Mercurial > repos > bgruening > cp_measure_texture
view test-data/identify_primary_objects.cppipe @ 3:658a2a451aec draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit c3917e27eb1c1deeb381aa0dc8161c07699562fb"
author | bgruening |
---|---|
date | Mon, 11 May 2020 07:45:48 -0400 |
parents | |
children | 80b200ae516b |
line wrap: on
line source
CellProfiler Pipeline: http://www.cellprofiler.org Version:3 DateRevision:319 GitHash: ModuleCount:5 HasImagePlaneDetails:False Images:[module_num:1|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'To begin creating your project, use the Images module to compile a list of files and/or folders that you want to analyze. You can also specify a set of rules to include only the desired files in your selected folders.\']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] : Filter images?:Images only Select the rule criteria:and (extension does isimage) (directory doesnot startwith ".") Metadata:[module_num:2|svn_version:\'Unknown\'|variable_revision_number:4|show_window:False|notes:\x5B\'The Metadata module optionally allows you to extract information describing your images (i.e, metadata) which will be stored along with your measurements. This information can be contained in the file name and/or location, or in an external file.\']|batch_state:array([], dtype=uint8)|enabled:True|wants_pause:False] Extract metadata?:Yes Metadata data type:Text Metadata types:{} Extraction method count:1 Metadata extraction method:Extract from file/folder names Metadata source:File name Regular expression to extract from file name:(?P<field1>.*)_(?P<field2>[a-zA-Z0-9]+)_(?P<field3>[a-zA-Z0-9]+)_(?P<field4>[a-zA-Z0-9]+) Regular expression to extract from folder name:(?P<folderField1>.*) Extract metadata from:All images Select the filtering criteria:and (file does contain "") Metadata file location: Match file and image metadata:[] Use case insensitive matching?:No NamesAndTypes:[module_num:3|svn_version:\'Unknown\'|variable_revision_number:8|show_window:False|notes:\x5B\'The NamesAndTypes module allows you to assign a meaningful name to each image by which other modules will refer to it.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Assign a name to:Images matching rules Select the image type:Grayscale image Name to assign these images:DNA Match metadata:[] Image set matching method:Order Set intensity range from:Image metadata Assignments count:1 Single images count:0 Maximum intensity:255.0 Process as 3D?:No Relative pixel spacing in X:1.0 Relative pixel spacing in Y:1.0 Relative pixel spacing in Z:1.0 Select the rule criteria:and (file does startwith "im") Name to assign these images:DNA Name to assign these objects:Cell Select the image type:Grayscale image Set intensity range from:Image metadata Select the image type:Grayscale image Maximum intensity:255.0 Groups:[module_num:4|svn_version:\'Unknown\'|variable_revision_number:2|show_window:False|notes:\x5B\'The Groups module optionally allows you to split your list of images into image subsets (groups) which will be processed independently of each other. Examples of groupings include screening batches, microtiter plates, time-lapse movies, etc.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Do you want to group your images?:Yes grouping metadata count:1 Metadata category:field1 IdentifyPrimaryObjects:[module_num:5|svn_version:\'Unknown\'|variable_revision_number:13|show_window:True|notes:\x5B\'Identify the nuclei from the DNA channel.\', \'PARAMS\x3A\', \'- Typical diameter of objects (Min,Max)\', \'- Method to distinguish clumped objects\x3A Shape/None. With Shape, the distance between the 2 centers can be changed.\'\x5D|batch_state:array(\x5B\x5D, dtype=uint8)|enabled:True|wants_pause:False] Select the input image:DNA Name the primary objects to be identified:Nuclei Typical diameter of objects, in pixel units (Min,Max):15,200 Discard objects outside the diameter range?:Yes Discard objects touching the border of the image?:Yes Method to distinguish clumped objects:Shape Method to draw dividing lines between clumped objects:Shape Size of smoothing filter:0 Suppress local maxima that are closer than this minimum allowed distance:7 Speed up by using lower-resolution image to find local maxima?:Yes Fill holes in identified objects?:After both thresholding and declumping Automatically calculate size of smoothing filter for declumping?:Yes Automatically calculate minimum allowed distance between local maxima?:Yes Handling of objects if excessive number of objects identified:Continue Maximum number of objects:500 Use advanced settings?:Yes Threshold settings version:10 Threshold strategy:Global Thresholding method:Otsu Threshold smoothing scale:1.3488 Threshold correction factor:0.9 Lower and upper bounds on threshold:0.0,1.0 Manual threshold:0 Select the measurement to threshold with:None Two-class or three-class thresholding?:Two classes Assign pixels in the middle intensity class to the foreground or the background?:Foreground Size of adaptive window:500 Lower outlier fraction:0.05 Upper outlier fraction:0.05 Averaging method:Mean Variance method:Standard deviation # of deviations:2.0 Thresholding method:Otsu