Exemplos de DescriptorLearning.MultNet em Python

Exemplo n.º 1

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)


import system.DescriptorLearning as System


if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])])
    action = input('Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n')
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'jet':
        machine.map_print()
    elif action == 'dataset':

Exemplo n.º 2

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)

import system.DescriptorLearning as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        dataset_file='../../../../datasets/lt_queries.yaml',
        trainer_file='../trainer.yaml')
    action = input(
        'Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n'
    )
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)

Exemplo n.º 3

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)

import system.DescriptorLearning as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        cnn_type='cnn.yaml',
        trainer_file='../trainer_ref_joint.yaml',
        dataset_file='../../../SummerTests/datasets/cmu_lt.yaml')
    action = input(
        'Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n'
    )
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()

Exemplo n.º 4

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)

import system.DescriptorLearning as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        cnn_type='cnn.yaml',
        dataset_file='../../../../../datasets/cmu_lt.yaml')
    action = input(
        'Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n'
    )
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)

Exemplo n.º 5

#!/usr/bin/env python
import os, sys
import setlog


conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)


import system.DescriptorLearning as System


if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
                             cnn_type='cnn.yaml',
                             trainer_file='../trainer_only_depth.yaml',
                             dataset_file='../../../SummerTests/datasets/snow_ft.yaml')
    action = input('Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n')
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)

Exemplo n.º 6

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)

import system.DescriptorLearning as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        dataset_file='../../../../datasets/cmu_training_depth.yaml',
        trainer_file='trainer.yaml')
    action = input(
        'Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n'
    )
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)

Exemplo n.º 7

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)

import system.DescriptorLearning as System

if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(
        sys.argv[0])[:-len(sys.argv[0])],
                             dataset_file='sparse_dataset.yaml')
    action = input(
        'Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n'
    )
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 's':

Exemplo n.º 8

#!/usr/bin/env python
import os, sys
import setlog

conf_file = os.environ['DEV'] + 'dl_management/.log/logging.yaml'
save_file = os.path.abspath(sys.argv[0])[:-len(sys.argv[0])] + 'log/'
setlog.reconfigure(conf_file, save_file)


import system.DescriptorLearning as System


if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
                             dataset_file='../../../SummerTests/datasets/cmu_lt.yaml',
                             trainer_file='../trainer_pca.yaml')
    action = input('Exec:\n[t]\ttrain\n[e]\ttest\n[p]\tprint (console)\n[P]\tprint (full)\n[ ]\ttrain+test\n')
    if action == 't':
        machine.train()
    elif action == 'e':
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
        machine.plot(print_loss=False, print_val=False)
    elif action == 's':