15d986da-2d7c-44fb-af71-700494485def

Showcasing the deepforest model

https://github.com/eds-book/15d986da-2d7c-44fb-af71-700494485def

Science Score: 67.0%

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

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CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
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.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 deepforest model

Basic Info

Host: GitHub
Owner: eds-book
License: other
Language: Jupyter Notebook
Default Branch: main
Homepage:
Size: 13.5 MB

Statistics

Stars: 2
Watchers: 2
Forks: 2
Open Issues: 0
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 detection using DeepForest

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/15d986da-2d7c-44fb-af71-700494485def.git
Move into the cloned repository bash cd 15d986da-2d7c-44fb-af71-700494485def
Create and activate your environment from the .binder/environment.yml file bash conda env create -f .binder/environment.yml conda activate 15d986da-2d7c-44fb-af71-700494485def
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 detect tree crown using a
  state-of-art Deep Learning model for object detection.
title: >-
  Tree crown detection using DeepForest (Jupyter Notebook) published in the
  Environmental Data Science book
authors:
  - family-names: Coca-Castro
    given-names: Alejandro
    affiliation: The Alan Turing Institute
    orcid: 0000-0002-9264-1539
    email: acoca@turing.ac.uk
date-released: '2024-09-13'
contact:
  - family-names: Coca-Castro
    given-names: Alejandro
    affiliation: The Alan Turing Institute
    orcid: 0000-0002-9264-1539
    email: acoca@turing.ac.uk
identifiers:
  - description: Open review report for this notebook
    type: url
    value: https://github.com/alan-turing-institute/environmental-ds-book/pull/5
keywords:
  - Forest & Biomass
  - Modelling
  - Standard
  - Python
license: MIT
license-url: https://opensource.org/license/MIT
repository: https://github.com/eds-book/15d986da-2d7c-44fb-af71-700494485def
type: software
version: v2025.6.0

GitHub Events

Total

Issue comment event: 5
Push event: 24
Pull request event: 3
Fork event: 1
Create event: 1

Last Year

Issue comment event: 5
Push event: 24
Pull request event: 3
Fork event: 1
Create event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 0
Total pull requests: 7
Average time to close issues: N/A
Average time to close pull requests: about 6 hours
Total issue authors: 0
Total pull request authors: 2
Average comments per issue: 0
Average comments per pull request: 1.86
Merged pull requests: 6
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 4
Average time to close issues: N/A
Average time to close pull requests: about 12 hours
Issue authors: 0
Pull request authors: 2
Average comments per issue: 0
Average comments per pull request: 1.75
Merged pull requests: 3
Bot issues: 0
Bot pull requests: 0

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