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comparison imagej2_find_maxima_jython_script.py @ 0:db3066ae9b09 draft default tip

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 8f49f3c66b5a1de99ec15e65c2519a56792f1d56
author imgteam
date Wed, 25 Sep 2024 16:28:45 +0000
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-1:000000000000 0:db3066ae9b09
1 import sys
2
3 from ij import IJ, ImagePlus
4 from ij.plugin.filter import Analyzer, MaximumFinder
5 from ij.process import ImageProcessor
6
7 # Fiji Jython interpreter implements Python 2.5 which does not
8 # provide support for argparse.
9 input_file = sys.argv[-9]
10 scale_when_converting = sys.argv[-8] == "yes"
11 weighted_rgb_conversions = sys.argv[-7] == "yes"
12 noise_tolerance = int(sys.argv[-6])
13 output_type = sys.argv[-5]
14 exclude_edge_maxima = sys.argv[-4] == "yes"
15 light_background = sys.argv[-3]
16 tmp_output_path = sys.argv[-2]
17 output_datatype = sys.argv[-1]
18
19 # Open the input image file.
20 input_image_plus = IJ.openImage(input_file)
21
22 # Create a copy of the image.
23 input_image_plus_copy = input_image_plus.duplicate()
24 image_processor_copy = input_image_plus_copy.getProcessor()
25 bit_depth = image_processor_copy.getBitDepth()
26 analyzer = Analyzer(input_image_plus_copy)
27
28 # Set the conversion options.
29 options = []
30 # The following 2 options are applicable only to RGB images.
31 if bit_depth == 24:
32 if scale_when_converting:
33 options.append("scale")
34 if weighted_rgb_conversions:
35 options.append("weighted")
36 # Perform conversion - must happen even if no options are set.
37 IJ.run(input_image_plus_copy, "Conversions...", " %s" % " ".join(options))
38 if output_type in ["List", "Count"]:
39 # W're generating a tabular file for the output.
40 # Set the Find Maxima options.
41 options = ["noise=%d" % noise_tolerance]
42 if output_type.find("_") > 0:
43 output_type_str = "output=[%s]" % output_type.replace("_", " ")
44 else:
45 output_type_str = "output=%s" % output_type
46 options.append(output_type_str)
47 if exclude_edge_maxima:
48 options.append("exclude")
49 if light_background:
50 options.append("light")
51 # Run the command.
52 IJ.run(input_image_plus_copy, "Find Maxima...", "%s" % " ".join(options))
53 results_table = analyzer.getResultsTable()
54 results_table.saveAs(tmp_output_path)
55 else:
56 # Find the maxima of an image (does not find minima).
57 # LIMITATIONS: With output_type=Segmented_Particles
58 # (watershed segmentation), some segmentation lines
59 # may be improperly placed if local maxima are suppressed
60 # by the tolerance.
61 mf = MaximumFinder()
62 if output_type == "Single_Points":
63 output_type_param = mf.SINGLE_POINTS
64 elif output_type == "Maxima_Within_Tolerance":
65 output_type_param = mf.IN_TOLERANCE
66 elif output_type == "Segmented_Particles":
67 output_type_param = mf.SEGMENTED
68 elif output_type == "List":
69 output_type_param = mf.LIST
70 elif output_type == "Count":
71 output_type_param = mf.COUNT
72 # Get a new byteProcessor with a normal (uninverted) LUT where
73 # the marked points are set to 255 (Background 0). Pixels outside
74 # of the roi of the input image_processor_copy are not set. No
75 # output image is created for output types POINT_SELECTION, LIST
76 # and COUNT. In these cases findMaxima returns null.
77 byte_processor = mf.findMaxima(
78 image_processor_copy,
79 noise_tolerance,
80 ImageProcessor.NO_THRESHOLD,
81 output_type_param,
82 exclude_edge_maxima,
83 False,
84 )
85 # Invert the image or ROI.
86 byte_processor.invert()
87 if output_type == "Segmented_Particles" and not light_background:
88 # Invert the values in this image's LUT (indexed color model).
89 byte_processor.invertLut()
90 image_plus = ImagePlus("output", byte_processor)
91 IJ.saveAs(image_plus, output_datatype, tmp_output_path)