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return_deskew_slop: no >90° search unless for full page, simplify

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Robert Sachunsky 2026-05-01 00:27:00 +02:00
parent cbb3be0e01
commit 29bb55ceff
1 changed files with 28 additions and 38 deletions
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66
src/eynollah/utils/separate_lines.py
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@ -1490,63 +1490,53 @@ def do_image_rotation(angle, img=None, sigma_des=1.0, logger=None):
var = 0
return var
def return_deskew_slop(img_patch_org, sigma_des,n_tot_angles=100,
main_page=False, logger=None, plotter=None, name=None):
def return_deskew_slop(img,
sigma_des,
n_tot_angles=100,
main_page=False,
logger=None,
plotter=None,
name=None):
if main_page and plotter:
plotter.save_plot_of_textline_density(img_patch_org, name)
img_int=np.zeros((img_patch_org.shape[0],img_patch_org.shape[1]))
img_int[:,:]=img_patch_org[:,:]#img_patch_org[:,:,0]
plotter.save_plot_of_textline_density(img, name)
max_shape=np.max(img_int.shape)
img_resized=np.zeros((int( max_shape*(1.1) ) , int( max_shape*(1.1) ) ))
height, width = img.shape[:2]
max_shape = int(np.max(img.shape) * 1.1)
onset_x=int((img_resized.shape[1]-img_int.shape[1])/2.)
onset_y=int((img_resized.shape[0]-img_int.shape[0])/2.)
onset_x = int(0.5 * (max_shape - width))
onset_y = int(0.5 * (max_shape - height))
#img_resized=np.zeros((int( img_int.shape[0]*(1.8) ) , int( img_int.shape[1]*(2.6) ) ))
#img_resized[ int( img_int.shape[0]*(.4)):int( img_int.shape[0]*(.4))+img_int.shape[0],
# int( img_int.shape[1]*(.8)):int( img_int.shape[1]*(.8))+img_int.shape[1] ]=img_int[:,:]
img_resized[ onset_y:onset_y+img_int.shape[0] , onset_x:onset_x+img_int.shape[1] ]=img_int[:,:]
img_resized = np.zeros((max_shape, max_shape))
img_resized[onset_y: onset_y + height,
onset_x: onset_x + width] = img
if main_page and img_patch_org.shape[1] > img_patch_org.shape[0]:
def best_angle(angles):
return get_smallest_skew(img_resized, sigma_des, angles,
logger=logger,
name=name,
plotter=plotter)
if main_page and width > height:
angles = np.array([-45, 0, 45, 90,])
angle, _ = get_smallest_skew(img_resized, sigma_des, angles, logger=logger, name=name, plotter=plotter)
angle, _ = best_angle(angles)
angles = np.linspace(angle - 22.5, angle + 22.5, n_tot_angles)
angle, _ = get_smallest_skew(img_resized, sigma_des, angles, logger=logger, name=name, plotter=plotter)
angle, _ = best_angle(sigma_des)
elif main_page:
#angles = np.linspace(-12, 12, n_tot_angles)#np.array([0 , 45 , 90 , -45])
angles = np.concatenate((np.linspace(-12, -7, n_tot_angles // 4),
np.linspace(-6, 6, n_tot_angles // 2),
np.linspace(7, 12, n_tot_angles // 4)))
angle, var = get_smallest_skew(img_resized, sigma_des, angles, logger=logger, name=name, plotter=plotter)
angle, var = best_angle(angles)
early_slope_edge=11
if abs(angle) > early_slope_edge:
if angle < 0:
angles2 = np.linspace(-90, -12, n_tot_angles)
else:
angles2 = np.linspace(90, 12, n_tot_angles)
angle2, var2 = get_smallest_skew(img_resized, sigma_des, angles2, logger=logger, name=name, plotter=plotter)
if var2 > var:
angle = angle2
else:
angles = np.linspace(-25, 25, int(0.5 * n_tot_angles) + 10)
angle, var = get_smallest_skew(img_resized, sigma_des, angles, logger=logger, name=name, plotter=plotter)
angle, var = best_angle(angles)
early_slope_edge=22
if abs(angle) > early_slope_edge:
if angle < 0:
angles2 = np.linspace(-90, -25, int(0.5 * n_tot_angles) + 10)
else:
angles2 = np.linspace(90, 25, int(0.5 * n_tot_angles) + 10)
angle2, var2 = get_smallest_skew(img_resized, sigma_des, angles2, logger=logger, name=name, plotter=plotter)
if var2 > var:
angle = angle2
# precision stage:
angles = np.linspace(angle - 2.5, angle + 2.5, n_tot_angles // 2)
angle, _ = get_smallest_skew(img_resized, sigma_des, angles, logger=logger, name=name, plotter=plotter)
angle, _ = best_angle(angles)
return angle
def get_smallest_skew(img, sigma_des, angles, logger=None, plotter=None, name=None):