Mercurial > repos > imgteam > imagej2_adjust_threshold_binary
diff imagej2_find_maxima_jython_script.py @ 0:f1ba33cd9edf draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit b08f0e6d1546caaf627b21f8c94044285d5d5b9c-dirty"
author | imgteam |
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date | Tue, 17 Sep 2019 17:09:25 -0400 |
parents | |
children | 29a4d422f32a |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/imagej2_find_maxima_jython_script.py Tue Sep 17 17:09:25 2019 -0400 @@ -0,0 +1,94 @@ +import sys +import jython_utils +from ij import ImagePlus, IJ +from ij.plugin.filter import Analyzer, MaximumFinder +from ij.process import ImageProcessor +from jarray import array + +# Fiji Jython interpreter implements Python 2.5 which does not +# provide support for argparse. +error_log = sys.argv[ -10 ] +input = sys.argv[ -9 ] +scale_when_converting = jython_utils.asbool( sys.argv[ -8 ] ) +weighted_rgb_conversions = jython_utils.asbool( sys.argv[ -7 ] ) +noise_tolerance = int( sys.argv[ -6 ] ) +output_type = sys.argv[ -5 ] +exclude_edge_maxima = jython_utils.asbool( sys.argv[ -4 ] ) +light_background = jython_utils.asbool( sys.argv[ -3 ] ) +tmp_output_path = sys.argv[ -2 ] +output_datatype = sys.argv[ -1 ] + +# Open the input image file. +input_image_plus = IJ.openImage( input ) + +# Create a copy of the image. +input_image_plus_copy = input_image_plus.duplicate() +image_processor_copy = input_image_plus_copy.getProcessor() +bit_depth = image_processor_copy.getBitDepth() +analyzer = Analyzer( input_image_plus_copy ) + +try: + # Set the conversion options. + options = [] + # The following 2 options are applicable only to RGB images. + if bit_depth == 24: + if scale_when_converting: + option.append( "scale" ) + if weighted_rgb_conversions: + options.append( "weighted" ) + # Perform conversion - must happen even if no options are set. + IJ.run( input_image_plus_copy, "Conversions...", "%s" % " ".join( options ) ) + if output_type in [ 'List', 'Count' ]: + # W're generating a tabular file for the output. + # Set the Find Maxima options. + options = [ 'noise=%d' % noise_tolerance ] + if output_type.find( '_' ) > 0: + output_type_str = 'output=[%s]' % output_type.replace( '_', ' ' ) + else: + output_type_str = 'output=%s' % output_type + options.append( output_type_str ) + if exclude_edge_maxima: + options.append( 'exclude' ) + if light_background: + options.append( 'light' ) + # Run the command. + IJ.run( input_image_plus_copy, "Find Maxima...", "%s" % " ".join( options ) ) + results_table = analyzer.getResultsTable() + results_table.saveAs( tmp_output_path ) + else: + # Find the maxima of an image (does not find minima). + # LIMITATIONS: With output_type=Segmented_Particles + # (watershed segmentation), some segmentation lines + # may be improperly placed if local maxima are suppressed + # by the tolerance. + mf = MaximumFinder() + if output_type == 'Single_Points': + output_type_param = mf.SINGLE_POINTS + elif output_type == 'Maxima_Within_Tolerance': + output_type_param = mf.IN_TOLERANCE + elif output_type == 'Segmented_Particles': + output_type_param = mf.SEGMENTED + elif output_type == 'List': + output_type_param = mf.LIST + elif output_type == 'Count': + output_type_param = mf.COUNT + # Get a new byteProcessor with a normal (uninverted) LUT where + # the marked points are set to 255 (Background 0). Pixels outside + # of the roi of the input image_processor_copy are not set. No + # output image is created for output types POINT_SELECTION, LIST + # and COUNT. In these cases findMaxima returns null. + byte_processor = mf.findMaxima( image_processor_copy, + noise_tolerance, + ImageProcessor.NO_THRESHOLD, + output_type_param, + exclude_edge_maxima, + False ) + # Invert the image or ROI. + byte_processor.invert() + if output_type == 'Segmented_Particles' and not light_background: + # Invert the values in this image's LUT (indexed color model). + byte_processor.invertLut() + image_plus = ImagePlus( "output", byte_processor ) + IJ.saveAs( image_plus, output_datatype, tmp_output_path ) +except Exception, e: + jython_utils.handle_error( error_log, str( e ) )