Mercurial > repos > imgteam > imagej2_noise
view imagej2_analyze_particles_binary_jython_script.py @ 3:73cc4e6a741d draft default tip
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/image_processing/imagej2 commit 8f49f3c66b5a1de99ec15e65c2519a56792f1d56
author | imgteam |
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date | Wed, 25 Sep 2024 16:16:10 +0000 |
parents | 756e062741dc |
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import sys from ij import IJ, Prefs from ij.plugin.filter import Analyzer OPTIONS = ["edm=Overwrite", "iterations=1", "count=1"] # Fiji Jython interpreter implements Python 2.5 which does not # provide support for argparse. roi_coordinate_file = sys.argv[-13] input_file = sys.argv[-12] black_background = sys.argv[-11] == "yes" size = sys.argv[-10] circularity_min = float(sys.argv[-9]) circularity_max = float(sys.argv[-8]) show = sys.argv[-7] display_results = sys.argv[-6] == "yes" exclude_edges = sys.argv[-5] == "yes" include_holes = sys.argv[-4] == "yes" output_filename = sys.argv[-3] output_datatype = sys.argv[-2] results_path = sys.argv[-1] if black_background: Prefs.blackBackground = True else: Prefs.blackBackground = False # Open the input image file. input_image_plus = IJ.openImage(input_file) # Create a copy of the image. input_image_plus_copy = input_image_plus.duplicate() image_processor_copy = input_image_plus_copy.getProcessor() analyzer = Analyzer(input_image_plus_copy) # Set binary options. options_list = OPTIONS if black_background: options_list.append("black") options = " ".join(options_list) IJ.run(input_image_plus_copy, "Options...", options) if not image_processor_copy.isBinary(): # Convert the image to binary grayscale. IJ.run(input_image_plus_copy, "Make Binary", "") # Set the options. options = ["size=%s" % size, "stack"] circularity_str = "%.3f-%.3f" % (circularity_min, circularity_max) options.append("circularity=%s" % circularity_str) if exclude_edges: options.append("exclude") if include_holes: options.append("include") # If you need the coordinates of ROIs we compute it twice if len(roi_coordinate_file) > 0: options2 = list(options) options2.append("show=Overlay") IJ.run(input_image_plus_copy, "Analyze Particles...", " ".join(options2)) ov = input_image_plus_copy.getOverlay() with open(roi_coordinate_file, 'w') as fo: fo.write("shape\tpoints\tlabel\tt\tz\n") for i, roi in enumerate(ov): if roi.getName() is None: roi.name = "ROI_%d" % i poly = roi.getPolygon() x_values = poly.xpoints y_values = poly.ypoints points_coo = ",".join(["(%d,%d)" % (x, y) for x, y in zip(x_values, y_values)]) fo.write("Polygon\t%s\t%s\t%d\t%d\n" % (points_coo, roi.getName(), roi.getTPosition(), roi.getZPosition())) analyzer.resetCounter() if show.find("_") >= 0: show_str = "[%s]" % show.replace("_", " ") else: show_str = show options.append("show=%s" % show_str) if display_results: options.append("display") # Always run "in_situ". options.append("in_situ") # Run the command. IJ.run(input_image_plus_copy, "Analyze Particles...", " ".join(options)) # Save outputs. if len(output_filename) > 0: # Save the ImagePlus object as a new image. IJ.saveAs(input_image_plus_copy, output_datatype, output_filename) if len(results_path) > 0: results_table = analyzer.getResultsTable() results_table.saveAs(results_path)