def run_OMR(inputPath, classifiersPath):
image, useAugmented = Preprocessing.read_and_preprocess_image(inputPath)
Processing = Pipeline.Augmented if useAugmented else Pipeline.Standard
Classifier.load_classifiers(classifiersPath)
image = Processing.remove_brace(image)
lineImage, staffDim = Processing.extract_staff_lines(image)
groups = Processing.split_bars(image, lineImage, staffDim)
output = []
for group in groups:
components, sanitized, staffDim, lineImage, dotBoxes = Processing.segment_image(
group)
Classifier.assign_components(sanitized, components, staffDim)
Processing.join_meters(components)
Processing.bind_accidentals_to_following_notes(components)
Processing.bind_dots_to_notes(components, dotBoxes)
Processing.assign_note_tones(components, sanitized, lineImage,
staffDim, group)
output.append(Display.get_guido_notation(components))
return output
