def find_lines(image, projection=True, horizontal_opening=True):
"""Recognize staff lines on image and return them
as a list of lists of lists of row numbers,
distances between them and average staff spacing.
:param image:
:param projection:
:param horizontal_opening:
"""
first = None
second = None
if projection:
first = get_white_rows(imo.crop_image(
imo.project_image(image)))
if horizontal_opening:
if projection:
line_distances = group_rows(first)[1]
avg_staff_spacing = []
for staff_line_distances in line_distances:
avg_staff_spacing += staff_line_distances
avg_staff_spacing = sum(avg_staff_spacing) * 1. / len(avg_staff_spacing)
second = get_white_rows(imo.open_image(image, np.ones((1, 2 * avg_staff_spacing))))
else:
second = get_white_rows(imo.open_image(image, np.ones((1, 20))))
if projection and horizontal_opening:
image_lines = intersect_lists(first, second)
elif projection:
image_lines = first
elif horizontal_opening:
image_lines = second
else:
raise Exception("To find lines either horizontal projection"
"of the image must be done or a horizontal"
"morphological opening")
lines, line_distances, staff_distances = \
group_rows(image_lines)
avg_staff_spacing = []
for staff_line_distances in line_distances:
avg_staff_spacing += staff_line_distances
avg_staff_spacing = sum(avg_staff_spacing) * 1. / len(avg_staff_spacing)
if len(staff_distances) > 0:
avg_staff_distance = sum(staff_distances) * 1. / len(staff_distances)
else:
avg_staff_distance = 0
return lines, line_distances, avg_staff_spacing, staff_distances, avg_staff_distance
def open_image(image, kernel=None):
return imo.open_image(image, kernel)
