Python PoseRegression Examples

Example #1

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.PoseRegression as System

if __name__ == '__main__':
    scene = 'indoor/apt1-kitchen'
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        #trainer_file= '../relative_pnp.yaml',
        #trainer_file='../self_multiscale_depth_trainer.yaml',
        trainer_file='../nn_index.yaml',
        #trainer_file='../pnp-5-images.yaml',
        #trainer_file='../pnp-1-image.yaml',
        dataset_file='../../../../datasets/' + scene + '.yaml',
        cnn_type='../multiscale_cnn.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)

Example #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.PoseRegression as System

if __name__ == '__main__':
    machine = System.Default(
        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()
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == '':
        machine.train()
        machine.test()
    else:
        raise ValueError('Unknown cmd: {}'.format(action))

Example #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.PoseRegression as System

if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(
        sys.argv[0])[:-len(sys.argv[0])],
                             trainer_file='trainer_depth.yaml',
                             dataset_file='../../datasets/aug_full.yaml',
                             cnn_type='cnn.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()

Example #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.PoseRegression as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        trainer_file='trainer.yaml',
        #trainer_file='feat_trainer.yaml',
        dataset_file='../../../../Exp_ICIP/datasets/heads.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()

Example #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.PoseRegression as System

if __name__ == '__main__':
    scene = 'chess'
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        #trainer_file='../../feat_trainer.yaml',
        trainer_file='trainer.yaml',
        dataset_file='../../../datasets/' + scene + '.yaml',
        #cnn_type='../cnn.yaml'
        cnn_type='../vladcnn.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':

Example #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.PoseRegression as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        #trainer_file='trainer.yaml',
        trainer_file='icp_trainer.yaml',
        dataset_file='../datasets/heads224.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()

Example #7

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.PoseRegression as System


if __name__ == '__main__':
    machine = System.MultNet(root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
                             #trainer_file='posenet_trainer.yaml',
                             trainer_file='trainer.yaml',
                             dataset_file='../datasets/seq_heads.yaml'
                             #dataset_file = '../datasets/minimal_heads.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()

Example #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.PoseRegression 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()
    elif action == 'p':
        machine.plot(print_loss=False, print_val=False)
    elif action == 'P':
        machine.plot()
    elif action == 'm':
        machine.map_print()
    elif action == 'mf':
        machine.map_print(final=True)
    elif action == '':
        machine.train()
        machine.test()

Example #9

#!/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.PoseRegression as System

if __name__ == '__main__':
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        #trainer_file='posenet_trainer.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 == 'ef':
        machine.test_on_final()
        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 == 'm':

Example #10

#!/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.PoseRegression as System

if __name__ == '__main__':
    scene = 'self-sup/KingsCollege'
    machine = System.MultNet(
        root=os.path.abspath(sys.argv[0])[:-len(sys.argv[0])],
        # trainer_file='../../feat_trainer.yaml',
        # trainer_file= 'trainer.yaml',
        trainer_file='self_multiscale_depth_trainer.yaml',
        dataset_file='../../../datasets/' + scene + '.yaml',
        cnn_type='../../multiscale_cnn.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 == 'ef':
        machine.test_on_final()
        machine.plot(print_loss=False, print_val=False)
    elif action == 'p':