def crop(im, bw, split=True):
im_h, im_w = im.shape[:2]
all_letters = algorithm.all_letters(bw)
AH = algorithm.dominant_char_height(bw, letters=all_letters)
letters = algorithm.filter_size(AH, bw, letters=all_letters)
all_lines = collate.collate_lines(AH, letters)
combined = algorithm.combine_underlined(AH, bw, all_lines, all_letters)
lines = algorithm.remove_stroke_outliers(bw, combined)
if not lines:
print('WARNING: no lines in image.')
return AH, []
lines = filter_position(AH, bw, lines, split)
lines = [
line for line in lines if not np.all(line.crop().apply(bw) == 255)
]
if not lines:
print('WARNING: eliminated all lines.')
return AH, []
if split and im_w > im_h: # two pages
line_sets = split_lines(lines)
else:
line_sets = [lines]
return AH, line_sets
def get_AH_lines(im):
all_letters = algorithm.all_letters(im)
# AH == average character height
AH = algorithm.dominant_char_height(im, letters=all_letters)
if lib.debug: print('AH =', AH)
letters = algorithm.filter_size(AH, im, letters=all_letters)
all_lines = collate.collate_lines(AH, letters)
# From up to down
all_lines.sort(key=lambda l: l[0].y)
combined = algorithm.combine_underlined(AH, im, all_lines, all_letters)
filtered = algorithm.remove_stroke_outliers(im, combined, k=2.0)
# filtered = algorithm.filter_spacing_deviation(im, AH, filtered)
lines = remove_outliers(im, AH, filtered)
# lines = combined
# if lib.debug:
# debug = cv2.cvtColor(bw, cv2.COLOR_GRAY2BGR)
# for l in all_lines:
# for l1, l2 in zip(l, l[1:]):
# cv2.line(debug, tuple(l1.base_point().astype(int)),
# tuple(l2.base_point().astype(int)), RED, 2)
# lib.debug_imwrite('all_lines.png', debug)
return AH, lines, all_lines
def ntirogiannis2014(im):
lib.debug_prefix.append('ng2014')
debug_imwrite('input.png', im)
im_h, _ = im.shape
N, BG_prime = ng2014_normalize(im)
O = otsu(N)
debug_imwrite('O.png', O)
letters = algorithm.all_letters(O)
height_map = HeightMap(letters)
ratio_sum = 0
for h in range(1, height_map.max_height() + 1):
if len(height_map[h]) == 0: continue
ratio_sum += height_map.ratio_pixels(h) / height_map.ratio_components(
h)
if ratio_sum > 1:
break
min_height = h
if lib.debug: print('Accept components only >= height', h)
OP = O.copy()
for h in range(1, min_height):
for letter in height_map[h]:
sliced = letter.slice(OP)
np.place(sliced, letter.raster(), 255)
debug_imwrite('OP.png', OP)
strokes = fast_stroke_width(OP)
debug_imwrite('strokes.png', normalize_u8(strokes.clip(0, 10)))
SW = int(round(strokes.sum() / np.count_nonzero(strokes)))
if lib.debug: print('SW =', SW)
S = skeleton(OP)
debug_imwrite('S.png', S)
S_inv = ~S
# S_inv_32 = S_inv.astype(np.int32)
# FG_count = np.count_nonzero(S_inv)
FG_pos = im[S_inv.astype(bool)]
FG_avg = FG_pos.mean()
FG_std = FG_pos.std()
# FG = (S_inv & im).astype(np.int32)
# FG_avg = FG.sum() / float(FG_count)
# FG_std = np.sqrt(((S_inv_32 & (FG - FG_avg)) ** 2).sum() / float(FG_count))
if lib.debug: print('FG:', FG_avg, FG_std)
BG_avg = BG_prime.mean()
BG_std = BG_prime.std()
if lib.debug: print('BG:', BG_avg, BG_std)
if FG_avg + FG_std != 0:
C = -50 * np.log10((FG_avg + FG_std) / (BG_avg - BG_std))
k = -0.2 - 0.1 * C / 10
else: # This is the extreme case when the FG is 100% black, check the article explaination page before equation 5
C = -50 * np.log10((2.5) / (BG_avg - BG_std))
k = -0.2 - 0.1 * C / 10
if lib.debug: print('niblack:', C, k)
local = niblack(N, window_size=(2 * SW) | 1, k=k)
debug_imwrite('local.png', local)
local_CCs = algorithm.all_letters(local)
# NB: paper uses OP here, which results in neglecting all small components.
O_inv = ~O
O_inv_32 = O_inv.astype(np.int8,
copy=False).astype(np.int32).astype(np.uint32,
copy=False)
label_map_O_inv = O_inv_32 & local_CCs[0].label_map
CO_inv = np.zeros(im.shape, dtype=np.uint8)
for cc in local_CCs:
if np.count_nonzero(cc.slice(label_map_O_inv) == cc.label) / float(
cc.area()) >= C / 100:
CO_sliced = cc.slice(CO_inv)
np.place(CO_sliced, cc.raster(), 255)
CO = ~CO_inv
debug_imwrite('CO.png', CO)
CO_inv_dilated = cv2.dilate(CO_inv, rect33)
FB = ~(CO_inv | ((~O) & CO_inv_dilated))
debug_imwrite('FB.png', FB)
lib.debug_prefix.pop()
return FB