addapted local filter

Readme.md

@@ -1,6 +1,6 @@
-October 31, 2024
+November 1, 2024
 
-Version: 1.1.1
+Version: 1.1.2
 
 
 <img src="./user_manual/figs/logo.png" style="zoom:20%;" />

myptv/segmentation_mod.py

@@ -8,13 +8,18 @@
 contains a class for segmentation of circular particles
 """
 
-from tracking_2D_mod import track_2D_multiframe
+from myptv.tracking_2D_mod import track_2D_multiframe
 from myptv.TsaiModel.camera import camera_Tsai
+from myptv.tracking_mod import fill_in_trajectory
 
-from numpy import ones, savetxt, meshgrid
+from pandas import read_csv
+
+from numpy import ones, savetxt, meshgrid, float32
 from numpy import sum as npsum
 from numpy import abs as npabs
 from numpy import median as npmedian
+from numpy import array 
+from numpy import append as npappend
 
 from skimage.io import imread
 from skimage import io
@@ -101,13 +106,23 @@ def __init__(self, image, sigma=None, threshold=10, mask=1.0,
     def local_filter(self, image):
         '''returns a new image where the local mean neighbourhood of
         each pixel is subtracted.'''
-        w = self.loc_filter
-        window = ones((w, w)) / w**2
-        local_mean = convolve2d(image, window, mode='same')
-        new_im = image - local_mean
-        new_im[new_im<0] = 0
-        new_im = new_im.astype('uint8')
-        return new_im
+        # w = self.loc_filter
+        # window = ones((w, w)) / w**2
+        # local_mean = convolve2d(image, window, mode='same')
+        # new_im = image - local_mean
+        # new_im[new_im<0] = 0
+        # new_im = new_im.astype('uint8')
+
+        S = self.loc_filter
+        flt = image.astype(float32) #/ 255.0
+        blur = gaussian_filter(flt, S)
+        num = flt - blur
+
+        blur = gaussian_filter(num*num, S)
+        den = blur**0.5        
+        normed = num / den
+
+        return image * (normed>1)
 
 
 
@@ -610,10 +625,6 @@ def save_results(self, fname):
 
 
 
-from numpy import array 
-from numpy import append as npappend
-from pandas import read_csv
-from tracking_mod import fill_in_trajectory
 
 class tracking_augmented_segmentation(track_2D_multiframe):
 

setup.py

@@ -9,7 +9,7 @@
 setup(
     name='myptv',
     packages=find_packages(include=['myptv', 'myptv.fibers', 'myptv.TsaiModel', 'myptv.extendedZolof', 'myptv.makePlots', 'myptv.sheets']),
-    version='1.1.1',
+    version='1.1.2',
     description='A 3D Particle Tracking Velocimetry library',
     install_requires=['numpy', 'scipy', 'scikit-image','pandas','matplotlib','pyyaml', 'tk', 'Pillow>=9.5.0'],
     author='Ron Shnapp',

user_manual/user_manual.aux

@@ -97,31 +97,33 @@
 \@writefile{toc}{\contentsline {subsubsection}{\numberline {3.3.1}How to segment in MyPTV}{14}{subsubsection.3.3.1}}
 \@writefile{toc}{\contentsline {subsubsection}{\numberline {3.3.2}Two methods of segmentation}{14}{subsubsection.3.3.2}}
 \citation{Bourgoin2020}
-\@writefile{lof}{\contentsline {figure}{\numberline {9}{\ignorespaces The effect oft various image filters on the segmentation.\relax }}{15}{figure.caption.13}}
-\newlabel{fig:image_filters}{{9}{15}{The effect oft various image filters on the segmentation.\relax }{figure.caption.13}{}}
-\@writefile{lof}{\contentsline {figure}{\numberline {10}{\ignorespaces An example showing that segmentation using the dilation method can be very useful when segmenting large objects as it can resolve overlap issues.\relax }}{15}{figure.caption.14}}
-\newlabel{fig:Labeling_vs_Dilation}{{10}{15}{An example showing that segmentation using the dilation method can be very useful when segmenting large objects as it can resolve overlap issues.\relax }{figure.caption.14}{}}
+\@writefile{lof}{\contentsline {figure}{\numberline {9}{\ignorespaces An example showing that segmentation using the dilation method can be very useful when segmenting large objects as it can resolve overlap issues.\relax }}{15}{figure.caption.13}}
+\newlabel{fig:Labeling_vs_Dilation}{{9}{15}{An example showing that segmentation using the dilation method can be very useful when segmenting large objects as it can resolve overlap issues.\relax }{figure.caption.13}{}}
+\@writefile{toc}{\contentsline {subsubsection}{\numberline {3.3.3}Segmentation filters}{15}{subsubsection.3.3.3}}
+\newlabel{sec:segment_filters}{{3.3.3}{15}{Segmentation filters}{subsubsection.3.3.3}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.4}Matching}{15}{subsection.3.4}}
 \newlabel{sec:workflow_match}{{3.4}{15}{Matching}{subsection.3.4}{}}
 \citation{Ouellette2006}
-\citation{Luthi2005}
-\citation{Xu2008}
+\@writefile{lof}{\contentsline {figure}{\numberline {10}{\ignorespaces The effect oft various image filters on the segmentation.\relax }}{16}{figure.caption.14}}
+\newlabel{fig:image_filters}{{10}{16}{The effect oft various image filters on the segmentation.\relax }{figure.caption.14}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.5}Tracking}{16}{subsection.3.5}}
 \newlabel{sec:workflow_track}{{3.5}{16}{Tracking}{subsection.3.5}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.6}Calibration with particles}{16}{subsection.3.6}}
 \newlabel{sec:workflow_calibration_with_particles}{{3.6}{16}{Calibration with particles}{subsection.3.6}{}}
-\@writefile{toc}{\contentsline {subsection}{\numberline {3.7}Smoothing}{16}{subsection.3.7}}
-\newlabel{sec:workflow_smooth}{{3.7}{16}{Smoothing}{subsection.3.7}{}}
+\citation{Luthi2005}
+\citation{Xu2008}
 \@writefile{lof}{\contentsline {figure}{\numberline {11}{\ignorespaces An example for experimental setup for 2D tracking. Note that the camera doesn't have to be perpendicular to the particles' plane and that the particles don't have to be at $z=0$. \relax }}{17}{figure.caption.20}}
 \newlabel{fig:2D_tracking}{{11}{17}{An example for experimental setup for 2D tracking. Note that the camera doesn't have to be perpendicular to the particles' plane and that the particles don't have to be at $z=0$. \relax }{figure.caption.20}{}}
+\@writefile{toc}{\contentsline {subsection}{\numberline {3.7}Smoothing}{17}{subsection.3.7}}
+\newlabel{sec:workflow_smooth}{{3.7}{17}{Smoothing}{subsection.3.7}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.8}Stitching}{17}{subsection.3.8}}
 \newlabel{sec:workflow_stitch}{{3.8}{17}{Stitching}{subsection.3.8}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.9}2D tracking guide}{17}{subsection.3.9}}
 \newlabel{sec:2D_tracking}{{3.9}{17}{2D tracking guide}{subsection.3.9}{}}
-\@writefile{toc}{\contentsline {subsection}{\numberline {3.10}Manual Matching GUI}{17}{subsection.3.10}}
-\newlabel{sec:man_match}{{3.10}{17}{Manual Matching GUI}{subsection.3.10}{}}
 \citation{Shnapp2023}
 \citation{Shnapp2023}
+\@writefile{toc}{\contentsline {subsection}{\numberline {3.10}Manual Matching GUI}{18}{subsection.3.10}}
+\newlabel{sec:man_match}{{3.10}{18}{Manual Matching GUI}{subsection.3.10}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.11}Fiber tracking}{18}{subsection.3.11}}
 \newlabel{sec:fibers}{{3.11}{18}{Fiber tracking}{subsection.3.11}{}}
 \@writefile{toc}{\contentsline {subsection}{\numberline {3.12}Plotting the results}{18}{subsection.3.12}}