def __call__(self, binarization):
# border removal
from gamera.toolkits.lyric_extraction.plugins.sample_histogram import sample_hist
mask = border_removal(win_dil=3, win_avg=5, win_med=5,
threshold1_scale=0.8, threshold1_gradient=6.0,
threshold2_scale=0.8, threshold2_gradient=6.0,
scale_length=0.25,
terminate_time1=15, terminate_time2=23, terminate_time3=75,
interval2=45, interval3=15)
# binarization
img_bw_staff0 = binarization(mask, sample_hist, do_wiener=1, wiener_width=5, wiener_height=3, noise_variance=-1.0,
med_size=17,
region_size=15, sensitivity=0.5, dynamic_range=128, lower_bound=20, upper_bound=150,
q=0.06, p1=0.7, p2=0.5)
img_bw_staff = img_bw_staff0.correct_rotation(0)
# staff removal
staffspace = img_bw_staff.staffspace_estimation(staff_win=30, staffspace_threshold1=5, staffspace_threshold2=10)
staffheight = img_bw_staff.staffheight_estimation(staff_win=30, staffspace_threshold1=5, staffspace_threshold2=10)
img_nostaff = binarization.staff_removal(staffspace, staffheight, scalar_med_width_staffspace=0.15, scalar_med_height_staffspace=0.6,
scalar_med_width_staffheight=1.2, scalar_med_height_staffheight=5.0,
neighbour_width=1, neighbour_height=1,
staff_win=30, staffspace_threshold1=5, staffspace_threshold2=10)
# lyricline detection
return img_nostaff.lyric_line_detection(staffspace, threshold_noise=15, scalar_cc_strip=1.0,
seg_angle_degree=30.0, scalar_seg_dist=3.5, min_group=4,
merge_angle_degree=5.0, scalar_merge_dist=5.0,
valid_angle_degree=20.0, scalar_valid_height=1.0, valid_min_group=8,
scalar_height=3.0,
fit_angle_degree=2.5, scalar_search_height=1.2,
scalar_fit_up=1.2, scalar_fit_down=0.3)
def __call__(self):
# border removal
from gamera.toolkits.lyric_extraction.plugins.sample_histogram import sample_hist
mask = border_removal(win_dil=3, win_avg=5, win_med=5,
threshold1_scale=0.8, threshold1_gradient=6.0,
threshold2_scale=0.8, threshold2_gradient=6.0,
scale_length=0.25,
terminate_time1=15, terminate_time2=23, terminate_time3=75,
interval2=45, interval3=15)
# binarization
img_bw0 = binarization(mask, sample_hist, do_wiener=0, wiener_width=5, wiener_height=3, noise_variance=-1.0,
med_size=17,
region_size=15, sensitivity=0.5, dynamic_range=128, lower_bound=20, upper_bound=150,
q=0.06, p1=0.7, p2=0.5)
img_bw = img_bw0.correct_rotation(0)
return img_bw
