image-processing-samplecode-python

This is image processing sample opensource code using python.

https://github.com/8kcool/image-processing-samplecode-python

Science Score: 31.0%

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
○
DOI references
○
Academic publication links
○
Academic email domains
○
Institutional organization owner
○
JOSS paper metadata
○
Scientific vocabulary similarity
Low similarity (12.4%) to scientific vocabulary

Last synced: 10 months ago · JSON representation ·

Repository

This is image processing sample opensource code using python.

Basic Info

Host: GitHub
Owner: 8KCool
License: other
Language: Python
Default Branch: main
Size: 74.7 MB

Statistics

Stars: 4
Watchers: 1
Forks: 0
Open Issues: 0
Releases: 0

Created over 3 years ago · Last pushed over 3 years ago

Metadata Files

Readme Contributing License Code of conduct Citation Support

Image processing in Python

Installation from binaries

pip: pip install scikit-image
conda: conda install -c conda-forge scikit-image

Also see installing scikit-image.

Installation from source

Install dependencies using:

pip install -r requirements.txt

Then, install scikit-image using:

$ pip install .

If you plan to develop the package, you may run it directly from source:

$ pip install -e . # Do this once to add package to Python path

Every time you modify Cython files, also run:

$ python setup.py build_ext -i # Build binary extensions

License (Modified BSD)

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of skimage nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Owner

Name: 8K
Login: 8KCool
Kind: user
Location: Ukraine
Company: Upwork

Repositories: 37
Profile: https://github.com/8KCool

Professional Full-Stack Developer * Front-end (Vue.js, React.js, Phaser.js, HTML/CSS, Browser Extension) * Back-end (Python, Django, Go, Ruby)

Citation (CITATION.bib)

@article{scikit-image,
    title = {scikit-image: image processing in Python},
    author = {van der Walt, Stéfan and Schönberger, Johannes L. and
              Nunez-Iglesias, Juan and Boulogne, François and
              Warner, Joshua D. and Yager, Neil and Gouillart, Emmanuelle and
              Yu, Tony and the scikit-image contributors},
    year = {2014},
    month = {jun},
    keywords = {Image processing, Reproducible research, Education,
                Visualization, Open source, Python, Scientific programming},
    abstract = {scikit-image is an image processing library that implements
                algorithms and utilities for use in research, education and
                industry applications. It is released under the liberal
                Modified BSD open source license, provides a well-documented
                API in the Python programming language, and is developed by
                an active, international team of collaborators. In this paper
                we highlight the advantages of open source to achieve the
                goals of the scikit-image library, and we showcase several
                real-world image processing applications that use scikit-image.
                More information can be found on the project homepage,
                http://scikit-image.org.},
    volume = {2},
    pages = {e453},
    journal = {PeerJ},
    issn = {2167-8359},
    url = {https://doi.org/10.7717/peerj.453},
    doi = {10.7717/peerj.453}
}

ecosyste.ms

Data

Tools

Indexes

Applications

Experiments

Open Source Science