changeset 0:4d6e6901df43 draft default tip

planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/2d_feature_extraction/ commit d93e1dd276027cfc3fb518236110395a23d96f66
author thomaswollmann
date Wed, 16 Jan 2019 15:32:39 -0500
parents
children
files 2d_feature_extraction.py 2d_feature_extraction.xml test-data/input.tiff test-data/out.csv
diffstat 4 files changed, 224 insertions(+), 0 deletions(-) [+]
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--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/2d_feature_extraction.py	Wed Jan 16 15:32:39 2019 -0500
@@ -0,0 +1,124 @@
+import argparse
+import numpy as np
+import pandas as pd
+import tifffile
+import skimage.io
+import skimage.measure
+import skimage.feature
+import skimage.segmentation
+import skimage.morphology
+
+#TODO make importable by python script
+
+parser = argparse.ArgumentParser(description='Extract Features 2D')
+
+#TODO create factory for boilerplate code
+features = parser.add_argument_group('compute features')
+features.add_argument('--all', dest='all_features', action='store_true')
+features.add_argument('--label', dest='add_label', action='store_true')
+features.add_argument('--patches', dest='add_roi_patches', action='store_true')
+features.add_argument('--max_intensity', dest='max_intensity', action='store_true')
+features.add_argument('--mean_intensity', dest='mean_intensity', action='store_true')
+features.add_argument('--min_intensity', dest='min_intensity', action='store_true')
+features.add_argument('--moments_hu', dest='moments_hu', action='store_true')
+features.add_argument('--centroid', dest='centroid', action='store_true')
+features.add_argument('--bbox', dest='bbox', action='store_true')
+features.add_argument('--area', dest='area', action='store_true')
+features.add_argument('--filled_area', dest='filled_area', action='store_true')
+features.add_argument('--convex_area', dest='convex_area', action='store_true')
+features.add_argument('--perimeter', dest='perimeter', action='store_true')
+features.add_argument('--extent', dest='extent', action='store_true')
+features.add_argument('--eccentricity', dest='eccentricity', action='store_true')
+features.add_argument('--equivalent_diameter', dest='equivalent_diameter', action='store_true')
+features.add_argument('--euler_number', dest='euler_number', action='store_true')
+features.add_argument('--inertia_tensor_eigvals', dest='inertia_tensor_eigvals', action='store_true')
+features.add_argument('--major_axis_length', dest='major_axis_length', action='store_true')
+features.add_argument('--minor_axis_length', dest='minor_axis_length', action='store_true')
+features.add_argument('--orientation', dest='orientation', action='store_true')
+features.add_argument('--solidity', dest='solidity', action='store_true')
+features.add_argument('--moments', dest='moments', action='store_true')
+features.add_argument('--convexity', dest='convexity', action='store_true')
+
+parser.add_argument('--label_file_binary', dest='label_file_binary', action='store_true')
+
+parser.add_argument('--raw', dest='raw_file', type=argparse.FileType('r'),
+                   help='Original input file', required=False)
+parser.add_argument('label_file', type=argparse.FileType('r'),
+                   help='Label input file')
+parser.add_argument('output_file', type=argparse.FileType('w'),
+                   help='Tabular output file')
+args = parser.parse_args()
+
+label_file_binary = args.label_file_binary
+label_file = args.label_file.name
+out_file = args.output_file.name
+add_patch = args.add_roi_patches
+
+raw_image = None
+if args.raw_file is not None:
+    raw_image = skimage.io.imread(args.raw_file.name)
+
+raw_label_image = skimage.io.imread(label_file)
+
+df = pd.DataFrame()
+if label_file_binary:
+    raw_label_image = skimage.measure.label(raw_label_image)
+regions = skimage.measure.regionprops(raw_label_image, intensity_image=raw_image)
+
+df['it'] = np.arange(len(regions))
+
+if add_patch:
+    df['image'] = df['it'].map(lambda ait: regions[ait].image.astype(np.float).tolist())
+    df['intensity_image'] = df['it'].map(lambda ait: regions[ait].intensity_image.astype(np.float).tolist())
+
+#TODO no matrix features, but split in own rows?
+if args.add_label or args.all_features:
+    df['label'] = df['it'].map(lambda ait: regions[ait].label)
+
+if raw_image is not None:
+    if args.max_intensity or args.all_features:
+        df['max_intensity'] = df['it'].map(lambda ait: regions[ait].max_intensity)
+    if args.mean_intensity or args.all_features:
+        df['mean_intensity'] = df['it'].map(lambda ait: regions[ait].mean_intensity)
+    if args.min_intensity or args.all_features:
+        df['min_intensity'] = df['it'].map(lambda ait: regions[ait].min_intensity)
+    if args.moments_hu or args.all_features:
+        df['moments_hu'] = df['it'].map(lambda ait: regions[ait].moments_hu)
+
+if args.centroid or args.all_features:
+    df['centroid'] = df['it'].map(lambda ait: regions[ait].centroid)
+if args.bbox or args.all_features:
+    df['bbox'] = df['it'].map(lambda ait: regions[ait].bbox)
+if args.area or args.all_features:
+    df['area'] = df['it'].map(lambda ait: regions[ait].area)
+if args.filled_area or args.all_features:
+    df['filled_area'] = df['it'].map(lambda ait: regions[ait].filled_area)
+if args.convex_area or args.all_features:
+    df['convex_area'] = df['it'].map(lambda ait: regions[ait].convex_area)
+if args.perimeter or args.all_features:
+    df['perimeter'] = df['it'].map(lambda ait: regions[ait].perimeter)
+if args.extent or args.all_features:
+    df['extent'] = df['it'].map(lambda ait: regions[ait].extent)
+if args.eccentricity or args.all_features:
+    df['eccentricity'] = df['it'].map(lambda ait: regions[ait].eccentricity)
+if args.equivalent_diameter or args.all_features:
+    df['equivalent_diameter'] = df['it'].map(lambda ait: regions[ait].equivalent_diameter)
+if args.euler_number or args.all_features:
+    df['euler_number'] = df['it'].map(lambda ait: regions[ait].euler_number)
+if args.inertia_tensor_eigvals or args.all_features:
+    df['inertia_tensor_eigvals'] = df['it'].map(lambda ait: regions[ait].inertia_tensor_eigvals)
+if args.major_axis_length or args.all_features:
+    df['major_axis_length'] = df['it'].map(lambda ait: regions[ait].major_axis_length)
+if args.minor_axis_length or args.all_features:
+    df['minor_axis_length'] = df['it'].map(lambda ait: regions[ait].minor_axis_length)
+if args.orientation or args.all_features:
+    df['orientation'] = df['it'].map(lambda ait: regions[ait].orientation)
+if args.solidity or args.all_features:
+    df['solidity'] = df['it'].map(lambda ait: regions[ait].solidity)
+if args.moments or args.all_features:
+    df['moments'] = df['it'].map(lambda ait: regions[ait].moments)
+if args.convexity or args.all_features:
+    df['convexity'] = df.area/(df.perimeter*df.perimeter)
+
+del df['it']
+df.to_csv(out_file, sep='\t', line_terminator='\n', index=False)
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/2d_feature_extraction.xml	Wed Jan 16 15:32:39 2019 -0500
@@ -0,0 +1,88 @@
+<?xml version="1.0"?>
+<tool name="2D Feature Extraction" id="ip_2d_feature_extraction" version="0.0.8">
+  <description>Feature Extraction</description>
+  <requirements>
+    <requirement type="package" version="0.23.4">pandas</requirement>
+    <requirement type="package" version="0.14.0">scikit-image</requirement>
+    <requirement type="package" version="1.15.4">numpy</requirement>
+    <requirement type="package" version="0.15.1">tifffile</requirement>
+  </requirements>
+  <command>
+  <![CDATA[
+    python '$__tool_directory__/2d_feature_extraction.py'
+    #if $feature_options['features'] == 'all'
+      --all
+    #else if $feature_options['features'] == 'select'
+      ${' '.join(str( $feature_options['selected_features'] ).split(','))}
+    #end if
+    #if $use_raw_option['use_raw'] == 'raw_image'
+      --raw '$input_raw'
+    #end if
+    '$input_label' '$output'
+    ]]>
+  </command>
+  <inputs>
+        <param name="input_label" type="data" format="tiff" label="Label file" />
+        <conditional name="use_raw_option">
+          <param label="Use original image to compute additional features" name="use_raw" type="select">
+            <option selected="True" value="no_original">No original image</option>
+            <option value="raw_image">Use original image</option>
+          </param>
+          <when value="no_original"> </when>
+          <when value="raw_image">
+            <param name="input_raw" type="data" format="tiff" label="Original image file" />
+          </when>
+        </conditional>
+        <conditional name="feature_options">
+            <param label="Select features to compute" name="features" type="select">
+              <option selected="True" value="all">All features</option>
+              <option value="select">Select features</option>
+            </param>
+            <when value="all"> </when>
+            <when value="select">
+              <param name="selected_features" type="select" label="Available features" multiple="true" display="checkboxes">
+                <option value="--label">Add label id of label image</option>
+                <option value="--patches">Patches (requires original image)</option>
+                <option value="--max_intensity">Max Intensity (requires original image)</option>
+                <option value="--mean_intensity">Mean Intensity (requires original image)</option>
+                <option value="--min_intensity">Minimum Intensity (requires original image)</option>
+                <option value="--moments_hu">Moments Hu</option>
+                <option value="--centroid">Centroid</option>
+                <option value="--bbox">Bounding Box</option>
+                <option value="--area">Area</option>
+                <option value="--filled_area">Filled Area</option>
+                <option value="--convex_area">Convex Area</option>
+                <option value="--perimeter">Perimeter</option>
+                <option value="--extent">Extent</option>
+                <option value="--eccentricity">Eccentricity</option>
+                <option value="--equivalent_diameter">Equivalent Diameter</option>
+                <option value="--euler_number">Euler Number</option>
+                <option value="--inertia_tensor_eigvals">Inertia Tensor Eigenvalues</option>
+                <option value="--major_axis_length">Major Axis Length</option>
+                <option value="--minor_axis_length">Minor Axis Length</option>
+                <option value="--orientation">Orientation</option>
+                <option value="--solidity">Solidity</option>
+                <option value="--moments">Moments</option>
+                <option value="--convexity">Convexity</option>
+              </param>
+            </when>
+        </conditional>
+  </inputs>
+  <outputs>
+       <data format="tabular" name="output" />
+  </outputs>
+  <tests>
+    <test>
+      <param name="input_label" value="input.tiff"/>
+      <param name="features" value="select"/>
+      <param name="selected_features" value="--area"/>
+      <output name="output" ftype="tabular" value="out.csv"/>
+    </test>
+  </tests>
+  <help>
+    This tool computes several features of a 2D label image and optionally more features using the original image.
+  </help>
+  <citations>
+      <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation>
+  </citations>
+</tool>
Binary file test-data/input.tiff has changed
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/out.csv	Wed Jan 16 15:32:39 2019 -0500
@@ -0,0 +1,12 @@
+area
+612
+612
+375
+375
+729
+729
+399
+399
+3
+3
+434042