Training a model uses a large number of labeled images. Therefore, label images before the model training. You can label images on the ModelArts management console. Alternatively, modify labels, or delete them and label them again.
Before labeling an image in image segmentation scenarios, pay attention to the following:
ModelArts automatically synchronizes data and labeling information from datasets to the labeling job.
To quickly obtain the latest data in a dataset, in the All statuses, Unlabeled, or Labeled tab of the labeling job details page, click Synchronize New Data.
In the All statuses, Unlabeled, or tab, click in the filter criteria area and add filter criteria to quickly filter the data you want to view.
The following filter criteria are available. You can set one or more filter criteria.
The labeling job details page displays the All statuses, Unlabeled, and Labeled tabs. The Unlabeled tab is displayed by default.
After you select a method to label the first image, the labeling method automatically applies to subsequent images.
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Polygon. In the area where the object to be labeled is located, click to label a point, move the mouse and click multiple points along the edge of the object, and then click the first point again. All the points form a polygon. In this way, the object to be labeled is within the bounding box. |
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Cancel the previous operation. |
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Redo the previous operation. |
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Zoom in an image. |
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Zoom out an image. |
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Delete all bounding boxes on the current image. |
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Show or hide a bounding box. This operation can be performed only on a labeled image. |
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Drag a bounding box to another position or drag the edge of the bounding box to resize it. |
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Reset a bounding box. After dragging a bounding box, you can click this button to quickly restore the bounding box to its original shape and position. |
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Display the labeled image in full screen. |
After labeling an image, click an image that has not been labeled in the image list below to label the new image.
The selected images are automatically moved to the Labeled tab. In the Unlabeled and All statuses tabs, the labeling information is updated along with the labeling process, including the added label names and the number of images for each label.
On the labeling job details page, click the Labeled tab to view the list of labeled images. Click an image to view its labeling information in the File Labels area on the right.
After labeling data, you can modify labeled data in the Labeled tab.
On the labeling details page, click the Labeled tab and then the image to be modified. On the displayed labeling page, modify the labeling information in the File Labels area on the right.
After the labeling information is modified, click Back to Data Labeling Preview in the upper left part of the page to exit the labeling page. In the displayed dialog box, click Yes to save the modification.
In addition to the data automatically synchronized from datasets, you can directly add images to labeling jobs for labeling. The added data is first imported to the dataset associated with the labeling job. Then, the labeling job automatically synchronizes the latest data from the dataset.
The images you have added will be automatically displayed in the image list in the All statuses tab. You can choose Add data > View historical records to view task history.
You can quickly delete the images you want to discard.
In the All statuses, Unlabeled, or Labeled tab, select the images to be deleted or click Select Images on Current Page, and click Delete in the upper left corner to delete them. In the displayed dialog box, select or deselect Delete the source files from OBS as required. After confirmation, click Yes to delete the images.
If a tick is displayed in the upper left corner of an image, the image is selected. If no image is selected on the page, the Delete button is unavailable.
If you select Delete the source files from OBS, images stored in the OBS directory will be deleted accordingly. This operation may affect other dataset versions or datasets using those files, for example, leading to an error in page display, training, or inference. Deleted data cannot be recovered. Exercise caution when performing this operation.