Skip to main content

Evaluation of Plane Segmentation.

Project description

EVOPS: library for evaluating plane segmentation algorithms

Build and publish

EVOPS is an open-source python library that provides various metrics for evaluating the results of the algorithms for segmenting and associating planes from point clouds collected from LIDARs and RGBD devices.

List of metrics implemented in the library:

For more, please visit the EVOPS documentation.

You can also find full information about the project on the EVOPS project website.

Python quick start

Library can be installed using the pip package manager:

$ # Install package
$ pip install evops

$ # Check installed version of package
$ pip show evops

Example of usage

Below is an example of using the precision metric:

>>> from evops.metrics import precision
>>> pred_labels = np.array([1, 1, 3, 3])
>>> gt_labels = np.array([2, 2, 0, 3])
>>> tp_condition = "iou"
>>> precision(pred_labels, gt_labels, tp_condition)
0.5

Citation

@misc{kornilova2022evops,
      title={EVOPS Benchmark: Evaluation of Plane Segmentation from RGBD and LiDAR Data}, 
      author={Anastasiia Kornilova, Dmitrii Iarosh, Denis Kukushkin, Nikolai Goncharov, Pavel Mokeev, Arthur Saliou, Gonzalo Ferrer},
      year={2022},
      eprint={2204.05799},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

License

This project is licensed under the Apache License - see the LICENSE file for details.

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

evops-1.0.0.tar.gz (13.9 kB view details)

Uploaded Source

Built Distribution

evops-1.0.0-py3-none-any.whl (24.7 kB view details)

Uploaded Python 3

File details

Details for the file evops-1.0.0.tar.gz.

File metadata

  • Download URL: evops-1.0.0.tar.gz
  • Upload date:
  • Size: 13.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.15 CPython/3.9.16 Linux/5.15.0-1023-azure

File hashes

Hashes for evops-1.0.0.tar.gz
Algorithm Hash digest
SHA256 2ab81ba7535e7ddeb45942c942f0055a0c9e4c7b64043685e59dce443d72873f
MD5 dbff7f2ab87f43bb7e1971d2ac529224
BLAKE2b-256 8b5ba0576dea7a452603f26df54b5099e67155c4078252ad31b7978671ff2594

See more details on using hashes here.

File details

Details for the file evops-1.0.0-py3-none-any.whl.

File metadata

  • Download URL: evops-1.0.0-py3-none-any.whl
  • Upload date:
  • Size: 24.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.15 CPython/3.9.16 Linux/5.15.0-1023-azure

File hashes

Hashes for evops-1.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a9f19fcfcab81d90ef5158f7cde13a5b7ad8f5e85ea7dfd8be3c261e31b8559a
MD5 e7b7760ee2538d392a06103bcce0158e
BLAKE2b-256 439433cb5d9be1f9e0c7937e6b13922eefeccdc3c91cb13dc6c9fb3f23acbf74

See more details on using hashes here.

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