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import xml.etree.ElementTree as ET
import jsonlines
import random
from tqdm import tqdm
import argparse
import os
import glob
def get_sentence_data(fn):
"""
Parses a sentence file from the Flickr30K Entities dataset
input:
fn - full file path to the sentence file to parse
output:
a list of dictionaries for each sentence with the following fields:
sentence - the original sentence
phrases - a list of dictionaries for each phrase with the
following fields:
phrase - the text of the annotated phrase
first_word_index - the position of the first word of
the phrase in the sentence
phrase_id - an identifier for this phrase
phrase_type - a list of the coarse categories this
phrase belongs to
"""
with open(fn, 'r') as f:
sentences = f.read().split('\n')
annotations = []
for sentence in sentences:
if not sentence:
continue
first_word = []
phrases = []
phrase_id = []
phrase_type = []
words = []
current_phrase = []
add_to_phrase = False
for token in sentence.split():
if add_to_phrase:
if token[-1] == ']':
add_to_phrase = False
token = token[:-1]
current_phrase.append(token)
phrases.append(' '.join(current_phrase))
current_phrase = []
else:
current_phrase.append(token)
words.append(token)
else:
if token[0] == '[':
add_to_phrase = True
first_word.append(len(words))
parts = token.split('/')
phrase_id.append(parts[1][3:])
phrase_type.append(parts[2:])
else:
words.append(token)
sentence_data = {'sentence' : ' '.join(words), 'phrases' : []}
for index, phrase, p_id, p_type in zip(first_word, phrases, phrase_id, phrase_type):
sentence_data['phrases'].append({'first_word_index' : index,
'phrase' : phrase,
'phrase_id' : p_id,
'phrase_type' : p_type})
annotations.append(sentence_data)
return annotations
def get_annotations(fn):
"""
Parses the xml files in the Flickr30K Entities dataset
input:
fn - full file path to the annotations file to parse
output:
dictionary with the following fields:
scene - list of identifiers which were annotated as
pertaining to the whole scene
nobox - list of identifiers which were annotated as
not being visible in the image
boxes - a dictionary where the fields are identifiers
and the values are its list of boxes in the
[xmin ymin xmax ymax] format
"""
tree = ET.parse(fn)
root = tree.getroot()
filename = root.findall('filename')[0].text
size_container = root.findall('size')[0]
anno_info = {'filename': filename, 'boxes' : {}, 'scene' : [], 'nobox' : []}
for size_element in size_container:
anno_info[size_element.tag] = int(size_element.text)
for object_container in root.findall('object'):
for names in object_container.findall('name'):
box_id = names.text
box_container = object_container.findall('bndbox')
if len(box_container) > 0:
if box_id not in anno_info['boxes']:
anno_info['boxes'][box_id] = []
xmin = int(box_container[0].findall('xmin')[0].text) - 1
ymin = int(box_container[0].findall('ymin')[0].text) - 1
xmax = int(box_container[0].findall('xmax')[0].text) - 1
ymax = int(box_container[0].findall('ymax')[0].text) - 1
anno_info['boxes'][box_id].append([xmin, ymin, xmax, ymax])
else:
nobndbox = int(object_container.findall('nobndbox')[0].text)
if nobndbox > 0:
anno_info['nobox'].append(box_id)
scene = int(object_container.findall('scene')[0].text)
if scene > 0:
anno_info['scene'].append(box_id)
return anno_info
def gen_record(sd, an):
filename = an["filename"]
caption = sd["sentence"]
regions = []
for ph in sd["phrases"]:
if ph["phrase_id"] in an["boxes"]:
for box in an["boxes"][ph["phrase_id"]]:
regions.append(
{
"phrase": ph["phrase"],
"bbox": box
}
)
if len(regions) < 1:
print("no phrase regions")
return None
return {
"filename": filename,
"height": an["height"],
"width": an["width"],
"grounding":{
"caption": caption,
"regions": regions
}
}
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="flickr30k entities to ODVG List.")
parser.add_argument("--root", type=str, default="", help="Source anno root")
parser.add_argument("--output_file", type=str, default="flickr30k_entities_odvg.jsonl")
parser.add_argument("--osoi", action="store_true", default=False)
args = parser.parse_args()
print(args)
odvg_anno = []
sentence_list = os.path.join(args.root, "Sentences")
annotation_list = os.path.join(args.root, "Annotations")
sentence_list = sorted(glob.glob(sentence_list + "/*"))
annotation_list = sorted(glob.glob(annotation_list + "/*"))
len_anno = len(annotation_list)
for idx in tqdm(range(len_anno)):
sds = get_sentence_data(sentence_list[idx])
an = get_annotations(annotation_list[idx])
if args.osoi:
sd = sds[random.randint(0, len(sds)-1)]
x = gen_record(sd, an)
if x:
odvg_anno.append(x)
else:
for sd in sds:
x = gen_record(sd, an)
if x:
odvg_anno.append(x)
with jsonlines.open(args.output_file, mode="w") as fwriter:
fwriter.write_all(odvg_anno) |