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from tqdm import tqdm
import re
class EvalAIAnswerProcessor:
"""
Processes an answer similar to Eval AI
copied from
https://github.com/facebookresearch/mmf/blob/c46b3b3391275b4181567db80943473a89ab98ab/pythia/tasks/processors.py#L897
"""
CONTRACTIONS = {
"aint": "ain't",
"arent": "aren't",
"cant": "can't",
"couldve": "could've",
"couldnt": "couldn't",
"couldn'tve": "couldn't've",
"couldnt've": "couldn't've",
"didnt": "didn't",
"doesnt": "doesn't",
"dont": "don't",
"hadnt": "hadn't",
"hadnt've": "hadn't've",
"hadn'tve": "hadn't've",
"hasnt": "hasn't",
"havent": "haven't",
"hed": "he'd",
"hed've": "he'd've",
"he'dve": "he'd've",
"hes": "he's",
"howd": "how'd",
"howll": "how'll",
"hows": "how's",
"Id've": "I'd've",
"I'dve": "I'd've",
"Im": "I'm",
"Ive": "I've",
"isnt": "isn't",
"itd": "it'd",
"itd've": "it'd've",
"it'dve": "it'd've",
"itll": "it'll",
"let's": "let's",
"maam": "ma'am",
"mightnt": "mightn't",
"mightnt've": "mightn't've",
"mightn'tve": "mightn't've",
"mightve": "might've",
"mustnt": "mustn't",
"mustve": "must've",
"neednt": "needn't",
"notve": "not've",
"oclock": "o'clock",
"oughtnt": "oughtn't",
"ow's'at": "'ow's'at",
"'ows'at": "'ow's'at",
"'ow'sat": "'ow's'at",
"shant": "shan't",
"shed've": "she'd've",
"she'dve": "she'd've",
"she's": "she's",
"shouldve": "should've",
"shouldnt": "shouldn't",
"shouldnt've": "shouldn't've",
"shouldn'tve": "shouldn't've",
"somebody'd": "somebodyd",
"somebodyd've": "somebody'd've",
"somebody'dve": "somebody'd've",
"somebodyll": "somebody'll",
"somebodys": "somebody's",
"someoned": "someone'd",
"someoned've": "someone'd've",
"someone'dve": "someone'd've",
"someonell": "someone'll",
"someones": "someone's",
"somethingd": "something'd",
"somethingd've": "something'd've",
"something'dve": "something'd've",
"somethingll": "something'll",
"thats": "that's",
"thered": "there'd",
"thered've": "there'd've",
"there'dve": "there'd've",
"therere": "there're",
"theres": "there's",
"theyd": "they'd",
"theyd've": "they'd've",
"they'dve": "they'd've",
"theyll": "they'll",
"theyre": "they're",
"theyve": "they've",
"twas": "'twas",
"wasnt": "wasn't",
"wed've": "we'd've",
"we'dve": "we'd've",
"weve": "we've",
"werent": "weren't",
"whatll": "what'll",
"whatre": "what're",
"whats": "what's",
"whatve": "what've",
"whens": "when's",
"whered": "where'd",
"wheres": "where's",
"whereve": "where've",
"whod": "who'd",
"whod've": "who'd've",
"who'dve": "who'd've",
"wholl": "who'll",
"whos": "who's",
"whove": "who've",
"whyll": "why'll",
"whyre": "why're",
"whys": "why's",
"wont": "won't",
"wouldve": "would've",
"wouldnt": "wouldn't",
"wouldnt've": "wouldn't've",
"wouldn'tve": "wouldn't've",
"yall": "y'all",
"yall'll": "y'all'll",
"y'allll": "y'all'll",
"yall'd've": "y'all'd've",
"y'alld've": "y'all'd've",
"y'all'dve": "y'all'd've",
"youd": "you'd",
"youd've": "you'd've",
"you'dve": "you'd've",
"youll": "you'll",
"youre": "you're",
"youve": "you've",
}
NUMBER_MAP = {
"none": "0",
"zero": "0",
"one": "1",
"two": "2",
"three": "3",
"four": "4",
"five": "5",
"six": "6",
"seven": "7",
"eight": "8",
"nine": "9",
"ten": "10",
}
ARTICLES = ["a", "an", "the"]
PERIOD_STRIP = re.compile(r"(?!<=\d)(\.)(?!\d)")
COMMA_STRIP = re.compile(r"(?<=\d)(\,)+(?=\d)")
PUNCTUATIONS = [
";",
r"/",
"[",
"]",
'"',
"{",
"}",
"(",
")",
"=",
"+",
"\\",
"_",
"-",
">",
"<",
"@",
"`",
",",
"?",
"!",
]
def __init__(self, *args, **kwargs):
pass
def word_tokenize(self, word):
word = word.lower()
word = word.replace(",", "").replace("?", "").replace("'s", " 's")
return word.strip()
def process_punctuation(self, in_text):
out_text = in_text
for p in self.PUNCTUATIONS:
if (p + " " in in_text or " " + p in in_text) or (
re.search(self.COMMA_STRIP, in_text) is not None
):
out_text = out_text.replace(p, "")
else:
out_text = out_text.replace(p, " ")
out_text = self.PERIOD_STRIP.sub("", out_text, re.UNICODE)
return out_text
def process_digit_article(self, in_text):
out_text = []
temp_text = in_text.lower().split()
for word in temp_text:
word = self.NUMBER_MAP.setdefault(word, word)
if word not in self.ARTICLES:
out_text.append(word)
else:
pass
for word_id, word in enumerate(out_text):
if word in self.CONTRACTIONS:
out_text[word_id] = self.CONTRACTIONS[word]
out_text = " ".join(out_text)
return out_text
def __call__(self, item):
item = self.word_tokenize(item)
item = item.replace("\n", " ").replace("\t", " ").strip()
item = self.process_punctuation(item)
item = self.process_digit_article(item)
return item
class TextVQAAccuracyEvaluator:
def __init__(self):
self.answer_processor = EvalAIAnswerProcessor()
def _compute_answer_scores(self, raw_answers):
"""
compute the accuracy (soft score) of human answers
"""
answers = [self.answer_processor(a) for a in raw_answers]
assert len(answers) == 10
gt_answers = list(enumerate(answers))
unique_answers = set(answers)
unique_answer_scores = {}
for unique_answer in unique_answers:
accs = []
for gt_answer in gt_answers:
other_answers = [item for item in gt_answers if item != gt_answer]
matching_answers = [
item for item in other_answers if item[1] == unique_answer
]
acc = min(1, float(len(matching_answers)) / 3)
accs.append(acc)
unique_answer_scores[unique_answer] = sum(accs) / len(accs)
return unique_answer_scores
def eval_pred_list(self, pred_list):
pred_scores = []
for entry in tqdm(pred_list):
pred_answer = self.answer_processor(entry["pred_answer"])
unique_answer_scores = self._compute_answer_scores(entry["gt_answers"])
score = unique_answer_scores.get(pred_answer, 0.0)
pred_scores.append(score)
accuracy = sum(pred_scores) / len(pred_scores)
return accuracy
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