https://github.com/olitheolix/ds2data

Space Sim Inspired Data Set for Machine Learning Purposes
https://github.com/olitheolix/ds2data

3d-models deep-learning deep-neural-networks machine-learning space-sim tensorflow

Last synced: about 1 month ago
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Space Sim Inspired Data Set for Machine Learning Purposes

• Host: GitHub
• URL: https://github.com/olitheolix/ds2data
• Owner: olitheolix
• License: other
• Created: 2017-06-17T03:43:03.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2017-08-16T07:07:37.000Z (almost 9 years ago)
• Last Synced: 2025-06-03T03:57:22.487Z (about 1 year ago)
• Topics: 3d-models, deep-learning, deep-neural-networks, machine-learning, space-sim, tensorflow
• Language: Python
• Size: 1.5 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# DS2Data

A Space Sim inspired data set to experiment with machine learning.

The objects of interest are cubes with a number on them. You may think of it as

a 3D version of the [MNIST](http://yann.lecun.com/exdb/mnist/) data set.



In addition to the training samples, the data also contains pre-rendered flight

through a 3D space scene.

The meta data for the flight is in `flightpath/meta.pickle`. It contains, among

other things, the screen position of each cube in each frame. The

`draw_bboxes.py` script shows how to use this information to draw bounding

boxes around all cubes.

| Original Scene               | After `draw_bboxes.py`      |

| ---------------------------- | --------------------------- |

|![](docs/img/scene_plain.jpg) | ![](docs/img/scene_bbox.jpg)|

# Installation

Download the [dataset](ds2.tar.gz) and use it in your ML model as you see fit.

# License

The data set and code are available under the Apache Software License 2.0.

# Disclaimer

The numeral textures are royalty free images

from

[PixaBay](https://pixabay.com/en/photos/?hp=&image_type=&cat=&min_width=&min_height=&q=counting+math+numbers+numerals+funny&order=popular).

The rendered images were created with

[PyHorde](https://github.com/olitheolix/pyhorde).

# Results

My own models are in the `models/` folder. The results are documented

[here](https://olitheolix.github.io/ds2data/)

# Feeback

I would be happy to hear from anyone who uses it. Does it work for you? Is

something missing? Which ML models have you built for it and how well did they

do?