def setup_method(self):
"""
Set up parameters for test methods
"""
Logger.init()
Logger.remove_file_logger()
self.params = DmdsParams()
# get one entry from the database
Config.add_config('./config.ini')
collection_details = ("local_mongodb", "depth", "driving_stereo")
scenes = [
"2018-10-26-15-24-18",
"2018-10-19-09-30-39",
]
self.train_data = []
self.val_data = []
self.collection_details = []
# get ids
for scene_token in scenes:
td, vd = load_ids(collection_details,
data_split=(80, 20),
limit=100,
shuffle_data=False,
mongodb_filter={"scene_token": scene_token},
sort_by={"timestamp": 1})
self.train_data.append(td)
self.val_data.append(vd)
self.collection_details.append(collection_details)
def setup_method(self):
Logger.init()
Logger.remove_file_logger()
self.params = CenternetParams(len(OD_CLASS_MAPPING))
self.params.REGRESSION_FIELDS["l_shape"].active = True
self.params.REGRESSION_FIELDS["3d_info"].active = True
# get some entries from the database
Config.add_config('./config.ini')
self.collection_details = ("local_mongodb", "labels", "nuscenes_train")
# Create Data Generators
self.train_data, self.val_data = load_ids(self.collection_details,
data_split=(70, 30),
limit=250)
def setup_method(self):
"""
Set up parameters for test methods
"""
Logger.init()
Logger.remove_file_logger()
self.params = SemsegParams()
# get one entry from the database
Config.add_config('./config.ini')
self.collection_details = ("local_mongodb", "labels", "comma10k")
# Create Data Generators
self.train_data, self.val_data = load_ids(self.collection_details,
data_split=(70, 30),
limit=30)
def setup_method(self):
Logger.init()
Logger.remove_file_logger()
self.params = MultitaskParams(len(OD_CLASS_MAPPING.items()))
# get one entry from the database
Config.add_config('./config.ini')
self.collection_details = ("local_mongodb", "labels", "nuscenes_train")
# Create Data Generators
self.td, self.vd = load_ids(
self.collection_details,
data_split=(70, 30),
shuffle_data=True,
limit=30
)
def setup_method(self):
"""
Set up parameters for test methods
"""
Logger.init()
Logger.remove_file_logger()
self.params = CentertrackerParams(len(OD_CLASS_MAPPING))
# get some entries from the database
Config.add_config('./config.ini')
self.collection_details = ("local_mongodb", "labels", "kitti")
# Create Data Generators
self.train_data, self.val_data = load_ids(
self.collection_details,
data_split=(70, 30),
limit=100
)
def setup_method(self):
"""
Set up parameters for test methods
"""
Logger.init()
Logger.remove_file_logger()
self.params = Params()
# get one entry from the database
Config.add_config('./config.ini')
collection_details = ("local_mongodb", "labels", "nuscenes_train")
# get ids
td, vd = load_ids(
collection_details,
data_split=(70, 30),
limit=100,
shuffle_data=True,
)
self.train_data = [td]
self.val_data = [vd]
self.collection_details = [collection_details]
def make_custom_callbacks(keras_model, show_pygame):
original_train_step = keras_model.train_step
def call_custom_callbacks(original_data):
data = data_adapter.expand_1d(original_data)
x, y_true, w = data_adapter.unpack_x_y_sample_weight(data)
y_pred = keras_model(x, training=True)
result = original_train_step(original_data)
# custom stuff called during training
show_pygame.show(x, y_true, y_pred)
return result
return call_custom_callbacks
if __name__ == "__main__":
Logger.init()
Logger.remove_file_logger()
params = MultitaskParams(len(OD_CLASS_MAPPING.items()))
Config.add_config('./config.ini')
con = ("local_mongodb", "labels", "nuscenes_train")
td, vd = load_ids(
con,
data_split=(90, 10),
shuffle_data=True
)
train_data = [td]
val_data = [vd]
import json
from common.constants import Constants
from common.utils import Logger, printInfo, printWarning, printError
from common.scheduler.scheduler import JobScheduler
from feed import Feed
from brain import Brain
if __name__ == '__main__':
# load config file
with open(Constants.CONFIG_FILE) as config_file:
config = json.load(config_file)
printInfo('Loading config:')
printInfo(config)
# initialize logger
Logger.init(Constants.LOG_FOLDER)
# initialize trading brain
Brain.init()
# setup data feed pulling
scheduler = JobScheduler(
instance_id = "data_feed",
job_execution_interval_in_seconds = Constants.FEED_EXECUTION_FREEQUENCY)
job_list = []
job_list.append(Feed(config))
scheduler.addJobs(job_list)
printInfo('Setting up data feed pulling. Will execute every ' + str(Constants.FEED_EXECUTION_FREEQUENCY) + ' seconds..')
scheduler.run()