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pytextureanalysis

PyTextureAnalysis is a Python package for analyzing the texture of images. It includes functions for calculating local orientation, degree of coherence, and structure tensor of an image. This package is built using NumPy, SciPy and OpenCV.

https://github.com/ajinkya-kulkarni/pytextureanalysis

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 1 DOI reference(s) in README
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    Academic publication links
    Links to: zenodo.org
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    Scientific vocabulary similarity
    Low similarity (14.4%) to scientific vocabulary

Keywords

fibre-organization orientation-detection python texture-analysis
Last synced: 6 months ago · JSON representation ·

Repository

PyTextureAnalysis is a Python package for analyzing the texture of images. It includes functions for calculating local orientation, degree of coherence, and structure tensor of an image. This package is built using NumPy, SciPy and OpenCV.

Basic Info
Statistics
  • Stars: 30
  • Watchers: 3
  • Forks: 7
  • Open Issues: 0
  • Releases: 3
Topics
fibre-organization orientation-detection python texture-analysis
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

Streamlit App License: GPL v3 DOI GitHub commit activity GitHub release (latest by date)

Texture Analysis using PyTextureAnalysis

PyTextureAnalysis is a Python package that contains tools to analyze the texture of images. This code contains functions to calculate the local orientation of fibers in an image, as well as the degree of coherence. A web application is also available for demonstrating the PyTextureAnalysis package, which allows users to analyze 2D grayscale images for texture analysis.

Features

  • Upload a 2D grayscale image for texture analysis
  • Adjust image filter sigma, Gaussian local window, and window size for evaluating local density
  • Adjust threshold value for pixel evaluation, spacing between orientation vectors, and scaling for orientation vectors
  • Calculates local density, coherence, and orientation of the image
  • Provides a progress bar for each stage of the analysis

Demo

A web application developed using Streamlit is available at https://textureinformation-package.streamlit.app/. Check out the Example.ipynb file to learn how to use the package to extract and visualize local fiber orientation and organization.

App Overview

Streamlit App Screenshot

Requirements

  • Python 3.8 or higher
  • Streamlit
  • NumPy
  • scikit-image
  • Matplotlib

Installation

  1. Clone the repository.
  2. Install the required packages via pip install -r requirements.txt.
  3. Run the web application via streamlit run PyTextureAnalysis_StreamlitApp.py.

Usage

  1. Open the web application via streamlit run PyTextureAnalysis_StreamlitApp.py.
  2. Upload a 2D grayscale image for analysis.
  3. Adjust the various parameters using the sliders provided.
  4. Click the "Analyze" button to begin the analysis.
  5. View the progress of the analysis via the progress bar.
  6. View the results of the analysis.

Credits

This web application was developed, tested, and maintained by Ajinkya Kulkarni at the Max Planck Institute for Multidisciplinary Sciences, Göttingen.

Contact

For more information or to provide feedback, please visit the project repository or contact the developer directly.

Owner

  • Name: Ajinkya Kulkarni
  • Login: ajinkya-kulkarni
  • Kind: user
  • Location: Göttingen
  • Company: Max Planck Institute for Multidisciplinary Sciences

Image Data Scientist @mpi_nat working in Translational Oncology

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Kulkarni"
  given-names: "Ajinkya"
  orcid: "https://orcid.org/0000-0003-1423-3676"
title: "PyTextureAnalysis"
version: 1.0
doi: 10.5281/zenodo.7562833
date-released: 2023-01-23
url: "https://github.com/ajinkya-kulkarni/PyTextureAnalysis"

GitHub Events

Total
  • Issues event: 3
  • Watch event: 6
  • Issue comment event: 1
Last Year
  • Issues event: 3
  • Watch event: 6
  • Issue comment event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 2
  • Total pull requests: 0
  • Average time to close issues: 13 days
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 0.5
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: 13 days
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 0.5
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • Broccaaa (1)
  • pravallika-kambhampati (1)
Pull Request Authors
  • DragonflyRobotics (1)
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Dependencies

requirements.txt pypi
  • Pillow *
  • matplotlib *
  • numpy *
  • opencv-python-headless *
  • scikit-image *
  • scipy *
  • tqdm *