Load Data Programmatically

This code programmatically loads images of book covers from a datastore:

To programmatically load a folder of images:

imageFolder = fullfile(toolboxdir("vision"),"visiondata","bookcovers")
imageLabeler(imageFolder)

Load Data Directly from the App

In this example, you load an image interactively from the app. To start, open the app from the Apps tab, under Image Processing and Computer Vision. Click Import to load images from a file or from a datastore in the workspace.

To load the image used for this example, click Import and then select From File. Select the boats.png image:

matlab/toolbox/vision/visiondata/boats.png

Create ROI Label

An ROI label is a label that corresponds to a region of interest (ROI) in an image. You can define these ROI label types.

For more details about these ROI label definitions, see ROI Labels, Sublabels, and Attributes.

In this example, you define a Boat group for labeling types of boats, and then create a Rectangle ROI label for a Sailboat and a Tanker. To control showing the ROI label names during labeling, select On Hover, Always, or Never from the Show ROI Labels drop-down menu.

Create Sublabels

A sublabel is a type of ROI label that corresponds to a parent ROI label. Each sublabel must belong to, or be a child of, a specific label defined in the ROI Labels pane. For example, in the ocean scene, a sailboat label might have sublabels for sails. For more details about sublabels, see ROI Labels, Sublabels, and Attributes.

Define a sublabel for sails.

Sublabels cannot have their own sublabels and they can be used with all ROI label types with the exception of pixel labels. Notice that the Labels, Sublabels, and Attributes pane provides a tally and stacking order for the created labels.

Show or Hide Labels and Sublabels

You can show or hide the labels or sublabels in a labeled image by using the icon on the ROI Labels pane. The appears only after you define a label or sublabel. By default, the app displays all the labels and the sublabels.

To hide a label or sublabel, click on the icon along side the label or sublabel name. The app hides the corresponding label or sublabel and displays the icon.

Create ROI Attribute

An ROI attribute specifies additional information about an ROI label or sublabel. For example, in a driving scene, attributes might include the type or color of a vehicle. In the ocean scene, attributes might include the type of sailboat or number of sails. You can define ROI attributes of these types.

For more details about these attribute types, see ROI Labels, Sublabels, and Attributes.

Add an attribute to a Label.

You can also add attributes to sublabels. For example, in this example you could an attribute for the sail sublabel to indicate whether it is a foresail or a mainsail. Or, in this step, a logical attribute is added to indicate whether the sail is raised.

To delete an attribute, right-click an ROI label or sublabel, and select the attribute to delete. Deleting the attribute removes attribute information from all previously created ROI label annotations.

Create Scene Labels

A scene label defines additional information for the scene. Use scene labels to describe conditions, such as lighting, weather, or events, such as lane changes or point of sail.

Create a scene label:

Label Ground Truth Manually

The ROI and Scene labels are defined for your entire session and for all of the images in the session. Unless you use an automation algorithm, you must label all the relevant images.

Label Ground Truth Using an Automation Algorithm

To speed up the labeling process, you can use an automation algorithm to label the remainder of your images. Select one of these types of automation algorithms from the app toolstrip Automate Labeling > Select Algorithm section.

After using an automation algorithm you can manually label the remaining frames with sublabel and attribute information.

To further evaluate your labels, you can view a visual summary of the labeled images. The Visual Summary information appears below the image pane of the app. Use this summary to compare the frames, frequency of labels, and scene conditions. For more details, see View Summary of ROI and Scene Labels. This summary does not show sublabels or attributes.

Data Source

DataSource is a groundTruthDataSource object containing the path to the images or video and timestamps. Display the properties of this object.

gTruth.DataSource

ans = 

groundTruthDataSource for a video file with properties

        Source: ...matlab\toolbox\vision\visiondata\visiontraffic.avi
    TimeStamps: [531×1 duration]

Label Definitions

LabelDefinitions is a table containing information about the label definitions. This table does not contain information about the labels that are drawn on the video frames. To save the label definitions in their own MAT-file, from the app toolstrip, select Save > Label Definitions. You can then import these label definitions into another app session by selecting Import Files.

Display the label definitions table. Each row contains information about an ROI label definition or a scene label definition. If you exported pixel label data, the LabelDefinitions table also includes a PixelLabelID column containing the ID numbers for each pixel label definition.

gTruth.LabelDefinitions

ans =
  3×6 table

      Name         Type        LabelColor        Group       Description     Hierarchy  
    _________    _________    ____________    ___________    ___________    ____________

    {'Car'  }    Rectangle    {1×3 double}    {'Vehicle'}    {0×0 char}     {1×1 struct}
    {'Truck'}    Rectangle    {1×3 double}    {'Vehicle'}    {0×0 char}     {0×0 double}
    {'Sunny'}    Scene        {1×3 double}    {'Weather'}    {0×0 char}     {0×0 double} 

Within LabelDefinitions, the Hierarchy column stores information about the sublabel and attribute definitions of a parent ROI label.

Display the sublabel and attribute information for the Car label.

gTruth.LabelDefinitions.Hierarchy{1}

ans = 

  struct with fields:
       numDoors: [1×1 struct]
          color: [1×1 struct]
       inMotion: [1×1 struct]
        carType: [1×1 struct]
      headlight: [1×1 struct]
           Type: Rectangle
    Description: ''

Display information about the headlight sublabel.

gTruth.LabelDefinitions.Hierarchy{1}.headlight

ans = 

  struct with fields:
           Type: Rectangle
    Description: ''
          Color: [0.5862 0.8276 0.3103]
           isOn: [1×1 struct]

Display information about the carType attribute.

gTruth.LabelDefinitions.Hierarchy{1}.carType

ans = 

  struct with fields:

      ListItems: {3×1 cell}
    Description: ''

Save App Session in a Team-based Project

Sessions are saved in each step of a team-based project. For more information about each of these steps, see Get Started with Team-Based Labeling.

Save App Session as an Individual Project

From the app toolstrip, select Save Project then Save asto save a MAT-file of the app session. The saved session includes the data source, label definitions, and labeled ground truth. It also includes your session preferences, such as the layout of the app. To change layout options, select Layout.

At any time during a session, you can select New Session to start a new session. You have the option of saving the current session or cancelling.

The app session MAT-file is separate from the ground truth MAT-file that is exported when you select Export. To share labeled ground truth data, as a best practice, share the ground truth MAT-file containing the groundTruth object, not the app session MAT-file. For more details, see Share and Store Labeled Ground Truth Data.