def __vital_algorithm_register__():
"""
Note:
We may be able to refactor somethign like this
# In vital.py
def _register_algorithm(cls, name=None, desc=''):
if name is None:
name = cls.__name__
from vital.algo import algorithm_factory
if not algorithm_factory.has_algorithm_impl_name(cls.static_type_name(), name):
algorithm_factory.add_algorithm(name, desc, cls)
algorithm_factory.mark_algorithm_as_loaded(name)
def register_algorithm(name=None, desc=''):
'''
POC refactor of __vital_algorithm_register__ into a decorator
'''
def _wrapper(cls):
_register_algorithm(cls, name, desc)
return cls
return _wrapper
def lazy_register(cls, name=None, desc=''):
''' Alternate Proof-of-Concept '''
def __vital_algorithm_register__():
return _register_algorithm(cls, name, desc)
return __vital_algorithm_register__
# Then in your class
import vital
@vial.register_algorithm(desc="PyTorch Netharn classification routine")
class MyAlgorithm(BaseAlgo):
...
# OR if the currenty lazy structure is important
import vital
class MyAlgorithm(BaseAlgo):
...
__vital_algorithm_register__ = vital.lazy_register(MyAlgorithm, desc="PyTorch Netharn classification routine")
# We could also play with adding class member variables for the lazy
# initialization. There is lots of room to make this better / easier.
"""
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "netharn_classifier"
if not algorithm_factory.has_algorithm_impl_name(
NetharnClassifier.static_type_name(), implementation_name):
algorithm_factory.add_algorithm(
implementation_name, "PyTorch Netharn classification routine",
NetharnClassifier)
algorithm_factory.mark_algorithm_as_loaded(implementation_name)
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "SimpleImageObjectDetector"
if algorithm_factory.has_algorithm_impl_name(
SimpleImageObjectDetector.static_type_name(), implementation_name):
return
algorithm_factory.add_algorithm(implementation_name,
"test image object detector arrow",
SimpleImageObjectDetector)
algorithm_factory.mark_algorithm_as_loaded(implementation_name)
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "CascadeClassifier"
if algorithm_factory.has_algorithm_impl_name(
CascadeClassifier.static_type_name(), implementation_name):
return
algorithm_factory.add_algorithm(
implementation_name,
"Opencv implementation of Haar cascade classifier", CascadeClassifier)
algorithm_factory.mark_algorithm_as_loaded(implementation_name)
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "SimpleImageObjectDetector"
if algorithm_factory.has_algorithm_impl_name(
SimpleImageObjectDetector.static_type_name(),
implementation_name):
return
algorithm_factory.add_algorithm( implementation_name,
"test image object detector arrow",
SimpleImageObjectDetector )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "npy_percentile_norm"
if algorithm_factory.has_algorithm_impl_name(
PercentileNorm16BitTo8Bit.static_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"Numpy percentile normalization", PercentileNorm16BitTo8Bit )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "mmdet"
if algorithm_factory.has_algorithm_impl_name(
MMDetDetector.static_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"PyTorch MMDetection testing routine", MMDetDetector )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "netharn"
if algorithm_factory.has_algorithm_impl_name(
NetHarnTrainer.static_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"PyTorch NetHarn detection training routine", NetHarnTrainer )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "tensorflow"
if algorithm_factory.has_algorithm_impl_name(
TFDetector.static_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"Tensorflow detector testing routine", TFDetector )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "mmdet"
if algorithm_factory.has_algorithm_impl_name(
MMDetDetector.static_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"PyTorch MMDetection testing routine", MMDetDetector )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
bbox_int = bbox.astype( np.int32 )
bounding_box = BoundingBox( bbox_int[0], bbox_int[1],
bbox_int[2], bbox_int[3] )
detected_object_type = DetectedObjectType( label, 1.0 )
detected_object = DetectedObject( bounding_box,
np.max( class_confidence ),
detected_object_type )
output.add( detected_object )
return output
def __vital_algorithm_register__():
from vital.algo import algorithm_factory
# Register Algorithm
implementation_name = "@template@"
if algorithm_factory.has_algorithm_impl_name(
@[email protected]_type_name(), implementation_name ):
return
algorithm_factory.add_algorithm( implementation_name,
"@template@ dection inference routine", @template@Detector )
algorithm_factory.mark_algorithm_as_loaded( implementation_name )
