yaak-ai/rbyte
Multimodal datasets for spatial intelligence
This project helps machine learning engineers prepare complex datasets for training models that understand spatial environments. It takes raw, multimodal sensor data (like images, lidar, radar, GPS) from real-world scenarios and structures it into a format ready for PyTorch. Engineers building autonomous systems or robotics applications would find this useful.
Available on PyPI.
Use this if you are a machine learning engineer working with diverse sensor data to train models for spatial intelligence applications, and you need a standardized, efficient way to manage and feed this data into PyTorch.
Not ideal if you are looking for a plug-and-play solution for a business problem rather than a tool for preparing complex machine learning datasets.
Stars
39
Forks
3
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 06, 2026
Commits (30d)
0
Dependencies
17
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