94486a7f-e046-461f-bbb9-334ec7b57040

Showcasing the detectreeRGB model

https://github.com/eds-book/94486a7f-e046-461f-bbb9-334ec7b57040

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
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DOI references
Found 2 DOI reference(s) in README
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Academic publication links
Links to: zenodo.org
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Academic email domains
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (11.2%) to scientific vocabulary

Keywords

deep-learning environmental-data-science forest modelling

Last synced: 6 months ago · JSON representation ·

Repository

Showcasing the detectreeRGB model

Basic Info

Host: GitHub
Owner: eds-book
License: other
Language: Jupyter Notebook
Default Branch: main
Homepage:
Size: 10.5 MB

Statistics

Stars: 0
Watchers: 3
Forks: 0
Open Issues: 1
Releases: 5

Topics

deep-learning environmental-data-science forest modelling

Created almost 4 years ago · Last pushed 6 months ago

Metadata Files

Readme License Citation

README.md

Tree crown delineation using detectreeRGB

How to run

Running on Binder

The notebook is designed to be launched from Binder.

Click the Launch Binder button at the top level of the repository

Running locally

You may also download the notebook from GitHub to run it locally: 1. Open your terminal

Check your conda install with conda --version. If you don't have conda, install it by following these instructions (see here)
Clone the repository bash git clone https://github.com/eds-book-gallery/94486a7f-e046-461f-bbb9-334ec7b57040.git
Move into the cloned repository bash cd 94486a7f-e046-461f-bbb9-334ec7b57040
Create and activate your environment from the .binder/environment.yml file bash conda env create -f .binder/environment.yml conda activate 94486a7f-e046-461f-bbb9-334ec7b57040
Launch the jupyter interface of your preference, notebook, jupyter notebook or lab jupyter lab

Owner

Name: Environmental Data Science Book
Login: eds-book
Kind: organization
Email: environmental.ds.book@gmail.com

Website: https://edsbook.org
Twitter: eds_book
Repositories: 1
Profile: https://github.com/eds-book

Organisation repo of EDS book for governance, outreach and other community-led activities

Citation (CITATION.cff)

cff-version: 1.2.0
message: Please cite the following works when using this project.
abstract: >-
  Notebook developed to demonstrate how to delineating trees using detectron2, a
  library that provides state-of-the-art deep learning detection and
  segmentation algorithms.
title: >-
  Tree crown delineation using detectreeRGB (Jupyter Notebook) published in the
  Environmental Data Science book
authors:
  - family-names: Hickman
    given-names: Sebastian H. M.
    affiliation: University of Cambridge
    orcid: 0000-0002-0148-935X
    email: shmh4@cam.ac.uk
date-released: '2024-09-13'
contact:
  - family-names: Hickman
    given-names: Sebastian H. M.
    affiliation: University of Cambridge
    orcid: 0000-0002-0148-935X
    email: shmh4@cam.ac.uk
identifiers:
  - description: Open review report for this notebook
    type: url
    value: https://github.com/alan-turing-institute/environmental-ds-book/pull/4
keywords:
  - Forest & Biomass
  - Modelling
  - Standard
  - Python
license: MIT
license-url: https://opensource.org/license/MIT
repository: https://github.com/eds-book/94486a7f-e046-461f-bbb9-334ec7b57040
type: software
version: v2025.6.0

GitHub Events

Total

Release event: 1
Push event: 14
Pull request event: 1
Create event: 2

Last Year

Release event: 1
Push event: 14
Pull request event: 1
Create event: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 0
Total pull requests: 8
Average time to close issues: N/A
Average time to close pull requests: about 2 hours
Total issue authors: 0
Total pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 1.75
Merged pull requests: 8
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 3
Average time to close issues: N/A
Average time to close pull requests: about 6 hours
Issue authors: 0
Pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 2.0
Merged pull requests: 3
Bot issues: 0
Bot pull requests: 0

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