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fix dataloader.py #2

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fix dataloader.py #2

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10 changes: 5 additions & 5 deletions utils/dataloader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,8 +35,8 @@ def __init__(self, db_path, ext):
if self.ext == '.npy':
self.loader = lambda x: np.load(x)
else:
self.loader = lambda x: np.load(x)['x']
# self.loader = lambda x: np.transpose(np.load(x)['x'])
# self.loader = lambda x: np.load(x)['x']
self.loader = lambda x: np.transpose(np.load(x)['x'])
if db_path.endswith('.pth'): # Assume a key,value dictionary
self.db_type = 'pth'
self.feat_file = torch.load(db_path)
Expand Down Expand Up @@ -157,7 +157,7 @@ def __init__(self, opt):
# self.fc_loader = HybridLoader(self.opt.input_fc_dir, '.npy')
self.att_loader = HybridLoader(self.opt.image_feat_dir, '.npz')
self.att2_loader = None
if len(self.opt.image_feat_dir2) != 0:
if hasattr(self.opt, 'image_feat_dir2') and len(self.opt.image_feat_dir2) != 0:
self.att2_loader = HybridLoaderv2(self.opt.image_feat_dir, '.npz', self.opt.image_feat_dir2)
# self.box_loader = HybridLoader(self.opt.input_att_dir, '.npz')['']

Expand Down Expand Up @@ -265,10 +265,10 @@ def collate_func(self, batch, split):
max_att_len = max([i[0] for i in num_bbox_batch])
data['att_feats'] = np.zeros([len(att_batch)*seq_per_img, 100, att_batch[0].shape[1]], dtype = 'float32')
for i in range(len(att_batch)):
data['att_feats'][i*5:(i+1)*5, :att_batch[i].shape[0]] = np.tile(att_batch[i], (5, 1)).reshape(5, att_batch[i].shape[0], att_batch[i].shape[1])
data['att_feats'][i*seq_per_img:(i+1)*seq_per_img, :att_batch[i].shape[0]] = np.tile(att_batch[i], (seq_per_img, 1)).reshape(seq_per_img, att_batch[i].shape[0], att_batch[i].shape[1])
data['att_masks'] = np.zeros(data['att_feats'].shape[:2], dtype='float32')
for i in range(len(att_batch)):
data['att_masks'][i*5:(i+1)*5, :att_batch[i].shape[0]] = np.ones([5, att_batch[i].shape[0]])
data['att_masks'][i*seq_per_img:(i+1)*seq_per_img, :att_batch[i].shape[0]] = np.ones([seq_per_img, att_batch[i].shape[0]])
# set att_masks to None if attention features have same length
if data['att_masks'].sum() == data['att_masks'].size:
data['att_masks'] = None
Expand Down