Label using the Google Cloud Console

For text, image, and video data, you can import data that has not yet been labeled and use the Cloud Console to add labels to this data. To import your data, use either a JSON or CSV file which specifies the location of the video files. Note: A header is not required in the CSV file.

Also, you can delete or add labels to existing datasets that have been labeled, previously. Note: You can always request to have human labelers add labels to the data items.

After creating the dataset and importing the unlabeled data, you will be in Browse mode.

browse mode

How to add labels

Instructions for labeling objectives are provided here for each data type.

Image

The images you have just imported in the dataset are unlabeled, as expected.

Classification

When in Browse mode, and the dataset with the unlabeled images is selected, you can see your uploaded images.

  1. Click Add new label and enter your new label.
  2. Click Done.
    Repeat for each label you want to add.
  3. Select the image you want to label.
    The list of labels appears.
  4. Select the label you want to associate with the image.
  5. Click Save.

Classification

When in Browse mode, and the dataset with the unlabeled images is selected, you can see your uploaded images.

  1. Click Add new label and enter your new label.
  2. Click Done.
    Repeat for each label you want to add.
  3. Select the image you want to label.
    The list of labels appears.
  4. Select the label you want to associate with the image.
  5. Click Save.
  6. You can view the labels applied to each image in the Browse tab. multi-labeled images

Object detection

When in Browse mode, and the dataset with the unlabeled images is selected, you can see your uploaded images.

  1. Click Add new label and enter your new label.
  2. Click Done.
    Repeat for each label you want to add.
  3. Select the image you want to label.
  4. The list of labels objects appears, if there are any.
  5. In the add annotation window, select the Add bounding box button to add an object bounding box to the image.
    add bounding box to image
  6. After drawing a bounding box, a list of labels to apply to the object will appear. Choose the appropriate label.
    add label bounding boxed image
  7. After you have added all labels and bounding boxes, click Save to update the image's annotations.
    save added labels for bounding boxed image

Text

The text you have just imported in the dataset may or may not be labeled.

Single-label classification

  1. Click the text to label.
  2. To add a new label, click Add label.
  3. For a single-label classification dataset, select one label to associate with the text.
  4. Click Save.

Multi-label classification

  1. Click the text to label.
  2. To add a new label, click Add label.
  3. For multi-label classification datasets, select one or more labels to associate with the text.
  4. Click Save.

Entity extraction

  1. Click the text to label.
  2. To add a new label, click Add label.
  3. Select one or more words to label.
  4. Select a label to associate with the selected text.
  5. Click Save.

Sentiment analysis

  1. Click the text to label.
  2. To add a new label, click Add label.
  3. Select a score to associate with the text.
  4. Click Save.

Video

The videos you have just imported in the dataset are unlabeled, as expected.

  1. To navigate to your new dataset, click "Datasets" in the left nav.
    getting to your datasets
  2. Select the dataset you want to add labels to.
    Dataset appears.

Action recognition

When in Browse mode, and the dataset with the unlabeled videos is selected, you should see your videos.

  1. Add label(s).
    unlabeled videos
  2. Select a video and start viewing.
  3. When the action starts appearing that you want to identify, slowly progress through till you find the center or the most representative moment of the action using "Next frame" option. next frame option
  4. Click Add annotation.
    Your list of labels appears.
  5. Select the label you want for this video segment.
  6. Click Save.

Classification

When the dataset with the unlabeled videos is selected, you will see your videos.
dataset appears with unlabeled
        videos

  1. Add labels.
    dataset appears with unlabeled
        videos
  2. Select the video you want to label. The video appears with your list of color-coded labels below. select segment
  3. Navigate to starting point of segment. Click Add segment.
    1. Select segment. Adjust to designate the segment to be used for training for your particular label:
      select segment
    2. Select label. You can select multiple labels for a segment.
    3. Click Done, then Save.
    4. Repeat steps to add another label to the same video with a different time segment. Here's an example of where two more labels were added:
      dataset appears multi
            labels
  4. Return to Datasets list to repeat.

Object tracking

When in BROWSE mode, and the dataset with the unlabeled videos is selected, you should see your videos.
unlabeled videos

  1. Click Add Label and add the labels you plan to use (for example, "sedan", "pickup", "SUV", etc.).
  2. Click Save. If you need to add more labels later, click Add new label and Save.
  3. Select a video and start viewing.
  4. When an object appears that you want to track,
    1. Stop the video.
    2. Drag a bounding box from the upper left corner, down to the lower right corner. Be sure to make the box as tight as possible around the object.
      A list of labels appears to the lower right-hand side of the bounding box.
    3. Select the appropriate label.
      unlabeled videos Note: Note: You can always add more labels during this process. Be sure to save the added label so it shows up in the list going forward.
    4. Click Save.

What's next