def get_save_dir_from_config(config_file_name):
""" Returns the configuration's save_dir
"""
param_pretrain = paramStruct()
param_pretrain.loadParam(config_file_name, verbose=False)
pathconf_pretrain = pathConfig()
# check the results directory to see if we are working on this
# configuration already
pathconf_pretrain.setupTrain(param_pretrain, 0)
save_dir_pretrain = pathconf_pretrain.result
return save_dir_pretrain
def get_save_dir_from_config(config_file_name):
""" Returns the configuration's save_dir
"""
param_pretrain = paramStruct()
param_pretrain.loadParam(config_file_name,
verbose=False)
pathconf_pretrain = pathConfig()
# check the results directory to see if we are working on this
# configuration already
pathconf_pretrain.setupTrain(param_pretrain, 0)
save_dir_pretrain = pathconf_pretrain.result
return save_dir_pretrain
def load_data(self, param, image_file_name, kp_file_name):
print(' --------------------------------------------------- ')
print(' Test Data Module ')
print(' --------------------------------------------------- ')
pathconf = pathConfig()
pathconf.setupTrain(param, 0)
cur_data = self.load_data_for_set(
pathconf, param, image_file_name, kp_file_name)
self.x = cur_data[0]
self.y = cur_data[1]
self.ID = cur_data[2]
self.pos = cur_data[3]
self.angle = cur_data[4]
self.coords = cur_data[5]
print(' -- Loading finished')
output_file = sys.argv[4]
bDumpPatch = bool(int(sys.argv[5]))
if len(sys.argv) >= 7:
bPrintTime = bool(int(sys.argv[6]))
else:
bPrintTime = False
if len(sys.argv) >= 8:
model_dir = sys.argv[7]
else:
model_dir = None
# ------------------------------------------------------------------------
# Setup and load parameters
param = paramStruct()
param.loadParam(config_file, verbose=True)
pathconf = pathConfig()
pathconf.setupTrain(param, 0)
# Overwrite with hard-coded base model
setattr(param.model, "descriptor_export_folder",
os.getenv("_LIFT_BASE_PATH", "") + "/models/base")
# Use model dir if given
if model_dir is not None:
pathconf.result = model_dir
# -------------------------------------------------------------------------
# Modify the network so that we bypass the keypoint part and the
# orientation part
param.model.sDetector = 'bypass'
# This ensures that you don't create unecessary scale space
output_file = sys.argv[4]
bDumpPatch = bool(int(sys.argv[5]))
if len(sys.argv) >= 7:
bPrintTime = bool(int(sys.argv[6]))
else:
bPrintTime = False
if len(sys.argv) >= 8:
model_dir = sys.argv[7]
else:
model_dir = None
# ------------------------------------------------------------------------
# Setup and load parameters
param = paramStruct()
param.loadParam(config_file, verbose=True)
pathconf = pathConfig()
pathconf.setupTrain(param, 0)
# Use model dir if given
if model_dir is not None:
pathconf.result = model_dir
# -------------------------------------------------------------------------
# Modify the network so that we bypass the keypoint part and the
# descriptor part.
param.model.sDetector = 'bypass'
# This ensures that you don't create unecessary scale space
param.model.fScaleList = np.array([1.0])
param.patch.fMaxScale = np.max(param.model.fScaleList)
# this ensures that you don't over eliminate features at boundaries
param.model.nPatchSize = int(np.round(param.model.nDescInputSize) *