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YOLOExplorer : Iterate on your YOLO / CV datasets using SQL, Vector semantic search, and more within seconds

Python 85.33% HTML 3.54% JavaScript 2.26% CSS 4.03% TypeScript 4.84%
computer-vision object-detection yolov5 yolov8

yoloexplorer's Issues

Contribution

Hello @AyushExel :wave, I want to contribute to this repo. Is there any contribution guideline or list of todos available?

Thank you.

Roadmap, Scope and API design

Scope

Roadmap to V1:

  • Dataset management - Simple ways to double down on specific parts of the dataset

Searching

  • Using SQL

  • Using Semantic search

  • Support multiple datasets, i.e, allow semantic search across datasets (Via staging area)

  • Using natural Language / AI search - Example- "Show me all images where a person is standing next to a car and the sample should be recorded before 2015"

  • Allow enriching datasets by adding/removing samples from various sources, including other datasets ( secondary datasets of data lakes)

  • Allow Various dataset formats (Users can load datasets from any format including 3rd party sources like RF, DagsHub, etc.)

  • Allow loading tables directly - local, or cloud based ( s3 etc.)

  • Allow various tasks:
  • Detection
  • Segmentation
  • Classification
  • ImgFolder structure used for generative AI or diffusion model samples

API Design:

  • GUI/ Dashboard - TODO
  • Pythonic/ Notebook - TODO

Use recordbatch iterator when creating tables

Currently the table is built using the entire dataset in one go which'll probably fail for massive datasets due to memory constraints. Switch to iterator for initialization of LanceDB tables.

Create Dashboard

Allows users to plot images, analytics and embeddings in interactive browser plots. the current solution (matplotlib) isn't scalable.
The best candidate that I found was plotly dash(https://dash.plotly.com/) but there might be more so open to suggestions.
The idea is avoid building the UI from scratch using js/node as it'll make installation complex and development slow.

How to use own dataset?

Hi there! Thanks for the great work!

If we want to use our own dataset, what should be included in the dataset? I mean, the directory format, labels, etc. Considering we have a dataset of images for a park, should we also have the labels for these images?

Hope this is not a stupid problem : )

Best regards,
Zijia

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