Skip to main content

neodroid

Vision

This repository will host implementation computer vision algorithms applying the Neodroid platform.


Neodroid is developed with support from Research Council of Norway Grant #262900. (https://www.forskningsradet.no/prosjektbanken/#/project/NFR/262900)


Build Status Coverage Status GitHub Issues GitHub Forks GitHub Stars GitHub License

python pytorch

numpy tqdm

Contents Of This Readme

Algorithms

Requirements

  • pytorch
  • tqdm
  • Pillow
  • numpy
  • matplotlib
  • torchvision
  • torch
  • Neodroid
  • pynput

To install these use the command:

pip3 install -r requirements.txt

Usage

Export python path to the repo root so we can use the utilities module

export PYTHONPATH=/path-to-repo/

For training a agent use:

python3 procedures/train_agent.py

For testing a trained agent use:

python3 procedures/test_agent.py

Results

Semntation

Using Depth, Segmentation And RGB images to estimate the location of target point in an environment.

Code

Screenshots

Segmentation

Contributing

See guidelines for contributing here.

Citation

For citation you may use the following bibtex entry:

@misc{neodroid-vision,
  author = {Heider, Christian},
  title = {Neodroid Vision},
  year = {2019},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/sintefneodroid/Vision}},
}

Metadata

Release files for NeodroidVision 0.0.1.20190501120313

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for NeodroidVision 0.0.1.20190501120313
File Interpreter ABI Platform Actions
NeodroidVision-0.0.1.20190501120313-py36-none-any.whl Python 3.6 none any Details for NeodroidVision-0.0.1.20190501120313-py36-none-any.whl

Release files / NeodroidVision-0.0.1.20190501120313-py36-none-any.whl

Download URL NeodroidVision-0.0.1.20190501120313-py36-none-any.whl
Size 50.7 kB
Tags Python 3.6
SHA-256 checksum
How to use checksums
e5b804745dac15a160e4f241c4ce572e18c42efc4fb4729afe081592c7f350ab
BLAKE2b-256 checksum
How to use checksums
9df18730ab31a347eb704789547b148adbd3ead89ccc545ee6cbdf90840d152a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.13.0 pkginfo/1.5.0.1 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.31.1 CPython/3.7.1

Security for NeodroidVision 0.0.1.20190501120313

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page