A description of the second MAIA stage.
When one of your MAIA jobs proceeds from novelty detection to the training proposals stage, you will get a notification from BIIGLE. In this stage, the MAIA job requires manual interaction from you before it can proceed to the next stage. This is done in two steps, the selection of training proposals and the refinement of training proposals.
To begin the selection of training proposals, open the select training proposals tab in the sidebar. This will load and display all training proposals that were generated by the novelty detection or from your existing annotations. For each training proposal an image thumbnail is shown in a regular grid.
Your task in this step is to review all training proposals and select each one that shows (part of) an interesting object or image region with a click on the thumbnail.
The regular grid of image thumbnails is specifically designed for you to be able to review a large amount of training proposals very quickly. The following keyboard shortcuts are available to navigate the grid:
||Move up one page|
||Move down one page|
||Move up one row|
||Move down one row|
||Move up to the first row|
||Move down to the last row|
We recommend you to use the keyboard shortcuts to move through the image grid page by page and the mouse to select the interesting training proposals. To quickly select multiple adjacent training proposals in the grid, select the first one and then hold the
Shift key while selecting the last one. This will select all training proposals between the first and the last selected one.
Please note that the quality of annotation candidates directly depends on the number of selected training proposals. In some cases a few hundred may be sufficient, in other cases many more might be required.
When you are finished with the selection of interesting training proposals, continue to the refinement step.
To continue to the refinement of training proposals, click on the button in the select training proposals tab or directly open the refine training proposals tab in the sidebar. This will display the training proposals directly on the images, similar to what you are used to from the annotation tool.
The refinement tool is designed to guide you quickly through all selected training proposals. The current selected training proposal is shown at the center and highlighted with a red circle. Other selected training proposals on the same image are displayed as blue circles. Other unselected training proposals are shown as semitransparent dashed circles.
Your task in this step is to modify the position and size of the circle of each selected training proposal so it closely fits to the interesting object or image region. To move a circle, click and hold the center point of the circle with the mouse, then move the mouse so the circle is moved to the new position and finally release the mouse button. To resize a circle, click, hold and move the border of the circle, and release the mouse button once the circle has the correct size.
When you are finished with the refinement of one selected training proposal, continue to the next one with a click on the button, or the
Arrow right shortcut keys. You can track your progress through all selected training proposals in the sidebar. It will tell you when have "seen" all selected training proposals.
If you notice an interesting training proposal which has not been selected yet, you can select it directly in the refinement tool. First, click on the button at the bottom and then click on the dashed circle of the unselected training proposal.
You can finish the training proposals stage at any time with a click on the button in the refine training proposals tab. Although we recommend you to review all training proposals in the select step and refine all training proposals in the refinement step, this is not a requirement for the submission of the selected training proposals. Training proposals can no longer be selected or modified once they have been submitted.
When the training proposals have been submitted, the MAIA job automatically proceeds to the instance segmentation stage.