarn install
   yarn start:core
   open localhost://5422 in your browser

Alternative to Running Code

1. install yarn
   npm install -g yarn

2. Clone tldraw-v1
   https://github.com/tldraw/tldraw-v1.git

3. Replace tldraw-1 core-example-advanced folder with the folder core-example-advanced folder from this github repo

4. Run code on new tldraw-v1 foler
   cd tldraw-v1
   yarn install
   yarn start:core
   open localhost://5422 in your browser

Video

A video demonstrating how SketchQL works can be found in the video folder