friendly_ground_truth

A tool for manually creating ground truth masks from images of plant roots where a significant amount of detail is required.

https://github.com/p2irc/friendly_ground_truth

Science Score: 44.0%

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
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.4%) to scientific vocabulary

Keywords from Contributors

mesh sequences interactive hacking network-simulation
Last synced: 8 months ago · JSON representation ·

Repository

A tool for manually creating ground truth masks from images of plant roots where a significant amount of detail is required.

Basic Info
  • Host: GitHub
  • Owner: p2irc
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 17.6 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 7
  • Releases: 54
Created about 6 years ago · Last pushed over 3 years ago
Metadata Files
Readme License Citation

README.md

CI Tests codecov Documentation

friendlygroundtruth

A tool for manually creating ground truth masks from images where a significant amount of detail is required. Particularily suited for large images of plant roots.

favicon

Installation

An in-depth installation guide can be found here The latest release of the project can be downloaded here.

Quick Links

Windows

Ubuntu

MacOs

Windows

A windows executable can be downloaded here.

You should be able to just download and run it. You may need administrator privileges.

NOTE: If windows gives a popup saying that "it protected you from a file", click on "more info", and then "run anyways".

Ubuntu

An Ubuntu version of the app can be downloaded here.

The zip file contains an executable binary file, an image, and a bash script that will install the application.

Copy-pasta:

Install

wget https://github.com/p2irc/friendly_ground_truth/releases/latest/download/friendly_gt-ubuntu.zip unzip friendly_gt-ubuntu.zip cd friendly_gt_ubuntu bash install_friendly_gt.sh

At this point, if no prompt appears, the application has been installed.

Otherwise: Add ~/bin to your path? (Y/N): yes Specify bash profile file (blank uses ~/.bashrc): ~/.bash_profile # This can be left blank if you prefer

Don't Install

wget https://github.com/p2irc/friendly_ground_truth/releases/latest/download/friendly_gt-ubuntu.zip unzip friendly_gt-ubuntu.zip cd friendly_gt_ubuntu chmod u+x friendly_gt_ubuntu-latest ./friendly_gt_ubuntu-latest

MacOs

A MacOs binary can be downloaded here.

You will need to change the permissions of the binary file to be executable, and then you can run it by double clicking it in the file browser, or by navigating to it in the terminal and typing ./friendly_gt_macos-latest.

Copy-pasta: wget https://github.com/p2irc/friendly_ground_truth/releases/latest/download/friendly_gt_macos-latest chmod u+x friendly_gt_macos-latest ./friendly_gt_macos-latest An experimental MacOs application bundle can be downloaded here. This bundle has not been fully tested, and may not work at all. It should be runnable just like any other mac app bundle once you have unzipped it. If you encounter problems with this bundle, please leave a Bug Report.

User Manual

A user manual can be found in the wiki

Bug Reports

Please report any software bugs on the issues page.

Thanks in advance for helping out!

Development

Detailed information about development for this application can be found on the Wiki

Basic Setup

This application is developed using python3 and virtualenv. Dependencies are found in requirements.txt. To get started:

python -m venv env source ./venv/bin/activate pip install -r requirements.txt

The main entrypoint for the application is run.py. To run it, simply do python run.py -debug. The -debug flag is optional and enables logging.

Tests

Tests have been developed using pytest, with the mocker and coverage modules. All tests can be found in the tests/ directory. To run tests, make sure you are in the main repository folder:

``` pytest --cov=friendlygroundtruth ./tests --cov-branch --cov-report=term-missing

```

This will run all tests and print a coverage report specifying any missed lines. A coverage check is run as part of all pull-requests.

Please refer to the Wiki for more details about the development process.

Documentation

Documentation can be generated with pdoc. Make sure to pip install pdoc3

cd doc pdoc --html ../friendly_ground_truth/

Internal documentation that has been generated by pdoc and can be found here

Owner

  • Name: p2irc
  • Login: p2irc
  • Kind: organization
  • Location: University of Saskatchewan

p2irc

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Seidenthal"
  given-names: "Kyle"
  orcid: " https://orcid.org/0000-0001-7020-4314 "
title: "Friendly Ground Truth"
version: 0.13.2
date-released: 2021-05-18
url: "https://github.com/p2irc/friendly_ground_truth"

GitHub Events

Total
Last Year

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 535
  • Total Committers: 2
  • Avg Commits per committer: 267.5
  • Development Distribution Score (DDS): 0.009
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
KyleS22 2****2 530
dependabot[bot] 4****] 5

Issues and Pull Requests

Last synced: about 2 years ago

All Time
  • Total issues: 44
  • Total pull requests: 56
  • Average time to close issues: 7 days
  • Average time to close pull requests: 10 days
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 0.23
  • Average comments per pull request: 0.34
  • Merged pull requests: 50
  • Bot issues: 0
  • Bot pull requests: 10
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • KyleS22 (44)
Pull Request Authors
  • KyleS22 (46)
  • dependabot[bot] (10)
Top Labels
Issue Labels
bug (27) enhancement (17) merged (17) low priority (4) high priority (2) documentation (1) medium priority (1)
Pull Request Labels
dependencies (10)

Dependencies

requirements.txt pypi
  • Pillow ==8.3.2
  • PyWavelets ==1.1.1
  • altgraph ==0.17
  • attrs ==19.3.0
  • certifi ==2020.4.5.1
  • chardet ==3.0.4
  • coverage ==5.0.4
  • cycler ==0.10.0
  • decorator ==4.4.2
  • entrypoints ==0.3
  • flake8 ==3.7.9
  • idna ==2.9
  • imageio ==2.8.0
  • importlib-metadata ==1.6.0
  • kiwisolver ==1.2.0
  • mccabe ==0.6.1
  • mock ==4.0.2
  • mocker ==1.1.1
  • more-itertools ==8.2.0
  • networkx ==2.4
  • numpy ==1.18.2
  • packaging ==20.3
  • pluggy ==0.13.1
  • py ==1.10.0
  • pycodestyle ==2.5.0
  • pyflakes ==2.1.1
  • pyparsing ==2.4.7
  • pytest ==5.4.1
  • pytest-cov ==2.8.1
  • pytest-mock ==3.0.0
  • python-dateutil ==2.8.1
  • requests ==2.26.0
  • scikit-image ==0.16.2
  • scipy ==1.4.1
  • six ==1.14.0
  • urllib3 ==1.26.5
  • wcwidth ==0.1.9
  • zipp ==3.1.0
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