Skip to main content

The ilvo plant centre model package

Project description

CenterNet ILVO

Introduction

This python package can be used to run the CenterNet model for plant centre detection. The plant CenterNet model is presented in the following paper:

Willekens, A., Callens, B., Pieters, J., Wyffels, F., & Cool, S. (2025). 
Cauliflower centre detection and 3-dimensional tracking for robotic intrarow weeding. 
Precision Agriculture. Springer.

An example for usage is provided on the Hugging Face - CenterNet ILVO

Installation

  1. Install pytorch (torch and torchvision)
  2. Install dependencies and the package
pip install numpy opencv-python scikit-image
pip install cams-ilvo-utils
pip install centernet-ilvo

Licence

This project is under the ILVO LICENCE.

Copyright (c) 2024 Flanders Research Institute for Agriculture, Fisheries and Food (ILVO)

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

When the Software, including modifications and extensions, is used for:
- commercial or non-commercial machinery: the ILVO logo has to be clearly
   visible on the machine or on any promotion material which may be used in any
   agricultural fair or conference, in a way it is clear that ILVO contributed
   to the development of the software for the machine.
- a scientific or vulgarising publication: a reference to ILVO must be made as
   well as to the website of the living lab Agrifood Technology of ILVO:
   https://www.agrifoodtechnology.be

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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

centernet_ilvo-0.0.1.tar.gz (5.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

centernet_ilvo-0.0.1-py3-none-any.whl (7.4 kB view details)

Uploaded Python 3

File details

Details for the file centernet_ilvo-0.0.1.tar.gz.

File metadata

  • Download URL: centernet_ilvo-0.0.1.tar.gz
  • Upload date:
  • Size: 5.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for centernet_ilvo-0.0.1.tar.gz
Algorithm Hash digest
SHA256 a9b269fd11f8622fbb08e615f50f72da1c218cb54876e4cbfbbec0f613d90bd3
MD5 ad229f9fbe0376c169d180ca37f18047
BLAKE2b-256 5940bfb71fa3a8aa14f8d36d578b1d11d4cdc022adba41da6eb657b9287c7b50

See more details on using hashes here.

Provenance

The following attestation bundles were made for centernet_ilvo-0.0.1.tar.gz:

Publisher: ci.yml on cams-ilvo/centernet-ilvo

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file centernet_ilvo-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: centernet_ilvo-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 7.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.0.1 CPython/3.12.8

File hashes

Hashes for centernet_ilvo-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 3995818df92a9694771f46f0419614dcb3064d909029594aae8f076a438fed37
MD5 5a842aec7c7d9f5d95587aa08f1124c5
BLAKE2b-256 2ab912c65a171dc553b9acec94a9a85d1745a875e09c65ebd60e71835dad3f28

See more details on using hashes here.

Provenance

The following attestation bundles were made for centernet_ilvo-0.0.1-py3-none-any.whl:

Publisher: ci.yml on cams-ilvo/centernet-ilvo

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

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