290 lines
12 KiB
Python
290 lines
12 KiB
Python
# String(label="Please enter your name",description="Name field") name
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# OUTPUT String greeting
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# A Jython script with parameters.
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# It is the duty of the scripting framework to harvest
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# the 'name' parameter from the user, and then display
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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 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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# image prefix :
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# AF
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# blé : coupes de blé
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# CA : coupe d'amande
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# FE : feuille d'épinard
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# GGH : globule gras humain
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# CRF chloroplastes de feuille d'épinard
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# OL : oléosome
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# DARK : dark
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# white :
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#
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# - cin1 : cinétique 1
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# phiG_40x_1 : cinétique avant et après injection enzyme gastrique
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# phiG_40x_Zstack20um_1 : stack
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# 0mn : on commence à enregistrer et on attend 10mn (pour le bleaching) -> phiG_40x_1
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# 10mn : debut injection phase gastrique (poussée)
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# 13mn : la phase gastrique (le petit tuyau contient 20ul) arrive dans la cellule d'un coup (1 nanol)
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# 15mn : on arrête l'injection
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# 50mn : on fait un stack -> phiG_40x_Zstack20um_1
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# 51mn : début d'injection phase intestinale (poussée) -> phiG_I_40x_1
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# x mn : on arrête l'injection
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# 90mn : on fait un stack -> phiG_I_40x_Zstack20um_1
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# - cin2 : autre échantillon similaire à cin1
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# - cond[5678] : condition non réalistes
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import json
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class Sequence(object):
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def __init__(self, catalog, sequence_id, micro_manager_metadata_file_path):
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self.catalog = catalog
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self.sequence_id = sequence_id
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self.micro_manager_metadata_file_path = micro_manager_metadata_file_path
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print(micro_manager_metadata_file_path)
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with open(micro_manager_metadata_file_path, "r") as mmm_file:
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self.mmm = json.load(mmm_file, encoding='latin-1') # note : the micromanager metadata files are encoded in latin-1, not utf8 (see accents in comments)
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@property
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def num_frames(self):
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summary = self.mmm['Summary']
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return int(summary['Frames'])
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@property
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def width(self):
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summary = self.mmm['Summary']
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return int(summary['Width'])
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@property
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def height(self):
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summary = self.mmm['Summary']
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return int(summary['Height'])
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@property
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def num_channels(self):
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summary = self.mmm['Summary']
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return int(summary['Channels'])
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@property
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def num_slices(self):
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summary = self.mmm['Summary']
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return int(summary['Slices'])
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@property
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def num_bits_per_pixels(self):
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summary = self.mmm['Summary']
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return int(summary['BitDepth'])
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def get_root_path(self):
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return '/'.join(self.micro_manager_metadata_file_path.split('/')[:-1])
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def get_image_file_path(self, channel_index, frame_index, z_index=0):
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'''
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:param int channel_index:
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:param int frame_index:
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:param int z_index:
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'''
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assert frame_index < self.num_frames
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assert channel_index < self.num_channels
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frame_info = self.mmm['FrameKey-%d-%d-%d' % (frame_index, channel_index, z_index)]
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rel_file_path = frame_info['FileName']
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return self.get_root_path() + '/' + rel_file_path
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def get_channel_index(self, channel_id):
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'''
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:param str channel_id:
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'''
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summary = self.mmm['Summary']
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channel_index = summary['ChNames'].index(channel_id)
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return channel_index
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def get_black(self):
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''' returns the black sequence related to the the sequence self
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:return Sequence:
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'''
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seqid_to_black = {
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'res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0': 'res_soleil2018/DARK/DARK_40X_60min_1 im pae min_1/Pos0',
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'res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2': 'res_soleil2018/DARK/DARK_40X_60min_1 im pae min_1/Pos0',
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}
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white_sequence = seqid_to_black[self.sequence_id]
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return self.catalog.sequences[white_sequence]
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def get_white(self):
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''' returns the white sequence related to the the sequence self
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:return Sequence:
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'''
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seqid_to_white = {
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'res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0': 'res_soleil2018/white/white_24112018_2/Pos0',
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'res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2': 'res_soleil2018/white/white_24112018_2/Pos0',
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}
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white_sequence = seqid_to_white[self.sequence_id]
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return self.catalog.sequences[white_sequence]
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def open_in_imagej(self):
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# ip = IJ.createHyperStack(title=self.sequence_id, width=self.width, height= self.height, channels=1, slices=1, frames=self.get_num_frames(), bitdepth=16)
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hyperstack = IJ.createHyperStack(self.sequence_id, self.width, self.height, self.num_channels, self.num_slices, self.num_frames, self.num_bits_per_pixels)
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for channel_index in range(self.num_channels):
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for frame_index in range(self.num_frames):
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slice_index = 0
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src_image_file_path = self.get_image_file_path(channel_index=channel_index, frame_index=frame_index)
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# print(src_image_file_path)
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src_image = IJ.openImage(src_image_file_path)
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# print(src_image.getProperties())
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hyperstack.setPositionWithoutUpdate(channel_index + 1, slice_index + 1, frame_index + 1)
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hyperstack.setProcessor(src_image.getProcessor())
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hyperstack.show()
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for channel_index in range(self.num_channels):
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hyperstack.setPositionWithoutUpdate(channel_index + 1, 1, 1)
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IJ.run("Enhance Contrast", "saturated=0.35")
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return hyperstack
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class ImageCatalog(object):
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def __init__(self, raw_images_root):
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self.raw_images_root = raw_images_root
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self.sequences = {}
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# nb : we use the path as sequence id because the "Comment" field in the summary section of the metadata file is not guaranteed to be unique (eg they are the same in res_soleil2018/white/white_24112018_1/Pos0 and in res_soleil2018/white/white_24112018_2/Pos0)
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sequence_ids = []
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sequence_ids.append('res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0')
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sequence_ids.append('res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2')
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sequence_ids.append('res_soleil2018/DARK/DARK_40X_60min_1 im pae min_1/Pos0')
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sequence_ids.append('res_soleil2018/DARK/DARK_40X_zstack_vis_327-353_1/Pos0')
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# sequence_ids.append('res_soleil2018/white/white_24112018_1/Pos0') # this sequence seems broken (only 5 images while there's supposed to be 201 frames)
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sequence_ids.append('res_soleil2018/white/white_24112018_2/Pos0')
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for sequence_id in sequence_ids:
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micro_manager_metadata_file_path = raw_images_root + '/' + sequence_id + '/metadata.txt'
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# micro_manager_metadata_file_path = '/tmp/toto.json'
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self.sequences[sequence_id] = Sequence(self, sequence_id, micro_manager_metadata_file_path)
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def __str__(self):
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for sequence_id, sequence in self.sequences.iteritems():
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return str(sequence_id) + ':' + str(sequence)
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# self.add_micromanager_metadata(raw_images_root + '/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/metadata.txt')
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# def add_micromanager_metadata(self, micro_manager_metadata_file_path):
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# self.sequences[ micro_manager_metadata_file_path ] = Sequence(self, micro_manager_metadata_file_path)
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def get_image_median_value(src_image):
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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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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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median_value = get_image_median_value(image.getProcessor())
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print('median value : %d' % median_value)
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# double median( cv::Mat channel )
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# {
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# double m = (channel.rows*channel.cols) / 2;
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# int bin = 0;
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# double med = -1.0;
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# int histSize = 256;
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# float range[] = { 0, 256 };
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# const float* histRange = { range };
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# bool uniform = true;
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# bool accumulate = false;
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# cv::Mat hist;
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# cv::calcHist( &channel, 1, 0, cv::Mat(), hist, 1, &histSize, &histRange, uniform, accumulate );
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# for ( int i = 0; i < histSize && med < 0.0; ++i )
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# {
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# bin += cvRound( hist.at< float >( i ) );
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# if ( bin > m && med < 0.0 )
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# med = i;
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# }
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# return med;
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# }
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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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:param IJ.ImageProcessor src_image:
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:param Sequence white_sequence:
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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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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_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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# white_mat = imp2mat.toMat(white_image.getProcessor())
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# white_mat = imread(white_image_file_path)
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print(white_image)
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break
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def process_sequence(sequence):
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'''
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:param Sequence sequence:
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'''
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white_seq = sequence.get_white()
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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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find_depth_index(src_image.getProcessor(), white_seq)
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def run_script():
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raw_images_root = '/Users/graffy/ownCloud/ipr/lipase/raw-images'
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catalog = ImageCatalog(raw_images_root)
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print(catalog)
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# catalog.sequences['GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0'].open_in_imagej()
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# catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2'].open_in_imagej()
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# catalog.sequences['DARK_40X_60min_1 im pae min_1/Pos0'].open_in_imagej()
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# catalog.sequences['white_24112018_1/Pos0'].open_in_imagej()
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process_sequence(catalog.sequences['res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos2'])
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if False:
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sequence = catalog.sequences['GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0']
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src_image_file_path = sequence.get_image_file_path(channel_index=sequence.get_channel_index('DM300_327-353_fluo'), frame_index=3)
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src_image = IJ.openImage(src_image_file_path) # pylint: disable=unused-variable
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# dark_image = IJ.openImage(raw_images_root + '/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_327-353_fluo_000.tif')
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# src_image.show()
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# assert src_image
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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 __name__ in ['__builtin__', '__main__']:
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run_script()
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# test_get_image_median_value()
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