def get_confidence_count(self,
char1,
char2,
char3,
cconf1,
cconf2,
cconf3,
wildcard_char='¦'):
def get_other_char(char_first, char_sec, char_thrd, co1, co2, co3):
if char_first != char_sec:
return char_sec, float(co2)
elif char_first != char_thrd:
return char_thrd, float(co3)
same_ctr = 0
cconf_ctr = float(cconf1)
if char1 == char2:
same_ctr += 1
cconf_ctr += float(cconf2)
if char1 == char3:
same_ctr += 1
cconf_ctr += float(cconf3)
# special cases space: ' ', ' ', 'x'
# wildcard character : '¦', '¦', '¦'
if char1 == ' ' and same_ctr == 1:
# if the confidence of the other character is below that value, space gets the high put in confidence value
return 1, 95.0 #todo j4t
SPACE_TRESH = 50.0
SPACE_PUT_IN_VALUE = 99.0
otherchar, otherconf = get_other_char(char1, char2, char3, cconf1,
cconf2, cconf3)
#print("otherchar",otherchar,"otherconf",otherconf)
if otherconf < SPACE_TRESH:
return 1, SPACE_PUT_IN_VALUE
elif char1 == wildcard_char and same_ctr == 1: #todo: differentiate type of character ??
# if there is two wildcards and one characters, characters confidence has to be higher than
# WILDCARD_TRESH to be taken
wildcard_tresh = 98.5
if self.config.MSA_BEST_CHANGE_VOTING_TRESHS_ON_EMPTY_LINE:
wildcard_tresh -= 10 # 0:99,19%, 20:99.16%, 10:99.27%
return 1, wildcard_tresh
elif char1 == wildcard_char and same_ctr == 0:
pass # todo maybe cover this case (cause wildcard has no confidence i.e if the two otherchars are very low prob, take wildcard)
elif char1 == '' and same_ctr == 0:
pass # todo maybe cover this case (cause space has no confidence ...
elif self.config.MSA_BEST_VOTING_DOWNSCALE_ONLY_SC \
and Random.is_special_character(char1) and same_ctr == 0 \
and char2 == wildcard_char and char3 == wildcard_char:
# lower the confidence of special characters which stand without any other chars
return same_ctr, cconf_ctr * 0.9
return same_ctr, cconf_ctr
def maybe_replace_voted_by_predicted_char(self, voted_char, aufsichtsrat_prediction_toggled, predicted_char, \
wildcard_character, voted_acc_conf, character_1, character_2, character_3):
if aufsichtsrat_prediction_toggled:
if Random.is_special_character(predicted_char):
one_char_sc = Random.is_special_character(character_1) \
or Random.is_special_character(character_2) or Random.is_special_character(
character_3)
voted_char_sc = Random.is_special_character(voted_char)
if predicted_char != voted_char and (
one_char_sc
or voted_char_sc) and voted_char != wildcard_character:
# print("FiloContent:", filo_content)
self.cpr_sc_predict.print("pc:", predicted_char, "vc:",
voted_char, "vc_acc",
voted_acc_conf)
if voted_acc_conf <= 90.0:
if voted_char != '\f': # don't swap formfeeds, they don't get predicted at all
self.cpr_sc_predict.print("swap")
voted_char = predicted_char
return voted_char
def fill_filo_last_chars(self, voted_char):
"""
fill filo for predictor usage with voted_char some additional chars around this char
:param voted_char:
:return:
"""
if self.config.PREDICTOR_AUFSICHTSRAT_ENABLED:
# create pre semi-tokenized input strings in the filos from the voted characters for prediction
if voted_char == ' ':
# the models usally use the 'ƿ' char in substitution for spaces
self.filo_last_chars.push(' ', filterchar='¦')
self.filo_last_chars.push('ƿ', filterchar='¦')
self.filo_last_chars.push(' ', filterchar='¦')
elif Random.is_special_character(voted_char):
self.filo_last_chars.push(' ', filterchar='¦')
self.filo_last_chars.push(voted_char, filterchar='¦')
self.filo_last_chars.push(' ', filterchar='¦')
else:
self.filo_last_chars.push(voted_char, filterchar='¦')
def recognize_a_line(self, line):
if line == None or line == False or line == True or line.textstr == None:
return False
whole_text = line.textstr
self.cpr.print("recognizing line:", whole_text)
# counters
counter_special_chars = 0
counter_alphanumerical_chars = 0
counter_numbers = 0
counter_chars = len(whole_text)
counter_alphabetical = 0
counter_words = 0
counters_alphabetical_ratios = []
counters_wordlengths = []
counters_numbers = []
character_index = 0
# special conditions
ultimo_is_first_word = False
first_word_no_table_indicator = False
starts_with_parenthesis = False
ends_with_parenthesis = False
last_xstop = 0
x_box_sizes = []
x_gaps = []
for key_index, key in enumerate(line.word['text']):
word = line.word['text'][key]
uid_info = line.word['UID'][key]
word_xstart = line.data['word_x0'][character_index]
word_xstop = line.data['word_x1'][character_index]
word_box_size = word_xstop - word_xstart
x_box_sizes.append(word_box_size)
if key_index >= 1:
x_gap = word_xstop - last_xstop
x_gaps.append(x_gap)
#line.data['word_x0']
if word is None or word == "":
continue
if key_index == 0:
if word in self.filter_start_words:
first_word_no_table_indicator = True
if word.lower() == "ultimo":
ultimo_is_first_word = True
if word[0] == "(":
starts_with_parenthesis = True
if key_index == len(line.word['text'])-1:
if word[-1] == ")":
ends_with_parenthesis = True
counter_alphabetical_chars_word = 0
counter_alphanumerical_chars_word = 0
counter_numbers_word = 0
counter_words += 1
word_list = list(word)
for char in word_list:
if Random.is_special_character(char):
counter_special_chars += 1
elif Random.is_alphanumerical_character(char):
counter_alphanumerical_chars += 1
counter_alphanumerical_chars_word += 1
if char.isdigit():
counter_numbers += 1
counter_numbers_word += 1
counter_alphabetical_word = counter_alphanumerical_chars_word - counter_numbers_word
ratio_alphabetical_word = np.round(counter_alphabetical_word/len(word), 2)
counters_alphabetical_ratios.append(ratio_alphabetical_word)
counters_wordlengths.append(len(word))
counters_numbers.append(counter_numbers_word)
character_index += len(uid_info)
last_xstop = word_xstop
# get number of spaces
len_whole_unspace = len(whole_text.replace(" ", ""))
counter_spaces = counter_chars - len_whole_unspace
# set alphabetical counter
counter_alphabetical = counter_alphanumerical_chars - counter_numbers
if counter_chars == 0:
self.cpr.printw("no chars shouldn't happen, no recognizion")
return False
special_chars_ratio = counter_special_chars/ counter_chars
alphanumerical_chars_ratio = counter_alphanumerical_chars / counter_chars
alphabetical_ratio = counter_alphabetical / counter_chars
spaces_ratio = counter_spaces/ counter_chars
numbers_ratio = counter_numbers / counter_chars
maximum_x_gap = None
mean_x_gap = None
median_x_gap = None
if len(x_gaps) >= 1:
maximum_x_gap = max(x_gaps)
mean_x_gap = np.mean(x_gaps)
median_x_gap = np.median(x_gaps)
many_numbers_in_first_word = False
many_alphabetical_in_middle_words = False
many_alphabetical_in_last_word = False
# check some middle and last word conditions
for counter_index, counter in enumerate(counters_wordlengths):
if counter_index == 0:
ctr_numbers = counters_numbers[counter_index]
numbers_ratio_word = np.round(ctr_numbers/counter,2)
if numbers_ratio_word > 0.8:
many_numbers_in_first_word = True
elif counter_index == len(counters_wordlengths)-1:
if counter >= 4:
alphabetical_ratio_word = counters_alphabetical_ratios[counter_index]
if alphabetical_ratio_word >= 0.75:
many_alphabetical_in_last_word = True
else:
if counter >= 4:
alphabetical_ratio_word = counters_alphabetical_ratios[counter_index]
if alphabetical_ratio_word >= 0.75:
many_alphabetical_in_middle_words = True
self.cpr.print("alle cntr:", counter_chars)
self.cpr.print("spec cntr:", counter_special_chars, "ratio", special_chars_ratio)
self.cpr.print("alnr cntr:", counter_alphanumerical_chars, "ratio", alphanumerical_chars_ratio)
self.cpr.print("albt cntr:", counter_alphabetical, "ratio", alphabetical_ratio)
self.cpr.print("spce cntr:", counter_spaces, "ratio", spaces_ratio)
self.cpr.print("nmbr cntr:", counter_numbers, "ratio", numbers_ratio)
self.cpr.print("x_box_sizes", x_box_sizes)
self.cpr.print("x_gaps", x_gaps)
self.cpr.print("x_gap_max_size", maximum_x_gap)
self.cpr.print("x_gaps_mean", mean_x_gap)
self.cpr.print("x_gaps_median", median_x_gap)
if "Gewinn nach Vortrag" in whole_text:
print("")
if ((alphabetical_ratio < 0.75 and \
numbers_ratio > 0.2 and \
counter_chars > 5 and \
counter_words >= 2) and not \
(starts_with_parenthesis and ends_with_parenthesis)) or ultimo_is_first_word:
if first_word_no_table_indicator:
return False
if mean_x_gap <= 115:
return False
if many_alphabetical_in_last_word:
return False
if many_alphabetical_in_middle_words and many_numbers_in_first_word:
return False
self.cpr.print("possible entry:", whole_text)
if self.PRINT_TO_CHECKFILE:
with open("checkfile_tables.txt", "a") as myfile:
myfile.write(whole_text+ "||| max x_gap: " + str(maximum_x_gap)+"||| mean x_gap: " + str(mean_x_gap) \
+ "||| median x_gap: " + str(median_x_gap)+"\n")
print("jab")
return True
return False
def vocabulary_related_corrections(self, accumulated_chars,
wildcard_character, accumulated_confs):
if self.config.KEYING_RESULT_VOCABULARY_CORRECTION_VOTE:
accumulated_chars_final = ""
acc_split = accumulated_chars.split()
len_split = len(acc_split)
for word_index, word in enumerate(acc_split):
if self.config.KEYING_RESULT_VC_IGNORE_SEPERATE_WRITING_CORRECTION:
if word_index == len_split - 1 and word.replace(
wildcard_character, "").endswith('-'):
self.previous_word_with_seperator = True
accumulated_chars_final += word + " "
continue
if word_index == 0:
if self.previous_word_with_seperator is True:
self.previous_word_with_seperator = False
accumulated_chars_final += word + " "
continue
acc_confs_word = accumulated_confs.pop_multi(len(word))
acc_conf, rate, change, word_starting_borders, word_trailing_borders, word_reduced = \
self.vocab_checker.get_accumulated_confidence_rate(word, acc_confs_word, wildcard_character)
self.cpr_vocab_check.print("w:", word, "wr:", word_reduced,
"accr:", acc_conf, "rate", rate)
# don't correct words below min vocab length ( mind that special chars in dict are toggled)
check_len = len(word)
if self.config.KEYING_RESULT_VC_DICT_REMOVE_SPECIAL_BORDER_CHARS:
check_len = len(word_reduced)
if check_len < self.config.KEYING_RESULT_VC_MIN_VOCAB_WORD_LENGTH:
accumulated_chars_final += word + " "
continue
if self.config.KEYING_RESULT_VC_CORRECT_ONLY_ERRONOUS_CHARS:
swappable_char_indices = []
acc_confs_used = None
word_used = None
if self.config.KEYING_RESULT_VC_CORRECT_ERRONOUS_SPECIAL_CHARS:
# use the full length confidences array including trailing and leading special characters
acc_confs_used = acc_confs_word
word_used = word
else:
# don't use trailing and starting special characters if no special chars needed
acc_confs_used = acc_confs_word[
len(word_starting_borders):(
len(acc_confs_word) -
len(word_trailing_borders))]
word_used = word_reduced
for conf_index, conf in enumerate(acc_confs_used):
if self.config.KEYING_RESULT_VC_CORRECT_ERRONOUS_SPECIAL_CHARS:
if conf <= 250:
character_related = word_used[conf_index]
is_special_char = Random.is_special_character(
character_related)
if is_special_char and character_related != wildcard_character:
# only swap special character indices
swappable_char_indices.append(conf_index)
else:
if conf <= 215:
swappable_char_indices.append(conf_index)
if len(swappable_char_indices) >= 1:
word_reduced_correct = self.vocab_checker.correct_text_at_certain_indices_only(
word_used, swappable_char_indices)
if word_reduced_correct != None:
word_correct_withtrails = None
if self.config.KEYING_RESULT_VC_CORRECT_ERRONOUS_SPECIAL_CHARS:
if Random.has_special_character(
word_reduced_correct):
# if special character was replaced with special character
word_correct_withtrails = word_reduced_correct
else:
# if special character was replaced by alphanumerical character
word_correct_withtrails = word
else:
word_correct_withtrails = word_starting_borders + word_reduced_correct + word_trailing_borders
# only print the changed results
if word != word_correct_withtrails:
self.cpr_vocab_check.print(
"w:", word, "wc:", word_correct_withtrails,
"accr:", acc_conf, "rate", rate)
accumulated_chars_final += word_correct_withtrails + " "
else:
accumulated_chars_final += word + " "
else:
accumulated_chars_final += word + " "
continue
if rate < self.config.KEYING_RESULT_VOCABULARY_CORRECTION_VOTE_TRESH \
and len(word_reduced) > 2:
# if the rate drops below tresh, try to fetch vocab entry
word_reduced_correct, suggestions, flh = self.vocab_checker.correct_text(
word_reduced)
if word_reduced_correct != None and word_reduced_correct != word_reduced:
word_correct_withtrails = word_starting_borders + word_reduced_correct + word_trailing_borders
self.cpr_vocab_check.print("w:", word, "wc:",
word_correct_withtrails,
"accr:", acc_conf, "rate",
rate)
accumulated_chars_final += word_correct_withtrails + " "
else:
accumulated_chars_final += word + " "
else:
accumulated_chars_final += word + " "
accumulated_chars = accumulated_chars_final
return accumulated_chars
def extract_line_features(self, line):
final_line_features = {}
whole_text = line['text']
self.cpr.print("recognizing text:", whole_text)
# counters
counter_special_chars = 0
counter_alphanumerical_chars = 0
counter_numbers = 0
counter_chars = len(whole_text)
counter_alphabetical = 0
counter_words = 0
counters_alphabetical_ratios = []
counters_wordlengths = []
counters_numbers = []
character_index = 0
# special conditions
ultimo_is_first_word = False
first_word_no_table_indicator = False
starts_with_parenthesis = False
ends_with_parenthesis = False
last_xstop = 0
x_box_sizes = []
x_gaps = []
for word_obj in line['words']:
word_index = word_obj['word_index']
word_text = word_obj['text']
hocr_coordinates = word_obj['hocr_coordinates']
word_xstart = hocr_coordinates[0]
word_xstop = hocr_coordinates[2]
word_box_size = word_xstop - word_xstart
x_box_sizes.append(word_box_size)
if word_index >= 1:
x_gap = word_xstop - last_xstop
x_gaps.append(x_gap)
#line.data['word_x0']
if word_text is None or word_text == "":
continue
if word_index == 0:
if word_text in self.filter_start_words:
first_word_no_table_indicator = True
if word_text.lower() == "ultimo":
ultimo_is_first_word = True
if word_text[0] == "(":
starts_with_parenthesis = True
if word_index == len(whole_text) - 1:
if word_text[-1] == ")":
ends_with_parenthesis = True
counter_alphabetical_chars_word = 0
counter_alphanumerical_chars_word = 0
counter_numbers_word = 0
counter_words += 1
word_list = list(word_text)
for char in word_list:
if Random.is_special_character(char):
counter_special_chars += 1
elif Random.is_alphanumerical_character(char):
counter_alphanumerical_chars += 1
counter_alphanumerical_chars_word += 1
if char.isdigit():
counter_numbers += 1
counter_numbers_word += 1
counter_alphabetical_word = counter_alphanumerical_chars_word - counter_numbers_word
ratio_alphabetical_word = np.round(
counter_alphabetical_word / len(word_text), 2)
counters_alphabetical_ratios.append(ratio_alphabetical_word)
counters_wordlengths.append(len(word_text))
counters_numbers.append(counter_numbers_word)
character_index += len(word_text)
last_xstop = word_xstop
# get number of spaces
len_whole_unspace = len(whole_text.replace(" ", ""))
counter_spaces = counter_chars - len_whole_unspace
# set alphabetical counter
counter_alphabetical = counter_alphanumerical_chars - counter_numbers
if counter_chars == 0:
self.cpr.printw("no chars in line:", str(line['line_index']),
"no features here")
return False
special_chars_ratio = counter_special_chars / counter_chars
alphanumerical_chars_ratio = counter_alphanumerical_chars / counter_chars
alphabetical_ratio = counter_alphabetical / counter_chars
spaces_ratio = counter_spaces / counter_chars
numbers_ratio = counter_numbers / counter_chars
maximum_x_gap = None
mean_x_gap = None
median_x_gap = None
if len(x_gaps) >= 1:
maximum_x_gap = max(x_gaps)
mean_x_gap = np.mean(x_gaps)
median_x_gap = np.median(x_gaps)
many_numbers_in_first_word = False
many_alphabetical_in_middle_words = False
many_alphabetical_in_last_word = False
# check some middle and last word conditions
for counter_index, counter in enumerate(counters_wordlengths):
if counter_index == 0:
ctr_numbers = counters_numbers[counter_index]
numbers_ratio_word = np.round(ctr_numbers / counter, 2)
if numbers_ratio_word > 0.8:
many_numbers_in_first_word = True
elif counter_index == len(counters_wordlengths) - 1:
if counter >= 4:
alphabetical_ratio_word = counters_alphabetical_ratios[
counter_index]
if alphabetical_ratio_word >= 0.75:
many_alphabetical_in_last_word = True
else:
if counter >= 4:
alphabetical_ratio_word = counters_alphabetical_ratios[
counter_index]
if alphabetical_ratio_word >= 0.75:
many_alphabetical_in_middle_words = True
final_line_features = LineFeatures(cpr=self.cpr)
final_line_features.many_alphabetical_in_last_word = many_alphabetical_in_last_word
final_line_features.counter_special_chars = counter_special_chars
final_line_features.counter_chars = counter_chars
final_line_features.counter_spaces = counter_spaces
final_line_features.counter_numbers = counter_numbers
final_line_features.counter_alphabetical = counter_alphabetical
final_line_features.counter_alphanumerical_chars = counter_alphanumerical_chars
final_line_features.counter_words = counter_words
final_line_features.counters_numbers = counters_numbers
final_line_features.counters_wordlengths = counters_wordlengths
final_line_features.counters_alphabetical_ratios = counters_alphabetical_ratios
final_line_features.numbers_ratio = numbers_ratio
final_line_features.alphabetical_ratio = alphabetical_ratio
final_line_features.alphanumerical_chars_ratio = alphanumerical_chars_ratio
final_line_features.special_chars_ratio = special_chars_ratio
final_line_features.spaces_ratio = spaces_ratio
final_line_features.many_alphabetical_in_last_word = many_alphabetical_in_last_word
final_line_features.many_alphabetical_in_middle_words = many_alphabetical_in_middle_words
final_line_features.many_numbers_in_first_word = many_numbers_in_first_word
final_line_features.x_box_sizes = x_box_sizes
final_line_features.x_gaps = x_gaps
final_line_features.maximum_x_gap = maximum_x_gap
final_line_features.mean_x_gap = mean_x_gap
final_line_features.median_x_gap = median_x_gap
return final_line_features
def validate_column_features(self,
search_space,
x_index,
reference_char=None,
count_up_similar_references=False):
counter_whitespaces = 0
counter_wildcards = 0
counter_nones = 0
counter_characters = 0
counter_reference_char = 0
counter_same_characters = 0
counter_dict = {}
counter_special_characters = 0
most_occuring_char = None
otherchar = None
otherchar_y_index = None
simchars = None
if reference_char is not None and count_up_similar_references is True:
simchars = self.get_simchars_for_char(reference_char)
if len(simchars) != 1:
self._cpr.print("evaluate")
# gather data
for y_index in range(0, self.get_y_size()):
row = search_space[y_index]
column_item = row[x_index]
if column_item == self.get_wildcard_char():
counter_wildcards += 1
elif column_item == ' ':
counter_whitespaces += 1
elif column_item == None or column_item == False or column_item == True:
counter_nones += 1
else:
if reference_char is not None:
if count_up_similar_references is False and column_item == reference_char:
counter_reference_char += 1
if count_up_similar_references is True:
matching = [s for s in simchars if column_item in s]
boolmatch = len(matching) >= 1
if boolmatch is True:
counter_reference_char += 1
counter_characters += 1
otherchar = column_item
otherchar_y_index = y_index
if column_item != None:
if column_item != self._wildcard_character and \
column_item != " ":
if not column_item in counter_dict.keys():
counter_dict.update({column_item: 1})
else:
counter_dict[column_item] += 1
if Random.is_special_character(column_item):
counter_special_characters += 1
# the highest amount of same characters in this column
if len(counter_dict.items()) >= 1:
most_occuring_char, counter_same_characters = max(
counter_dict.items(), key=operator.itemgetter(1))
# extract features
features = []
counter_whitespace_and_wildcards = counter_whitespaces + counter_wildcards
if counter_nones == self.get_y_size():
features.append(ColumnFeatures.ONLY_NONE.value)
if counter_wildcards == self.get_y_size(
) - 1 and counter_characters == 1:
features.append((ColumnFeatures.ONE_CHAR_REST_WILDCARDS).value)
# additional feature, the only char is a special character
if Random.is_special_character(otherchar):
features.append(
ColumnFeatures.ONE_SPECIALCHAR_REST_WILDCARDS.value)
if counter_whitespaces == self.get_y_size(
) - 1 and counter_characters == 1:
features.append(ColumnFeatures.ONE_CHAR_REST_WHITESPACE.value)
if counter_whitespace_and_wildcards == self.get_y_size(
) - 1 and counter_characters == 1:
features.append(
ColumnFeatures.ONE_CHAR_REST_WHITESPACE_OR_WILDCARDS.value)
# additional feature, the only char is a special character
if otherchar != self._wildcard_character and otherchar != " "\
and Random.is_special_character(otherchar):
#print("feature extraction")
#print(search_space[0])
#print(search_space[1])
#print(search_space[2])
#print("x-index",x_index)
features.append(
ColumnFeatures.
ONE_SPECIALCHAR_REST_WHITESPACE_OR_WILDCARDS.value)
if counter_reference_char == self.get_y_size() - 1 and (
counter_whitespaces == 1 or counter_wildcards == 1):
features.append(ColumnFeatures.MOSTLY_REFERENCE_CHAR.value)
if counter_whitespaces == self.get_y_size():
features.append(ColumnFeatures.ONLY_WHITESPACE.value)
if counter_reference_char == self.get_y_size():
features.append(ColumnFeatures.ONLY_WILDCARD.value)
if counter_whitespace_and_wildcards == self.get_y_size():
features.append(ColumnFeatures.ONLY_WHITESPACE_OR_WILDCARD.value)
if counter_reference_char >= 1:
features.append(ColumnFeatures.CONTAINS_REFERENCE_CHAR.value)
if counter_same_characters == self.get_y_size():
if counter_special_characters == self.get_y_size():
features.append(ColumnFeatures.ONLY_SAME_SPECIAL_CHAR.value)
if Random.is_special_character(most_occuring_char) \
and counter_same_characters == self.get_y_size()-1 \
and most_occuring_char != self._wildcard_character \
and counter_whitespace_and_wildcards == 1:
features.append(ColumnFeatures.MOSTLY_SAME_SPECIAL_CHAR.value)
return features, otherchar, otherchar_y_index