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ms_faceRecognition_pb2_grpc.py
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ms_faceRecognition_pb2_grpc.py
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# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import ms_faceRecognition_pb2 as ms__faceRecognition__pb2
class FaceRecognitionServiceStub(object):
"""This tells gRPC we have an InferenceServer service with an inference function, notice that we need to specify the type of the messages: InferenceRequest and InferenceReply
"repeated" means list of
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.Inference = channel.unary_unary(
'/faceRecognition.FaceRecognitionService/Inference',
request_serializer=ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
response_deserializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
)
self.InferenceWithoutDetection = channel.unary_unary(
'/faceRecognition.FaceRecognitionService/InferenceWithoutDetection',
request_serializer=ms__faceRecognition__pb2.FaceRecognitionWithRectListRequest.SerializeToString,
response_deserializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
)
self.FastInferenceWithDetection = channel.unary_unary(
'/faceRecognition.FaceRecognitionService/FastInferenceWithDetection',
request_serializer=ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
response_deserializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
)
self.AccurateInferenceWithDetection = channel.unary_unary(
'/faceRecognition.FaceRecognitionService/AccurateInferenceWithDetection',
request_serializer=ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
response_deserializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
)
class FaceRecognitionServiceServicer(object):
"""This tells gRPC we have an InferenceServer service with an inference function, notice that we need to specify the type of the messages: InferenceRequest and InferenceReply
"repeated" means list of
"""
def Inference(self, request, context):
"""Whatever
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def InferenceWithoutDetection(self, request, context):
"""Does inference on image based on the faces detected bounding box from a third party
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def FastInferenceWithDetection(self, request, context):
"""Does face detection and then face recognition, uses a fast face detection mode (ex: OpenCV)
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def AccurateInferenceWithDetection(self, request, context):
"""Does face detection and then face recognition, uses a accurate face detection mode, way slower than Opencv (ex: Retinaface)
"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def add_FaceRecognitionServiceServicer_to_server(servicer, server):
rpc_method_handlers = {
'Inference': grpc.unary_unary_rpc_method_handler(
servicer.Inference,
request_deserializer=ms__faceRecognition__pb2.FaceRecognitionRequest.FromString,
response_serializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.SerializeToString,
),
'InferenceWithoutDetection': grpc.unary_unary_rpc_method_handler(
servicer.InferenceWithoutDetection,
request_deserializer=ms__faceRecognition__pb2.FaceRecognitionWithRectListRequest.FromString,
response_serializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.SerializeToString,
),
'FastInferenceWithDetection': grpc.unary_unary_rpc_method_handler(
servicer.FastInferenceWithDetection,
request_deserializer=ms__faceRecognition__pb2.FaceRecognitionRequest.FromString,
response_serializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.SerializeToString,
),
'AccurateInferenceWithDetection': grpc.unary_unary_rpc_method_handler(
servicer.AccurateInferenceWithDetection,
request_deserializer=ms__faceRecognition__pb2.FaceRecognitionRequest.FromString,
response_serializer=ms__faceRecognition__pb2.FaceRecognitionInferenceReply.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'faceRecognition.FaceRecognitionService', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
# This class is part of an EXPERIMENTAL API.
class FaceRecognitionService(object):
"""This tells gRPC we have an InferenceServer service with an inference function, notice that we need to specify the type of the messages: InferenceRequest and InferenceReply
"repeated" means list of
"""
@staticmethod
def Inference(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/faceRecognition.FaceRecognitionService/Inference',
ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def InferenceWithoutDetection(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/faceRecognition.FaceRecognitionService/InferenceWithoutDetection',
ms__faceRecognition__pb2.FaceRecognitionWithRectListRequest.SerializeToString,
ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def FastInferenceWithDetection(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/faceRecognition.FaceRecognitionService/FastInferenceWithDetection',
ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
@staticmethod
def AccurateInferenceWithDetection(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/faceRecognition.FaceRecognitionService/AccurateInferenceWithDetection',
ms__faceRecognition__pb2.FaceRecognitionRequest.SerializeToString,
ms__faceRecognition__pb2.FaceRecognitionInferenceReply.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)