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short description in each function
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ajitjohnson committed Mar 4, 2024
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11 changes: 6 additions & 5 deletions pixelpartitioner/PixelPartitioner.py
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# Created on Tue Feb 13 22:02:40 2024
# @author: Ajit Johnson Nirmal
"""
!!! abstract "Short Description"
The `PixelPartitioner` function applies multi-class OTSU thresholding to a set of images
to partition pixels based on intensity. It iteratively increases the number of classes for
images with a high percentage of pixels exceeding a specified threshold, accumulating
results in a DataFrame. The final results are saved in a CSV file within the specified output folder.
The `PixelPartitioner` function applies multi-class OTSU thresholding to a set of images
to partition pixels based on intensity. It iteratively increases the number of classes for
images with a high percentage of pixels exceeding a specified threshold, accumulating
results in a DataFrame. The final results are saved in a CSV file within the specified output folder.
## Function
"""


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8 changes: 5 additions & 3 deletions pixelpartitioner/getImages.py
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#@author: Ajit johnson Nirmal

"""
The `pp.getImages` function retrieves image file paths from a specified directory,
with an optional filter for file extensions. It simplifies collecting images for analysis,
allowing for specific format selection in folders with multiple elements.
!!! abstract "Short Description"
The `pp.getImages` function retrieves image file paths from a specified directory,
with an optional filter for file extensions. It simplifies collecting images for analysis,
allowing for specific format selection in folders with multiple elements.
## Function
"""
# import
import os
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11 changes: 6 additions & 5 deletions pixelpartitioner/plotPixel.py
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# Created on Sun Mar 3 14:13:43 2024
# @author: Ajit Johnson Nirmal
"""
!!! abstract "Short Description"
The `plotPixel` function visualizes the effect of multi-class OTSU thresholding on an image,
highlighting the positive regions determined by the threshold. he result is a side-by-side plot
of the original and highlighted images, with a quantitative display of the positive pixels'
percentage.
The `plotPixel` function visualizes the effect of multi-class OTSU thresholding on an image,
highlighting the positive regions determined by the threshold. he result is a side-by-side plot
of the original and highlighted images, with a quantitative display of the positive pixels'
percentage.
## Function
"""

#import
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2 changes: 1 addition & 1 deletion pyproject.toml
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[tool.poetry]
name = "pixelpartitioner"
version = "1.0.1"
version = "1.0.2"
description = "Tools for pixel partitioning, intensity-based segmentation, and visualization."
authors = ["Ajit Johnson Nirmal <ajitjohnson.n@gmail.com>"]
readme = "README.md"
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