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Version: v0.3.0

Tutorial 2B: Annotation task: Image regression

Overview​

This tutorial annotates a dataset that enables you to understand the process of annotating and specifying an annotation task rubric for an image regression annotation task. To highlight the process, we are going to annotate a dataset that contains images of healthy and diseased apple leaves for plant pathology recognition. This tutorial also quickly explores how you can download the fully annotated dataset supported in H2O Hydrogen Torch.

Step 1: Explore dataset​

We are going to use the preloaded plant-pathology-demo demo dataset for this tutorial. The dataset contains 32 images depicting healthy and diseased apple leaves. Let's quickly explore the dataset.

  1. On the H2O Label Genie navigation menu, click Datasets.
  2. In the datasets table, click plant-pathology-demo.

Various diseased apple leaves

Step 2: Create an annotation task​

Now that we understand the dataset let's create an annotation task that enables you to annotate the dataset. An annotation task refers to the process of labeling data. For example, an image regression annotation task refers to assigning one continuous target label to each input image. Let's create an annotation task.

  1. Click New annotation task.
  2. In the Task name box, enter tutorial-2b.
  3. In the Task description box, enter Annotate a dataset containing images of healthy and diseased apple leaves.
  4. In the Select task list, select Regression.
  5. Click Create task.

Step 3: Specify annotation task rubric​

Before we can start annotating our dataset, we need to specify an annotation task rubric. An annotation task rubric refers to the labels (for example, object classes) you want to use when annotating a dataset. We are going to label each image on a scale between 0 to 9 to rank the severity of the plant disease. A 0 refers to the plant having the least disease severity, and 9 refers to the plant having the most disease severity.

  1. In the Data minimum value box, enter 0.
    • The Data minimum value value refers to the minimum value in your continuous values (digits ranging between 0 to 9)
  2. In the Data maximum value box, enter 9.
    • The Data maximum value value refers to the maximum value in your continuous values (digits ranging between 0 to 9)
  3. In the Data step size (interval) box, enter 1.
    • The Data step size (interval) value refers to the value the label range slider interval takes (the slider is utilized in step 4)
  4. Click Apply

Annotated image dataset with slider ranging from 0 to 9

Let's utilize the slider, not the picker, to annotate the samples. To enable the slider, consider the following instructions:

  1. In the Annotation selection list, select Slider.

Annotation task rubric configuration of Car and Coffee classes

Step 4: Annotate dataset​

Now that we have specified the annotation task rubric, let's annotate the dataset. In the Annotate tab, you can individually annotate each image in the dataset. Let's annotate the first image.

  1. In the Label slider, slide to 3. Annotated image dataset with slider selection at 3
  2. Click Save and next.
    Note
    • Save and next saves the annotated image
    • To skip an image to annotate later: Click Skip.
      • Skipped images reappear after all non-skipped images are annotated
    • To download all annotated samples so far, consider the following instructions:
      1. Click the Export tab.
      2. In the Export approved samples list, select Download ZIP.
        note

        H2O Label Genie downloads a zip file containing the annotated dataset in a format that is supported in H2O Hydrogen Torch. To learn more, see Downloaded dataset formats: Image regression.

Download annotated dataset​

After annotating all the images, you can download the dataset in a format that H2O Hydrogen Torch supports. Let's download the annotated dataset.

  1. In the Annotate tab, click Export approved samples. Notification of completed annotation task ready to export approved samples
  2. In the Export approved samples list, select Download ZIP.

Summary​

In this tutorial, we learned the process of annotating and specifying an annotation task rubric for an image regression annotation task. We also learned how to download a fully annotated dataset supported in H2O Hydrogen Torch.

Next​

To learn the process of annotating and specifying an annotation task rubric for other various annotation tasks in computer vision (CV), natural language processing (NLP), and audio, see Tutorials.

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