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View Code? Open in Web Editor NEWAROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors
AROMA: A Deep Multi-Task Learning Based Simple and Complex Human Activity Recognition Method Using Wearable Sensors
Hello,
I am trying to use the OpportunityDataset
class (in data1.py) to parse the files in the dataset using the configuration below but it is not working. It cannot reshape the X tensor correctly at line 214
return np.reshape(res, (int(len(res) / win), win, self.config.f_num))
I was wondering how do you reduce the number of channels to 113 and which sensors are selected.
Thanks!
Config:
class OpportunityConfig(object):
def __init__(self):
''' Without unlabeled data
'''
self.channels = 113
self.f_num = self.channels
self.overlap_ratio = 0.5
self.s_win_size = 24
self.c_win_size = 10 # 10
self.s_labels_num = 4
self.c_labels_num = 5
self.batch_size = 64
self.norm = False
self.max_lr = 0.003
self.min_lr = 0.0001
self.decay_speed = 700
self.iter = 2101
self.test_point = 30
self.dataset = data1.OpportunityDataset("OpportunityUCIDataset/dataset/", self)
I'm wondering if you could provide huynh.cp
dataset or the scripts generating it? I couldn't find it online. That would be much appreciated.
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