Python Ganomaly.test Exemples

Exemple #1

Fichier : test.py Projet : deepstore/ganomaly

def test():
    ##
    # ARGUMENTS
    opt = Options().parse()
    ##
    # LOAD DATA
    dataloader = load_data(opt)
    ##
    # LOAD MODEL
    model = Ganomaly(opt, dataloader)
    ##
    # test model
    performance = model.test()
    print(performance)

Exemple #2

Fichier : test.py Projet : RForestLiu/ganomaly_s

def test():
    """ Training
    """

    ##
    # ARGUMENTS
    opt = Options().parse()
    ##
    # LOAD DATA
    dataloader = load_data(opt)
    ##
    # LOAD MODEL
    model = Ganomaly(opt, dataloader)
    ##
    # MODEL TEST
    res = model.test()

    print('AUC:%f\n' % res['AUC'])

Exemple #3

Fichier : train_z.py Projet : RForestLiu/ganomaly_s

def train():
    """ Training
    """

    ##
    # ARGUMENTS
    opt = Options().parse()
    ##
    # LOAD DATA
    dataloader = load_data(opt)
    ##
    # LOAD MODEL
    model = Ganomaly(opt, dataloader)
    ##
    # MODEL TEST
    res = model.test()

    model.z_train()

Exemple #4

def test():
    """ Testing
    """
    dataset = 'cus_mnist'
    #dataroot = './data/cus_mnist'
    opt = Options().parse(dataset)
    opt.isTrain = False
    opt.load_weights = True

    ##
    # LOAD DATA
    dataloader = load_data(opt)
    print(opt)
    ##
    # LOAD MODEL
    model = Ganomaly(opt, dataloader)

    print(model.test())

Exemple #5

Fichier : train.py Projet : kuzhang/CVproject

def train():
    """ Training
    """

    ##
    # ARGUMENTS
    opt = Options().parse()
    ##
    # LOAD DATA
    dataloader = load_data(opt)
    ##
    # LOAD MODEL
    model = Ganomaly(opt, dataloader)
    ##
    if opt.phase == 'train':
        # TRAIN MODEL
        model.train()
    elif opt.phase =='test':
        performance=model.test()
        print(performance)

Exemple #6

Fichier : test1.py Projet : kerviasx/ganomaly-waibao

    def test(self):
        self.textEdit.append('开始测试，得出阈值...')

        """ Testing
        """
        dataset = 'cus_mnist'
        # dataroot = './data/cus_mnist'
        opt = Options().parse(dataset)
        opt.isTrain = False
        opt.load_weights = True

        ##
        # LOAD DATA
        dataloader = load_data(opt)
        print(opt)
        ##
        # LOAD MODEL
        opt.showProcess = self.progressBar
        opt.showText = self.textEdit
        model = Ganomaly(opt, dataloader)

        print(model.test())

Exemple #7

os.chdir('E:\ganomly')
from options import Options
from lib.data import load_data
from lib.model import Ganomaly
from lib.evaluate import roc

##
# def main():
opt = Options().parse()
dataloader = load_data(opt)
model = Ganomaly(opt, dataloader)
torch.cuda.empty_cache() 
model.train()

# Test out the model: 
per, an, gt, dat = model.test()

def assessment(an, gt, dat):
    groundtruth = an.cpu().data.numpy()
    anomaly = gt.cpu().data.numpy()
    
    id_u = []
    for i in np.array(dat):
        id_u.append(i)
    
    id_s = []
    for i in id_u: 
        for j in i:
            j = j[-26:]
            id_s.append(j)
    

Exemple #8

from lib.model import Ganomaly

##
# def main():
""" Training
"""

##
# ARGUMENTS
opt = Options().parse()

##
# LOAD DATA
dataloader = load_data(opt)

##
# LOAD MODEL
model = Ganomaly(opt, dataloader)

##
# TRAIN MODEL
if opt.phase == 'train':
    opt.logger.info('train')
    model.train()
else:
    opt.logger.info('test')
    model.test()

# if __name__ == '__main__':
#     main()