Mercurial > repos > imgteam > imagej2_find_maxima
comparison imagej2_find_maxima_jython_script.py @ 2:6a07f71806bb draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 57a0433defa3cbc37ab34fbb0ebcfaeb680db8d5
author | imgteam |
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date | Sun, 05 Nov 2023 14:19:21 +0000 |
parents | e2622ebb5ce4 |
children | 4409f9eb9433 |
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1:e2622ebb5ce4 | 2:6a07f71806bb |
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6 | 6 |
7 # Fiji Jython interpreter implements Python 2.5 which does not | 7 # Fiji Jython interpreter implements Python 2.5 which does not |
8 # provide support for argparse. | 8 # provide support for argparse. |
9 error_log = sys.argv[-10] | 9 error_log = sys.argv[-10] |
10 input_file = sys.argv[-9] | 10 input_file = sys.argv[-9] |
11 scale_when_converting = sys.argv[-8] == 'yes' | 11 scale_when_converting = sys.argv[-8] == "yes" |
12 weighted_rgb_conversions = sys.argv[-7] == 'yes' | 12 weighted_rgb_conversions = sys.argv[-7] == "yes" |
13 noise_tolerance = int(sys.argv[-6]) | 13 noise_tolerance = int(sys.argv[-6]) |
14 output_type = sys.argv[-5] | 14 output_type = sys.argv[-5] |
15 exclude_edge_maxima = sys.argv[-4] == 'yes' | 15 exclude_edge_maxima = sys.argv[-4] == "yes" |
16 light_background = sys.argv[-3] | 16 light_background = sys.argv[-3] |
17 tmp_output_path = sys.argv[-2] | 17 tmp_output_path = sys.argv[-2] |
18 output_datatype = sys.argv[-1] | 18 output_datatype = sys.argv[-1] |
19 | 19 |
20 # Open the input image file. | 20 # Open the input image file. |
34 options.append("scale") | 34 options.append("scale") |
35 if weighted_rgb_conversions: | 35 if weighted_rgb_conversions: |
36 options.append("weighted") | 36 options.append("weighted") |
37 # Perform conversion - must happen even if no options are set. | 37 # Perform conversion - must happen even if no options are set. |
38 IJ.run(input_image_plus_copy, "Conversions...", "%s" % " ".join(options)) | 38 IJ.run(input_image_plus_copy, "Conversions...", "%s" % " ".join(options)) |
39 if output_type in ['List', 'Count']: | 39 if output_type in ["List", "Count"]: |
40 # W're generating a tabular file for the output. | 40 # W're generating a tabular file for the output. |
41 # Set the Find Maxima options. | 41 # Set the Find Maxima options. |
42 options = ['noise=%d' % noise_tolerance] | 42 options = ["noise=%d" % noise_tolerance] |
43 if output_type.find('_') > 0: | 43 if output_type.find("_") > 0: |
44 output_type_str = 'output=[%s]' % output_type.replace('_', ' ') | 44 output_type_str = "output=[%s]" % output_type.replace("_", " ") |
45 else: | 45 else: |
46 output_type_str = 'output=%s' % output_type | 46 output_type_str = "output=%s" % output_type |
47 options.append(output_type_str) | 47 options.append(output_type_str) |
48 if exclude_edge_maxima: | 48 if exclude_edge_maxima: |
49 options.append('exclude') | 49 options.append("exclude") |
50 if light_background: | 50 if light_background: |
51 options.append('light') | 51 options.append("light") |
52 # Run the command. | 52 # Run the command. |
53 IJ.run(input_image_plus_copy, "Find Maxima...", "%s" % " ".join(options)) | 53 IJ.run(input_image_plus_copy, "Find Maxima...", "%s" % " ".join(options)) |
54 results_table = analyzer.getResultsTable() | 54 results_table = analyzer.getResultsTable() |
55 results_table.saveAs(tmp_output_path) | 55 results_table.saveAs(tmp_output_path) |
56 else: | 56 else: |
58 # LIMITATIONS: With output_type=Segmented_Particles | 58 # LIMITATIONS: With output_type=Segmented_Particles |
59 # (watershed segmentation), some segmentation lines | 59 # (watershed segmentation), some segmentation lines |
60 # may be improperly placed if local maxima are suppressed | 60 # may be improperly placed if local maxima are suppressed |
61 # by the tolerance. | 61 # by the tolerance. |
62 mf = MaximumFinder() | 62 mf = MaximumFinder() |
63 if output_type == 'Single_Points': | 63 if output_type == "Single_Points": |
64 output_type_param = mf.SINGLE_POINTS | 64 output_type_param = mf.SINGLE_POINTS |
65 elif output_type == 'Maxima_Within_Tolerance': | 65 elif output_type == "Maxima_Within_Tolerance": |
66 output_type_param = mf.IN_TOLERANCE | 66 output_type_param = mf.IN_TOLERANCE |
67 elif output_type == 'Segmented_Particles': | 67 elif output_type == "Segmented_Particles": |
68 output_type_param = mf.SEGMENTED | 68 output_type_param = mf.SEGMENTED |
69 elif output_type == 'List': | 69 elif output_type == "List": |
70 output_type_param = mf.LIST | 70 output_type_param = mf.LIST |
71 elif output_type == 'Count': | 71 elif output_type == "Count": |
72 output_type_param = mf.COUNT | 72 output_type_param = mf.COUNT |
73 # Get a new byteProcessor with a normal (uninverted) LUT where | 73 # Get a new byteProcessor with a normal (uninverted) LUT where |
74 # the marked points are set to 255 (Background 0). Pixels outside | 74 # the marked points are set to 255 (Background 0). Pixels outside |
75 # of the roi of the input image_processor_copy are not set. No | 75 # of the roi of the input image_processor_copy are not set. No |
76 # output image is created for output types POINT_SELECTION, LIST | 76 # output image is created for output types POINT_SELECTION, LIST |
77 # and COUNT. In these cases findMaxima returns null. | 77 # and COUNT. In these cases findMaxima returns null. |
78 byte_processor = mf.findMaxima(image_processor_copy, | 78 byte_processor = mf.findMaxima( |
79 noise_tolerance, | 79 image_processor_copy, |
80 ImageProcessor.NO_THRESHOLD, | 80 noise_tolerance, |
81 output_type_param, | 81 ImageProcessor.NO_THRESHOLD, |
82 exclude_edge_maxima, | 82 output_type_param, |
83 False) | 83 exclude_edge_maxima, |
84 False, | |
85 ) | |
84 # Invert the image or ROI. | 86 # Invert the image or ROI. |
85 byte_processor.invert() | 87 byte_processor.invert() |
86 if output_type == 'Segmented_Particles' and not light_background: | 88 if output_type == "Segmented_Particles" and not light_background: |
87 # Invert the values in this image's LUT (indexed color model). | 89 # Invert the values in this image's LUT (indexed color model). |
88 byte_processor.invertLut() | 90 byte_processor.invertLut() |
89 image_plus = ImagePlus("output", byte_processor) | 91 image_plus = ImagePlus("output", byte_processor) |
90 IJ.saveAs(image_plus, output_datatype, tmp_output_path) | 92 IJ.saveAs(image_plus, output_datatype, tmp_output_path) |