UI Tools

Interaction with the OMR engine

The OMR engine works as a sequence of 20 sheet steps, a step being a kind of mini-batch.
You, as an interacting user, can get in only at the end of a step.
[When a sheet first appears with its Data tab, the OMR engine has already performed the LOAD and BINARY steps.]

Following any user manual action, OMR data is immediately updated depending on the impacted steps, the sheet view is updated to reflect the new status of OMR elements directly or indirectly modified, and also to indicate any “abnormal” situations detected on-the-fly by the OMR engine.

For example, a black note head with no compatible stem nearby, or vice versa a stem with no linked note head, will appear in red. Such a situation can happen temporarily while items are being manually created or edited, one after the other.
Similarly, a whole measure may have its background colored in pink to signal a rhythm problem.

Tasks

Task sequence

Whenever you modify an entity in some way, this task is recorded as such, perhaps with some joint tasks, into a “task sequence” which is then performed on the targeted entities.

A task sequence can be pretty large. For example:

You can select a dozen inters and ask for the removal of the whole set.
You can remove an inter ensemble; this triggers the removal of all the members of the ensemble: words of a sentence, heads of a head-chord, etc.
Removing the last remaining member of an ensemble also removes the now-empty ensemble.

A task sequence is indivisible, but you can do it, undo and redo it at will, with no limits. Only moving the engine forward (or pseudo backward) from one step to another clears the user task history.

Undo

Undo cancels the last task sequence (whether it was a do or a redo) with all its consequences.

Press the Undo button on the tool bar,
Or type Ctrl+Z (Command+Z for MacOS)

Redo

Redo re-performs the last un-done task sequence.

Press the Redo button on the tool bar,
Or type Ctrl+Shift+Z (Command+Shift+Z for MacOS).

When to interact?

Most user corrections can be done at the end of a sheet transcription (at the final PAGE step of the engine pipeline).

Some corrections are more effective at earlier moments; experience will tell you.
Here are interesting stopping points, presented in chronological order:

SCALE step is an interesting stop if the beams are questionable.
That is, if you get a message saying that the beam thickness value is just “extrapolated”, be careful! This tells you that beam-related data could not reach the quorum needed to infer a reliable thickness value.
So, measure the actual beam thickness by yourself (using the Pixel Board) and modify the beam scale if needed (see the Sheet scale section).
GRID step is where staff lines, then staves and systems are detected.
Hence, this is the most convenient point to interact if you need to manually modify lines and staves (see the Staff editing section).
REDUCTION step is where all candidate note heads are combined with candidate stems and beams and then reduced to come up with reliable notes (this does not include any flag or rest, which are addressed later in the SYMBOLS step).
It is a key moment in the engine pipeline, because these “reliable” notes will never be called into question by the following steps. So much so that their underlying pixels will not be presented to the glyph classifier during the SYMBOLS step. This includes a “dilation” margin ring around each note head, something that the user cannot select as a glyph in any subsequent selection.
So, if some of these notes are false positives, then it’s much more efficient to correct them immediately, at the end of the REDUCTION step.
TEXTS step is another key moment.
It aims at retrieving all the textual items in the image and assigning them a role (such as title, part name, lyrics). The engine output for the TEXT step depends heavily on an external program (Tesseract OCR) which Audiveris has little control upon. It is hard for the OMR engine to decide if an item is really a piece of text, or if it should also be considered as a possible music symbol.
Thus, it is efficient to manually remove text false positives at the end of this TEXT step to let their pixels be taken into account by the SYMBOLS step.
PAGE step is where the OMR engine ends on a sheet and where you can observe and correct the final results.