Skip to main content

Awesome socc_plotter created by AdityaNG

Project description

socc_plotter

codecov CI GitHub License PyPI - Version PyPI - Downloads

Semantic Occupancy 3D Plotter. This is the plotter made by the SOccDPT project to create fancy 3D visuals. You can use this for your own AV or Robotics visualization!

demo

Install it from PyPI

pip install socc_plotter

Usage

The socc_plotter works on a callback mechanism since the GUI must be run on the main thread.

from socc_plotter.plotter import Plotter
import time

def callback(plot: Plotter):
    time.sleep(1)
    print("in callback")
    graph_region = plot.graph_region

    points = np.array([[1, 0, 0]])
    colors = np.array([[1, 1, 1]])

    graph_region.setData(pos=points, color=colors)

plotter = Plotter(
    callback=callback,
)
plotter.start()

NuScenes Demo

Start by downloading the NuScenes mini datset

mkdir -p data/nuscenes/
cd data/nuscenes/
wget -c https://www.nuscenes.org/data/v1.0-mini.tgz
tar -xf v1.0-mini.tgz

Install a few dependencies for the demo

pip install nuscenes-devkit==1.1.10
pip install transformers torch torchvision timm accelerate general_navigation

Run the demo

$ python -m socc_plotter
#or
$ socc_plotter

Development

Read the CONTRIBUTING.md file.

Cite

Cite our work if you find it useful

@article{NG2024SOccDPT,
  title={SOccDPT: 3D Semantic Occupancy from Dense Prediction Transformers trained under memory constraints},
  author={NG, Aditya},
  journal={Advances in Artificial Intelligence and Machine Learning},
  volume={ISSN: 2582-9793, Source Id: 21101164612},
  year={2024},
  url={https://www.oajaiml.com/}
}

TODO

  • Demo
    • RGB Frame
    • Depth perception
    • Semantic segmentation
    • NuScenes Calibration
    • NuScenes Vehicle trajectory
    • Semantic Occupancy Grid
  • Ensure demo dependencies are seperate from the module
  • Demo is to prompt the user to install dependencies
  • Demo is to auto download NuScenes and unarchive it
  • Test Cases
  • PiPy deployment

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

socc_plotter-0.4.0.tar.gz (592.4 kB view details)

Uploaded Source

Built Distribution

socc_plotter-0.4.0-py3-none-any.whl (594.5 kB view details)

Uploaded Python 3

File details

Details for the file socc_plotter-0.4.0.tar.gz.

File metadata

  • Download URL: socc_plotter-0.4.0.tar.gz
  • Upload date:
  • Size: 592.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for socc_plotter-0.4.0.tar.gz
Algorithm Hash digest
SHA256 879c036c8a10c53791da90aa3529f1057608359ed250f5c12ddb5ff4b096fe48
MD5 0ba3ac8986a9545e74615aafed7a0280
BLAKE2b-256 183a0fabee48e391703cdfd5837f1675968f238be3889f65d1af84e2eabcddfd

See more details on using hashes here.

Provenance

File details

Details for the file socc_plotter-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: socc_plotter-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 594.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for socc_plotter-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 e4a06d33ad6a85bd05194054d6e560d0b7a26e1dab28dbc34f73864f295bf281
MD5 9f76047c7072a3d4d22602d692c61852
BLAKE2b-256 02f7f54da5aa1f6dad1dcaee6a317f403467cb96b28c384caa7c1ab06b4aec63

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page