def __init__(self,args):
BaseTupleLoader.__init__(self,args)
self.img_path = args['db_path'] + '/images/'
lbls = self.data_df['label']
lbl2idx = np.sort(np.unique(lbls))
self.lbl2idx_dict = {k: v for v, k in enumerate(lbl2idx)}
self.final_lbls = [self.lbl2idx_dict[x] for x in list(lbls.values)]
self.num_classes = len(self.lbl2idx_dict.keys())
print(self.__class__.__name__, ' Data size ', self.data_df.shape[0], 'Num lbls', len(self.lbl2idx_dict.keys()))
def __init__(self,args=None):
BaseTupleLoader.__init__(self,args)
self.img_path = config.db_path + '/jpg/'
lbls = self.data_df['label']
lbl2idx = np.sort(np.unique(lbls))
self.lbl2idx_dict = {k: v for v, k in enumerate(lbl2idx)}
self.final_lbls = [self.lbl2idx_dict[x] for x in list(lbls.values)]
self.num_classes = len(self.lbl2idx_dict.keys())
print('Data size ', self.data_df.shape[0], 'Num lbls', len(self.lbl2idx_dict.keys()))
def __init__(self, args):
BaseTupleLoader.__init__(self)
csv_file = args['csv_file']
self.data_df = pd.read_csv(config.db_path + csv_file)
self.img_path = config.db_path + '/'
lbls = self.data_df['label']
lbl2idx = np.sort(np.unique(lbls))
self.lbl2idx_dict = {k: v for v, k in enumerate(lbl2idx)}
self.final_lbls = [self.lbl2idx_dict[x] for x in list(lbls.values)]
self.num_classes = len(self.lbl2idx_dict.keys())
self.data_permutation = np.random.permutation(self.data_df.shape[0])
self.data_idx = 0
print('Data size ', self.data_df.shape[0], 'Num lbls',
len(self.lbl2idx_dict.keys()))