Open Source 3D-model-datasets 🐶

This repository holds open-source 3D-model-datasets ready to download and be used for ML!

What is DagsHub?

DagsHub is a centralized platform to host and manage machine learning projects including code, data, models, experiments, annotations, model registry, and more! DagsHub does the MLOps heavy lifting for its users. Every repository comes with configured S3 storage, an experiment tracking server, and an annotation workspace - all using popular open-source tools like MLflow, DVC, Git, and Label Studio.

What is Hacktoberfest?

Hacktoberfest is a month-long virtual festival of open source! Participants are giving back to the community by completing pull requests, participating in events, and donating to open-source projects. This project is part of Hacktoberfest 2023, where participants enrich the open-source 3D datasets

Quick Start to Contribution

• Sign-up to Hacktoberfest & DagsHub.
• Join our Hacktoberfest Discord channel.
• Read the contribution guidelines.
• Create a Pull Requests on the 3D Model datasets repository.

What does the DagsHub community contribute?

This year we'd like to focus our contribution on the 3D Models domain. For that, we added 3D data catalog capabilities to DagsHub! You can now upload 3D Models or motion clips to DagsHub and see, move and diff it! You can see a vivid example of this (extremely cool) feature in our HUMAN4D project.

How to contribute?

• Claim the dataset you wish to contribute from the list (KUDOS to Papers With Code) by opening a new issue on the repository and name it after the dataset. Please make sure that the dataset wasn't claimed.
• Open a new DagsHub repository and upload the data to its DagsHub storage (e.g., dataset repository).
• Write information about the dataset in the README file (e.g., HUMAN4D README).
• Add relevant tags to the repository and files.
• Add the following labels to the repository:
  • dataset
  • 3D Model
  • hacktoberfest
• In the GitHub 3D-model-datasets project:
  • Open a new branch named after the dataset.
  • Add a directory named after the dataset with the README file.
  • Commit and push the changes to GitHub.
  • Create a pull request on GitHub.
• Optional: Share the project on DagsHub Hacktoberfest Discord channel.

Reference materials

• DVC Integration
• Hacktoberfest 2022 Discord channel