Model Panel
The Model panel provides a list of all the models you created and details about each model. You can also create new models here.
Click the Model tab on the Segmentation Trainer dialog to open the panel, shown below.
Model panel
A. Models list B. Model details C. Classes table
Models List
All available models — both trained and untrained — are listed in the top section of the Model panel.
Models list
Filter models… You can filter the list by state, category, the number of datasets or classes, engine, and working area to find a particular classifier. The filter options are shown below.
Model filters
New… Automatically creates a new model.
Delete… Deletes the selected model.
A number of additional options — Create New, Duplicate, Delete, and Reset — are available in the pop-up menu.
Pop-up menu
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Description |
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Create New |
Automatically creates a new model that includes the following files. You should note that all files in the model are saved in the root directory: Classifier files (*.classifier extension)… Stores the classifier summary and description. Dataset features presets files (*.datasetFeaturesPresets extension)… Stores the filters and settings for each dataset feature preset that is added to the model's features tree in a separate file. Engine file (*.engine extension)… Stores the selected classification engine. Region features presets files (*.regionFeaturesPresets extension)… Stores the filters and settings for each region feature preset that is added to the model's features tree in a separate file. |
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Duplicate |
Creates an untrained copy of the current classifier with the same inputs and features. Note The name of a classifier can be edited by double-clicking it in the list. |
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Delete |
Deletes the selected classifier. |
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Reset |
Restores the default engine parameters and lets you change the classifier engine or its parameters after a model has been trained. However, the classifier inputs and features will be retained. This will allow you to try different engines and parameters without duplicating the model. |
Model Details
Details about the selected model — category, description, summary, and author — are available in the bottom section of the Classifier panel, as shown below.
Details
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Description |
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Summary |
Indicates the current status of the classifier and lists the inputs, engine, and working area. You should note that some items are color coded to draw your attention to issues that may require attention. Issues that are currently blocking the workflow are colored red, while items colored yellow may require attention, but are not blocking the workflow. For example, Classes: (Not filled) will be colored in red if the engine is not trained since they are mandatory to train the engine. For trained engines, Classes: (Not filled) will appear in yellow since they are not mandatory for trained engines and can remain unfilled. Requirements… Indicates the current status of the classifier — Functional or Not Functional. State… Indicates the current state of the classifier— Trained or Not Trained. Datasets… Indicates the number of datasets required to run the segmentation workflow and if they are filled or not filled. Status can be Undefined for a new classifier, xx (Not Filled) for a trained classifier that does not have the required dataset input, and xx for a trained classifier with the required dataset input. Classes… Indicates the number of segmentation labels, or training classes, used to train the classifier and if they are filled or not filled. Not required when segmenting a dataset with a trained classifier. Status can be Undefined for a new classifier, xx (Not Filled) for a trained classifier that does not have any inputs, and xx for a trained classifier with the indicated segmentation label inputs. Histogram Matching… indicates if histogram matching is enabled or disabled. Features Tree… Indicates the status of the features tree — Ready or Not Ready. Algorithm… Lists the algorithm used by the classifier. Working Area… Indicates the working area selected for the classifier — Pixel, Region, or Pixel on Region. |
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Category |
Indicates the category to which you assigned the selected classifier — Biological, Demo, Experimental, Production, or Other. Note If required, you can create new categories by clicking the New button. |
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General documentation |
This optional field can be used to add additional information about the classifier. Provides input fields to add general information, such as the name or names of the classifier author, as well as their contact information, applicable copyrights, creation date, and version number. Note The general documentation fields are populated automatically from the information in your user profile (see Adding Your User Profile). |
Classes
Lists the classes in the selected model, as well as the color and name associated with each class.
Visible… If selected, the highlight applied to classified voxels will be shown.
Color… Determines the highlight color applied to classified voxels. If required, you can change the highlight color.
Name… Is the name assigned to the class label and the name that will appear in the output multi-ROI. If required, you can change the assigned name.
Classes
