def find_label_pos(label, sys_utt_tokens, usr_utt_tokens):
for _label in [label] + SEMANTIC_DICT.get(label, []):
_label_tokens = utils.tokenize(_label)
sys_label_pos = list(utils.find_sublist(sys_utt_tokens, _label_tokens))
usr_label_pos = list(utils.find_sublist(usr_utt_tokens, _label_tokens))
if sys_label_pos or usr_label_pos:
return _label, sys_label_pos, usr_label_pos
return label, sys_label_pos, usr_label_pos
def advanced_tagger(sentence):
NP = X_extractor(sentence, 'NP')
tok = nltk.word_tokenize(sentence)
tag = nltk.pos_tag(tok)
for np in NP:
index = utils.find_sublist(nltk.word_tokenize(np), tok)[0] #have trouble if occur multiple times
tok = tok[:index[0]] + [np] + tok[index[1]+1:]
tag = tag[:index[0]] + [(np, 'NP')] +tag[index[1]+1:]
return (tok, tag)
def get_test_entities(self):
""" Returns dictionary of test entity indices by type """
print('\nTEST')
test_entities = {'PER': [], 'LOC': [], 'ORG': [], 'MISC': []}
#for triplet in test list
for sent, pos_tags, indices in self.test_data:
for key in self.known_entities:
for ne in self.known_entities[key]:
matches = find_sublist(ne, sent)
#DEBUG('-> matches = {}'.format(matches))
for begin, end in matches:
tag = {
'string': ' '.join(sent[begin:end + 1]),
'indices': (indices[begin], indices[end])
}
test_entities[key].append(tag)
return test_entities
def _load_flickr30k(dataroot, img_id2idx, bbox, pos_boxes):
"""Load entries
img_id2idx: dict {img_id -> val} val can be used to retrieve image or features
dataroot: root path of dataset
name: 'train', 'val', 'test-dev2015', test2015'
"""
pattern_phrase = r'\[(.*?)\]'
pattern_no = r'\/EN\#(\d+)'
missing_entity_count = dict()
multibox_entity_count = 0
entries = []
for image_id, idx in img_id2idx.items():
phrase_file = os.path.join(
dataroot, 'Flickr30kEntities/Sentences/%d.txt' % image_id)
anno_file = os.path.join(
dataroot, 'Flickr30kEntities/Annotations/%d.xml' % image_id)
with open(phrase_file, 'r', encoding='utf-8') as f:
sents = [x.strip() for x in f]
# Parse Annotation
root = parse(anno_file).getroot()
obj_elems = root.findall('./object')
pos_box = pos_boxes[idx]
bboxes = bbox[pos_box[0]:pos_box[1]]
target_bboxes = {}
for elem in obj_elems:
if elem.find('bndbox') == None or len(elem.find('bndbox')) == 0:
continue
left = int(elem.findtext('./bndbox/xmin'))
top = int(elem.findtext('./bndbox/ymin'))
right = int(elem.findtext('./bndbox/xmax'))
bottom = int(elem.findtext('./bndbox/ymax'))
assert 0 < left and 0 < top
for name in elem.findall('name'):
entity_id = int(name.text)
assert 0 < entity_id
if not entity_id in target_bboxes:
target_bboxes[entity_id] = []
else:
multibox_entity_count += 1
target_bboxes[entity_id].append([left, top, right, bottom])
# Parse Sentence
for sent_id, sent in enumerate(sents):
sentence = utils.remove_annotations(sent)
entities = re.findall(pattern_phrase, sent)
entity_indices = []
target_indices = []
entity_ids = []
entity_types = []
for entity_i, entity in enumerate(entities):
info, phrase = entity.split(' ', 1)
entity_id = int(re.findall(pattern_no, info)[0])
entity_type = info.split('/')[2:]
entity_idx = utils.find_sublist(sentence.split(' '),
phrase.split(' '))
assert 0 <= entity_idx
if not entity_id in target_bboxes:
if entity_id >= 0:
missing_entity_count[
entity_type[0]] = missing_entity_count.get(
entity_type[0], 0) + 1
continue
assert 0 < entity_id
entity_ids.append(entity_id)
entity_types.append(entity_type)
target_idx = utils.get_match_index(target_bboxes[entity_id],
bboxes)
entity_indices.append(entity_idx)
target_indices.append(target_idx)
if 0 == len(entity_ids):
continue
entries.append(
_create_flickr_entry(idx, sentence, entity_indices,
target_indices, entity_ids, entity_types))
if 0 < len(missing_entity_count.keys()):
print('missing_entity_count=')
print(missing_entity_count)
print('multibox_entity_count=%d' % multibox_entity_count)
return entries
def _load_kairos(dataset,
img_id2idx,
bbox,
pos_boxes,
topic_doc_json,
topic=None):
"""Load entries
img_id2idx: dict {img_id -> val} val can be used to retrieve image or features
dataroot: root path of dataset
name: 'train', 'val', 'test-dev2015', test2015'
"""
pattern_phrase = r'\[\/EN\#(.*?)\]'
pattern_no = r'\/EN\#(\d+)'
missing_entity_count = dict()
multibox_entity_count = 0
entries = []
if topic is None:
topic = dataset
for image_id, idx in img_id2idx.items():
# anno_file = f'data/{dataset}/annotations/{image_id}.xml'
for phrase_id in topic_doc_json[topic]:
phrase_file = f'data/{dataset}/json_output/ent_sents/{phrase_id}.txt'
with open(phrase_file, 'r', encoding='utf-8') as f:
sents = [x.strip() for x in f]
# Parse Annotation
# root = parse(anno_file).getroot()
# obj_elems = root.findall('./object')
# pos_box = pos_boxes[idx]
# bboxes = bbox[pos_box[0]:pos_box[1]]
# target_bboxes = {}
# for elem in obj_elems:
# if elem.find('bndbox') == None or len(elem.find('bndbox')) == 0:
# continue
# left = int(elem.findtext('./bndbox/xmin'))
# top = int(elem.findtext('./bndbox/ymin'))
# right = int(elem.findtext('./bndbox/xmax'))
# bottom = int(elem.findtext('./bndbox/ymax'))
# assert 0 <= left and 0 <= bottom, f"[{left}, {top}, {right}, {bottom}]"
# for name in elem.findall('name'):
# entity_id = int(name.text)
# assert 0 < entity_id
# if not entity_id in target_bboxes:
# target_bboxes[entity_id] = []
# else:
# multibox_entity_count += 1
# target_bboxes[entity_id].append([left, top, right, bottom])
# Parse Sentence
for sent_id, sent in enumerate(sents):
sentence = utils.remove_annotations(sent)
entities = re.findall(pattern_phrase, sent)
entity_indices = []
# target_indices = []
entity_ids = []
entity_types = []
# pdb.set_trace()
for entity_i, entity in enumerate(entities):
entity = "/EN#" + entity
info, phrase = entity.split(' ', 1)
try:
entity_id = int(re.findall(pattern_no, info)[0])
except:
print(
f"entity_id = {entity_id}, entity = {entity} \nsentence = {sentence}, info = {info}"
)
raise Exception("entry creation failed")
entity_type = info.split('/')[2:]
entity_idx = utils.find_sublist(sentence.split(' '),
phrase.split(' '))
try:
assert 0 <= entity_idx, f"entity_idx = {entity_idx}, entity = {phrase} \nsentence = {sentence}, info = {info}"
except:
continue
# if not entity_id in target_bboxes:
# if entity_id >= 0:
# missing_entity_count[entity_type[0]] = missing_entity_count.get(entity_type[0], 0) + 1
assert 0 < entity_id
entity_ids.append(entity_id)
entity_types.append(entity_type)
# target_idx = utils.get_match_index(target_bboxes[entity_id], bboxes)
entity_indices.append(entity_idx)
# target_indices.append(target_idx)
if 0 == len(entity_ids):
continue
try:
entry = _create_kairos_entry(idx,
f"{phrase_id}-s{sent_id}",
sentence, entity_indices,
entity_ids, entity_types)
except:
print(idx, sent_id, sentence, sent)
raise Exception("entry creation failed")
entries.append(entry)
if 0 < len(missing_entity_count.keys()):
print('missing_entity_count=')
print(missing_entity_count)
print('multibox_entity_count=%d' % multibox_entity_count)
return entries
