Skip to main content

A collection of image and statistical processing functions and classes

Project description

PyLogik

A Python package dedicated to sharing functions and classes for common image processing and statistical tools. This includes Sorensen–Dice coefficient (Dice) score and plotting functions.


Citing this work:

A. Kline, PyLogik, 2022


  • Integration with Jupyter Lab/Jupyter Notebooks
  • Built-in plotting functionality for image comparisons


Installation

Install the package through pip:

$ pip install pylogik

Image Processing Import

from pylogik.image import imag_analysis

Data Import

Options for reading in images:

  • Matplotlib - plt.imread()

  • OpenCV - cv2.imread()

  • Pillow - Image.open()

  • scikit-image - io.imread()

# read in your data
im1 = cv2.imread('example_im1.png')
im2 = cv2.imread('example_im2.png')

Dice Score

The mathematical formalism of the Dice score is denoted by the equation:

$$ DSC = \frac{2*|X \cap Y|}{|X|+ |Y|} $$

where $\cap$ denotes the intersection of two images $X$ and $Y$.

Performing the calculation using a function in PyLogik:

dice = imag_analysis.dice_score(pred, true, k=1)

Note:

  • pred - array of the predicted segmentation
  • true - array of the ground truth segmentation
  • k - value to perform matching on (default = 1)
  • Returns: dice score (float)

Impairshow Graphical Output

imshowpair returns the array and image associated with a dice score comparison of 2 logical images. Colors are prespecified as magenta and green but can be adjusted by the user.

imag_analysis.imshowpair(pred, true, color1 = (124,252,0), color2 = (255,0,252), show_fig = True):

Note:

  • pred - array of the predicted segmentation
  • true - array of the ground truth segmentation
  • color1 - first color to show unique values from first image
  • color2 - second color to show unique values from second image
  • Returns: array and graphical plot

Conclusion

This package offers a user friendly dice score calculation and dice score plotting functionality to showcase the intersection and complement of each image relative to the other. This package will be continually built on to incorporate other statistical and image processin functionality

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pylogik-0.0.2.tar.gz (4.5 kB view details)

Uploaded Source

Built Distribution

pylogik-0.0.2-py3-none-any.whl (4.8 kB view details)

Uploaded Python 3

File details

Details for the file pylogik-0.0.2.tar.gz.

File metadata

  • Download URL: pylogik-0.0.2.tar.gz
  • Upload date:
  • Size: 4.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for pylogik-0.0.2.tar.gz
Algorithm Hash digest
SHA256 a2896204436a10a88e960c98fb7c372b96ab6c23b0eb3c92db2b3dc17d8d924d
MD5 b4974067bb2101a68fda04983cd6b75b
BLAKE2b-256 a9e004bb373503c6c4bf2a0d32541f14be300c3b91bdb06c71a8dadee1078b3e

See more details on using hashes here.

File details

Details for the file pylogik-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: pylogik-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 4.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for pylogik-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 247fa8ace547e2cca333c6d75919aa246948ecebe244ecdc1d813f192c6973e8
MD5 2ed327c8a7c366d8dd626ece0ec92cdc
BLAKE2b-256 507fc8d4aa47498e8ccb1606c136ee03c58f9ea13b0eee69b77cba9c7dee353f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page