/
darpa_experiments.py
143 lines (102 loc) · 6.24 KB
/
darpa_experiments.py
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from starflow.protocols import Apply, Applies, protocolize
import deploy
import pythor_protocols as protocols
@Applies(deploy.images,args=('../config/darpa_heli_200_2500.py',False,('../../darpa/helidata/',)))
def generate_darpa_images():
Apply()
@protocolize()
def make_darpa_test_models(depends_on='../config/darpa_test_models.py'):
"""
"""
protocols.model_protocol(depends_on,parallel=False,write=True)
@protocolize()
def extract_darpa_test_models(depends_on=('../config/darpa_test_extraction.py',
'../config/darpa_test_models.py',
'../config/darpa_heli_200_2500.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,parallel=True,save_to_db=True,batch_size=100)
@Applies(deploy.images,args=('../config/darpa_heli_200_2500_enriched.py',False,('../../darpa/helidata/',)))
def generate_darpa_enriched_images():
Apply()
@protocolize()
def make_darpa_models(depends_on='../config/darpa_models.py'):
protocols.model_protocol(depends_on,parallel=False,write=True)
@protocolize()
def extract_darpa_models(depends_on=('../config/darpa_extraction.py',
'../config/darpa_models.py',
'../config/darpa_heli_200_2500_enriched.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,
parallel=True, save_to_db=True, batch_size=100)
@protocolize()
def screen_darpa_models(depends_on=('../config/darpa_screen_evaluation.py',
'../config/darpa_extraction.py',
'../config/darpa_models.py',
'../config/darpa_heli_200_2500_enriched.py')):
"""
"""
a,b,c,d = depends_on
protocols.evaluate_protocol(a,b,c,d, write=True,parallel=True,use_db = True)
@Applies(deploy.images,args=('../config/darpa_heli_optimalbbox_100000_enriched.py',False,('../../darpa/helidata/',)))
def generate_darpa_optimalbbox_images():
Apply()
@protocolize()
def make_optimal_darpa_models(depends_on='../config/darpa_optimal_models.py'):
protocols.model_protocol(depends_on,parallel=False,write=True)
@protocolize()
def extract_optimal_darpa_models(depends_on=('../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_optimalbbox_100000_enriched.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,parallel=True, save_to_db=True, batch_size=100)
@protocolize()
def train_optimal_darpa_models(depends_on=('../config/darpa_optimal_training.py',
'../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_optimalbbox_100000_enriched.py')):
a,b,c,d = depends_on
protocols.evaluate_protocol(a,b,c,d, write=True,parallel=False,use_db = True)
@protocolize()
def train_optimal_darpa_models_more_enriched(depends_on=('../config/darpa_optimal_training_more_enriched.py',
'../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_optimalbbox_100000_enriched.py')):
a,b,c,d = depends_on
protocols.evaluate_protocol(a,b,c,d, write=True,parallel=False,use_db = True)
@Applies(deploy.images,args=('../config/darpa_heli_test_optimalbbox_gridded.py',False,('../../darpa/helidata_test/',)))
def generate_darpa_test_optimalbbox_images():
Apply()
@Applies(deploy.images,args=('../config/darpa_heli_optimalbbox_gridded.py',False,('../../darpa/helidata/',)))
def generate_darpa_train_gridded_optimalbbox_images():
Apply()
@protocolize()
def extract_optimal_darpa_models_ontest(depends_on=('../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_test_optimalbbox_gridded.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,parallel=True, save_to_db=True, batch_size=100)
@Applies(deploy.images,args=('../config/darpa_heli_test_all_optimalbbox_gridded.py',False,('../../darpa/helidata_test_all/',)))
def generate_darpa_test_all_optimalbbox_images():
Apply()
@protocolize()
def extract_optimal_darpa_models_ontest_all(depends_on=('../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_test_all_optimalbbox_gridded.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,parallel=True, save_to_db=True, batch_size=200)
@Applies(deploy.images,args=('../config/darpa_heli_test_all_irobot.py',False,('../../darpa/helidata_test_all/','../../darpa/nv2_detections/')))
def generate_darpa_test_all_optimalbbox_images_irobot():
Apply()
@protocolize()
def extract_optimal_darpa_models_ontest_irobot(depends_on=('../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_test_all_irobot.py')):
a,b,c = depends_on
protocols.extraction_protocol(a,b,c,convolve_func_name='numpy', write=True,parallel=True, save_to_db=True, batch_size=200)
@protocolize()
def evaluate_optimal_darpa_models_ontest_irobot(depends_on=('../config/darpa_irobot_binary_task.py',
'../config/darpa_extraction.py',
'../config/darpa_optimal_models.py',
'../config/darpa_heli_test_all_irobot.py')):
a,b,c,d = depends_on
protocols.evaluate_protocol(a,b,c,d, write=True,parallel = False, use_db = True)