telekinesis-datatypes 0.0.1rc5

Official core data types and serialization utilities package for the Telekinesis SDK and APIs.

Telekinesis Examples | Telekinesis Data

GitHub  •  LinkedIn  •  X  •  Discord

Telekinesis Datatypes

Telekinesis Datatypes is a core library providing canonical, strongly typed data structures for robotics and computer vision within the Telekinesis ecosystem. It includes:

• 3D data types: point clouds, meshes, transforms, and geometric primitives
• 2D data types: images, bounding boxes, masks, and pixel-space geometry
• Standardized representations for common perception and geometry formats
• Efficient serialization and deserialization for reliable data exchange

This library is used internally by the Telekinesis SDK as the foundation for data exchange across perception, planning, and learning components.

Telekinesis Datatypes is currently in its initial release cycle, published as release candidates (RC).

Important: Please note that in this phase, the modules are introduced incrementally, and the versions are continuously evolving, therefore please always ensure you are on the latest version of the package.

Installation

1. Create an isolated environment so that there is no dependency conflicts. We recommend installing Miniconda environment by following instructions from here.

2. Create a new conda environment called datatypes:

   conda create -n datatypes python=3.11
   

3. Activate the environment:

   conda activate datatypes
   

4. Install the core SDK using pip:

   We currently support Python versions - 3.11, 3.12. Ensure your environment is in the specified Python version.

   pip install telekinesis-datatypes
   

   Note: The Python module is called datatypes, while the package published on PyPI is telekinesis-datatypes.

Example

Run a sample python code to quickly test your installation.

1. Create a Python file named datatypes_example.py in a directory of your choice in your system, and copy paste the below:

   import numpy as np
   from datatypes import datatypes
   
   # Create Rgba32 colors for R, G, B
   red = datatypes.Rgba32([255, 0, 0, 255])
   green = datatypes.Rgba32([0, 255, 0, 255])
   blue = datatypes.Rgba32([0, 0, 255, 255])
   
   print(f"Red color (packed uint32): {red.rgba}")
   print(f"Green color (packed uint32): {green.rgba}")
   print(f"Blue color (packed uint32): {blue.rgba}")
   
   # Use __int__() to convert to integer
   red_int = int(red)
   
   print(f"Red as int: {red_int}")
   print(f"Direct comparison: int(red) == red.rgba: {red_int == red.rgba}" )
   

2. On a terminal, navigate to the directory where the above file named datatypes_example.py has been created, run the below command:

   python datatypes_example.py
   

   Expected output:

   Red color (packed uint32): 4278190335
   Green color (packed uint32): 16711935
   Blue color (packed uint32): 65535
   Red as int: 4278190335
   Direct comparison: int(red) == red.rgba: True
   

You are now set up with Telekinesis Datatypes.

Resources

• Examples
  Runnable usage examples for Telekinesis Datatypes: Telekinesis Examples (see examples/datatypes_examples.py)

• Documentation
  Full SDK documentation and usage details: Telekinesis Documentation

• Sample Data
  Datasets used across the examples: Telekinesis Data

Support

For issues and questions:

• Create an issue in the GitHub repository.
• Contact the Telekinesis development team at [e-mail] or on Discord.