managed to compute the image mean value
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								lipase.py
								
								
								
								
							
							
						
						
									
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								lipase.py
								
								
								
								
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					@ -7,7 +7,8 @@
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# the 'greeting' output parameter, based on its type.
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					# the 'greeting' output parameter, based on its type.
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from ij import IJ  # pylint: disable=import-error
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					from ij import IJ  # pylint: disable=import-error
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from ij import ImagePlus  # pylint: disable=import-error
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					from ij import ImagePlus  # pylint: disable=import-error
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					from ij.process import ImageStatistics
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					from ij.plugin import ImageCalculator
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# greeting = "Hello, " + name + "!"
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					# greeting = "Hello, " + name + "!"
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					@ -176,13 +177,20 @@ class ImageCatalog(object):
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def get_image_median_value(src_image):
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					def get_image_median_value(src_image):
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    return 0
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					    '''
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					    :param ImageProcessor src_image:
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					    '''
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					    # https://imagej.nih.gov/ij/developer/api/ij/process/ImageStatistics.html
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					    stats = ImageStatistics.getStatistics(src_image, ImageStatistics.MEDIAN, None)
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					    print(stats)
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					    print(stats.pixelCount)
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					    return stats.median
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def test_get_image_median_value():
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					def test_get_image_median_value():
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    image_file_path = '/Users/graffy/ownCloud/ipr/lipase/raw-images/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_327-353_fluo_000.tif'
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					    image_file_path = '/Users/graffy/ownCloud/ipr/lipase/raw-images/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_327-353_fluo_000.tif'
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    image = IJ.openImage(image_file_path)
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					    image = IJ.openImage(image_file_path)
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    median_value = get_image_median_value(image)
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					    median_value = get_image_median_value(image.getProcessor())
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    print('median value : %d' % median_value)
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					    print('median value : %d' % median_value)
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# double median( cv::Mat channel )
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					# double median( cv::Mat channel )
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					@ -213,12 +221,28 @@ def test_get_image_median_value():
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def find_depth_index(src_image, white_sequence):
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					def find_depth_index(src_image, white_sequence):
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    ''' finds in the image sequence white_sequence the image that correlates the best to src_image
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					    ''' finds in the image sequence white_sequence the image that correlates the best to src_image
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    :param IJ.ImagePlus src_image:
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					    :param IJ.ImageProcessor src_image:
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    :param Sequence white_sequence:
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					    :param Sequence white_sequence:
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    '''
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					    '''
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					    src_median_value = get_image_median_value(src_image)
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					    normalized_src = src_image.convertToFloat()
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					    normalized_src.multiply(1.0 / src_median_value)
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    for z_index in range(white_sequence.num_slices):
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					    for z_index in range(white_sequence.num_slices):
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        white_image_file_path = white_sequence.get_image_file_path(channel_index=0, frame_index=0, z_index=z_index)
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					        white_image_file_path = white_sequence.get_image_file_path(channel_index=0, frame_index=0, z_index=z_index)
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        white_image = IJ.openImage(white_image_file_path)
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					        white_image = IJ.openImage(white_image_file_path)
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					        white_median_value = get_image_median_value(white_image.getProcessor())
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					        # white_to_src_factor = 1.0 / float(white_median_value)
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					        normalized_white = white_image.getProcessor().convertToFloat()
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					        normalized_white.multiply(1.0 / float(white_median_value))
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					        imp1 = IJ.openImage("http://imagej.nih.gov/ij/images/boats.gif")
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					        print(imp1)
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					        imp2 = IJ.openImage("http://imagej.nih.gov/ij/images/bridge.gif")
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					        print(imp2)
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					        ic = ImageCalculator()
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					        imp3 = ic.run("sub create float", imp1, imp2)
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					        imp3.show()
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        # imp2mat = ImagePlusMatConverter()
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					        # imp2mat = ImagePlusMatConverter()
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        # white_mat = imp2mat.toMat(white_image.getProcessor())
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					        # white_mat = imp2mat.toMat(white_image.getProcessor())
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        # white_mat = imread(white_image_file_path)
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					        # white_mat = imread(white_image_file_path)
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					@ -235,7 +259,7 @@ def process_sequence(sequence):
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    src_image_file_path = sequence.get_image_file_path(channel_index=0, frame_index=0, z_index=0)
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					    src_image_file_path = sequence.get_image_file_path(channel_index=0, frame_index=0, z_index=0)
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    src_image = IJ.openImage(src_image_file_path)
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					    src_image = IJ.openImage(src_image_file_path)
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    # src_image = IJ.openImage(src_image_file_path)
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					    # src_image = IJ.openImage(src_image_file_path)
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    find_depth_index(src_image, white_seq)
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					    find_depth_index(src_image.getProcessor(), white_seq)
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def run_script():
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					def run_script():
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					@ -261,5 +285,5 @@ def run_script():
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# If a Jython script is run, the variable __name__ contains the string '__main__'.
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					# If a Jython script is run, the variable __name__ contains the string '__main__'.
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# If a script is loaded as module, __name__ has a different value.
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					# If a script is loaded as module, __name__ has a different value.
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if __name__ in ['__builtin__', '__main__']:
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					if __name__ in ['__builtin__', '__main__']:
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    # run_script()
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					    run_script()
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    test_get_image_median_value()
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					    # test_get_image_median_value()
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