Header shows Deep Learning Tool Icon

Labeling

Data labeling is an essential task for many Deep Learning projects. During labeling, the user adds the information to the system about how the problem is solved correctly. Depending on the method, this information can be image classes, object locations or pixel masks assigned to classes or instances.

Labeling for Object Detection

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

With object detection, labeling is done by drawing rectangles around each relevant object and assigning these rectangles to the corresponding classes. Depending on the project requirements, the user can label his data with either axis-parallel or oriented rectangles.

Labeling for Classification

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

Labeling for classification is done by simply importing the images and assigning them to a class. If the images are stored in appropriately named folders, they can also be labeled automatically during import.

Labeling for Segmentation: Polygons

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

Labeling for semantic segmentation and instance segmentation can be done by drawing polygonal regions around relevant objects.

Labeling for Segmentation: Pixel masks

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

Labeling for semantic segmentation and instance segmentation can also be done by painting pixel masks with brush and eraser that cover relevant objects.

Labeling for Segmentation: Smart Labeling

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

To greatly reduce labeling time and cost, a smart labeling tool can be used to benefit from label suggestions. 

Labeling for Deep OCR Training

Please note: Once you watch the video, data will be transmitted to Youtube/Google. For more information, see Google Privacy.

By retraining a Deep OCR model, the recognition rate of HALCON's Deep OCR can be increased even further. With the Deep Learning Tool, large data sets can be labeled very efficiently for this purpose - thanks to the automatic text suggestions of labeled words.