iDS NXT Ocean: A simplified Artificial Intelligence workflow experience

The first step in this process is to open iDS NXT Lighthouse in a web browser and then proceed to log-in. As seen below, the NXT Lighthouse platform has a simple-to-follow interface.

The next step is to open the "data sets" section in the top left hand corner of the screen. In this section users can add new image data for training and can view any existing data sets. To create a new data set, you click on the large "+" icon. When here users can enter a text title for the data set, a brief description of the data set as well as add a thumbnail image from a PC's local drive.

Next, click on the "image data" tab where images that have been acquired can be added to a data set. Users will then click "add", then "add folders" and then we click "add" again on the resulting dialogue. When here users can navigate to the folder on the PC that contains the images needed for the intended data set. Users will then see a preview of the images. After you choose the appropriate labeling, click upload to complete the process.

For object classification with the iDS NXT all that is required of users is for data sets to be created and images to be uploaded and then appropriately labeled. Similarly for object detection users will need to add labels to specific regions within the image. In some cases - you can use the same data sets for object classification and object detection. In this editorial we will give an example on how to label for detection. Labeling for classification is even simpler.


The first step of labeling for object detection, is to create the bounding box annotation which is used to draw around each of the objects in the images. By clicking on the first image in the data set you see the full image, as well as a new toolbar on the right of the screen for annotations. It's here that users should now expand the boxes section, choose a colour, give the box a name to reflect the object class and click the "add" button. This box is now available as a template for the object detection annotation process. Now users can draw boxes around each instance of the detection class in the image and when all of the objects in the image are annotated click "save" and "next" to proceed to the next image. If dealing with multiple detection classes the NXT Lighthouse platform allows users to add subsequent boxes with different colours and labels.

Once users have completed the labeling process iDS Lighthouse displays statistics on the number of images in the data set and the number of instances of an object. To conclude the process, the last tab on the "display annotations" provides an overview of all of the labels, box names and layouts associated with this data set allowing users to edit as required.

And just like that, the process of labeling and making annotations for classification or object detection is complete.