def __init__(self,
input_dir,
input_vqa,
max_qst_length=30,
max_num_ans=10,
transform=None):
self.input_dir = input_dir
self.vqa = np.load(input_dir + '/' + input_vqa)
self.qst_vocab = text_helper.VocabDict(input_dir +
'/vocab_questions.txt')
self.ans_vocab = text_helper.VocabDict(input_dir +
'/vocab_answers.txt')
self.max_qst_length = max_qst_length
self.max_num_ans = max_num_ans
self.load_ans = ('valid_answers'
in self.vqa[0]) and (self.vqa[0]['valid_answers']
is not None)
self.transform = transform
def __init__(self,
input_dir,
input_vqa,
max_qst_length=30,
max_num_ans=10,
transform=None):
self.input_dir = input_dir
self.vqa = np.load(input_dir + '/preprocessed_data' + '/' + input_vqa,
allow_pickle=True) # 整合后的数据集
self.qst_vocab = text_helper.VocabDict(input_dir + '/questions' +
'/vocab_questions.txt') # 建立类
self.ans_vocab = text_helper.VocabDict(input_dir + '/annotations' +
'/vocab_answers.txt')
self.max_qst_length = max_qst_length # 设置问题长度
self.max_num_ans = max_num_ans # 设置答案数目
self.load_ans = ('valid_answers' in self.vqa[0]) and (
self.vqa[0]['valid_answers'] is not None
) # Ture or False. 有效答案没有的都赋成了['<unk>']
self.transform = transform