Create Automation Algorithm for Labeling - MATLAB & Simulink (original) (raw)
The Image Labeler,Video Labeler,Lidar Labeler (Lidar Toolbox), and Ground Truth Labeler (Automated Driving Toolbox) apps enable you to label ground truth for a variety of data sources. You can use an automation algorithm to automatically label your data by creating and importing a custom automation algorithm. You can also use a custom function that creates an automation algorithm. The function, which you can specify in the labeling apps, enables you to adjust the automation parameters. For more details, see Create Automation Algorithm Function for Labeling.
Create New Algorithm
The vision.labeler.AutomationAlgorithm class enables you to define a custom label automation algorithm for use in the labeling apps. You can use the class to define the interface used by the app to run an automation algorithm.
To define and use a custom automation algorithm, you must first define a class for your algorithm and save it to the appropriate folder.
Define Class That Inherits from AutomationAlgorithm Class
At the MATLAB® command prompt, enter the appropriate command to open the labeling app:
imageLabelervideoLabelerlidarLabelergroundTruthLabeler
Then, load a data source, create at least one label definition, and on the app toolstrip, select > > . In the vision.labeler.AutomationAlgorithm class template that opens, define your custom automation algorithm. Follow the instructions in the header and comments in the class.
If the algorithm is_time-dependent_, that is, has a dependence on the timestamp of execution, your custom automation algorithm must also inherit from thevision.labeler.mixin.Temporal class. For more details on implementing time-dependent, or temporal, algorithms, see Temporal Automation Algorithms.
If the algorithm is blocked image based, your custom automation algorithm must also inherit from the vision.labeler.mixin.BlockedImageAutomation class. For more details on implementing blocked image algorithms, see Blocked Image Automation Algorithms.
Create Automation Folder
Create a +vision/+labeler/ folder within a folder that is on the MATLAB path. For example, if the folder /local/MyProject is on the MATLAB path, then create the +vision/+labeler/ folder hierarchy as follows:
projectFolder = fullfile('local','MyProject'); automationFolder = fullfile('+vision','+labeler'); mkdir(projectFolder,automationFolder)
The resulting folder is located at /local/MyProject/+vision/+labeler.
Save Class File to Automation Folder
To use your custom algorithm from within the labeling app, save the file to the +vision/+labeler folder that you created. Make sure that this folder is on the MATLAB search path. To add a folder to the path, use the addpath function.
Refresh Algorithm List in Labeling App
To start using your custom algorithm, refresh the algorithm list so that the algorithm displays in the app. On the app toolstrip, select > .
Import Existing Algorithm
To import an existing custom algorithm into a labeling app, on the app toolstrip, select > > and then refresh the list.
Custom Algorithm Execution
When you run an automation session in a labeling app, the properties and methods in your automation algorithm class control the behavior of the app.
Check Label Definitions
When you click Automate, the app checks each label definition in the ROI Labels andScene Labels panes by using the checkLabelDefinition method defined in your custom algorithm. Label definitions that return true are retained for automation. Label definitions that return false are disabled and not included. Use this method to choose a subset of label definitions that are valid for your custom algorithm. For example, if your custom algorithm is a semantic segmentation algorithm, use this method to return false for label definitions that are not of type PixelLabel.
Control Settings
After you select the algorithm, clickAutomate to start an automation session. Then, clickSettings, which enables you to modify custom app settings. To control the Settings options, use the settingsDialog method.
Control Algorithm Execution
When you open an automation algorithm session in the app and then clickRun, the app calls the checkSetup method to check if it is ready for execution. If the method returnsfalse, the app does not execute the automation algorithm. If the method returns true, the app calls theinitialize method and then the run method on every frame selected for automation. Then, at the end of the automation run, the app calls the terminate method.
The diagram shows this flow of execution for the labeling apps.
- Use the checkSetup method to check whether all conditions needed for your custom algorithm are set up correctly. For example, before running the algorithm, check that the scene contains at least one ROI label.
- Use the initialize method to initialize the state for your custom algorithm by using the frame.
- Use the run method to implement the core of the algorithm that computes and returns labels for each frame.
- Use the terminate method to clean up or terminate the state of the automation algorithm after the algorithm runs.
See Also
Apps
- Video Labeler | Image Labeler | Ground Truth Labeler (Automated Driving Toolbox) | Lidar Labeler (Lidar Toolbox)
Functions
- vision.labeler.AutomationAlgorithm | vision.labeler.mixin.Temporal | vision.labeler.mixin.BlockedImageAutomation
See Also
Topics
- Automate Ground Truth Labeling of Lane Boundaries (Automated Driving Toolbox)
- Automate Ground Truth Labeling for Semantic Segmentation (Automated Driving Toolbox)
- Automate Attributes of Labeled Objects (Automated Driving Toolbox)