Upload 3 files

inference_pb2.py

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+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: inference.proto
+# Protobuf Python Version: 5.26.1
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import symbol_database as _symbol_database
+from google.protobuf.internal import builder as _builder
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\x0finference.proto\x12\tinference\"\x92\x01\n\x0fHairSwapRequest\x12\x0c\n\x04\x66\x61\x63\x65\x18\x01 \x01(\x0c\x12\r\n\x05shape\x18\x02 \x01(\x0c\x12\r\n\x05\x63olor\x18\x03 \x01(\x0c\x12\x10\n\x08\x62lending\x18\x04 \x01(\t\x12\x15\n\rpoisson_iters\x18\x05 \x01(\x05\x12\x17\n\x0fpoisson_erosion\x18\x06 \x01(\x05\x12\x11\n\tuse_cache\x18\x07 \x01(\x08\"!\n\x10HairSwapResponse\x12\r\n\x05image\x18\x01 \x01(\x0c\x32R\n\x0fHairSwapService\x12?\n\x04swap\x12\x1a.inference.HairSwapRequest\x1a\x1b.inference.HairSwapResponseb\x06proto3')
+
+_globals = globals()
+_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
+_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'inference_pb2', _globals)
+if not _descriptor._USE_C_DESCRIPTORS:
+  DESCRIPTOR._loaded_options = None
+  _globals['_HAIRSWAPREQUEST']._serialized_start=31
+  _globals['_HAIRSWAPREQUEST']._serialized_end=177
+  _globals['_HAIRSWAPRESPONSE']._serialized_start=179
+  _globals['_HAIRSWAPRESPONSE']._serialized_end=212
+  _globals['_HAIRSWAPSERVICE']._serialized_start=214
+  _globals['_HAIRSWAPSERVICE']._serialized_end=296
+# @@protoc_insertion_point(module_scope)

inference_pb2.pyi

@@ -0,0 +1,29 @@
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import message as _message
+from typing import ClassVar as _ClassVar, Optional as _Optional
+
+DESCRIPTOR: _descriptor.FileDescriptor
+
+class HairSwapRequest(_message.Message):
+    __slots__ = ("face", "shape", "color", "blending", "poisson_iters", "poisson_erosion", "use_cache")
+    FACE_FIELD_NUMBER: _ClassVar[int]
+    SHAPE_FIELD_NUMBER: _ClassVar[int]
+    COLOR_FIELD_NUMBER: _ClassVar[int]
+    BLENDING_FIELD_NUMBER: _ClassVar[int]
+    POISSON_ITERS_FIELD_NUMBER: _ClassVar[int]
+    POISSON_EROSION_FIELD_NUMBER: _ClassVar[int]
+    USE_CACHE_FIELD_NUMBER: _ClassVar[int]
+    face: bytes
+    shape: bytes
+    color: bytes
+    blending: str
+    poisson_iters: int
+    poisson_erosion: int
+    use_cache: bool
+    def __init__(self, face: _Optional[bytes] = ..., shape: _Optional[bytes] = ..., color: _Optional[bytes] = ..., blending: _Optional[str] = ..., poisson_iters: _Optional[int] = ..., poisson_erosion: _Optional[int] = ..., use_cache: bool = ...) -> None: ...
+
+class HairSwapResponse(_message.Message):
+    __slots__ = ("image",)
+    IMAGE_FIELD_NUMBER: _ClassVar[int]
+    image: bytes
+    def __init__(self, image: _Optional[bytes] = ...) -> None: ...

inference_pb2_grpc.py

@@ -0,0 +1,101 @@
+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+import warnings
+
+import inference_pb2 as inference__pb2
+
+GRPC_GENERATED_VERSION = '1.63.0'
+GRPC_VERSION = grpc.__version__
+EXPECTED_ERROR_RELEASE = '1.65.0'
+SCHEDULED_RELEASE_DATE = 'June 25, 2024'
+_version_not_supported = False
+
+try:
+    from grpc._utilities import first_version_is_lower
+    _version_not_supported = first_version_is_lower(GRPC_VERSION, GRPC_GENERATED_VERSION)
+except ImportError:
+    _version_not_supported = True
+
+if _version_not_supported:
+    warnings.warn(
+        f'The grpc package installed is at version {GRPC_VERSION},'
+        + f' but the generated code in inference_pb2_grpc.py depends on'
+        + f' grpcio>={GRPC_GENERATED_VERSION}.'
+        + f' Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}'
+        + f' or downgrade your generated code using grpcio-tools<={GRPC_VERSION}.'
+        + f' This warning will become an error in {EXPECTED_ERROR_RELEASE},'
+        + f' scheduled for release on {SCHEDULED_RELEASE_DATE}.',
+        RuntimeWarning
+    )
+
+
+class HairSwapServiceStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.swap = channel.unary_unary(
+                '/inference.HairSwapService/swap',
+                request_serializer=inference__pb2.HairSwapRequest.SerializeToString,
+                response_deserializer=inference__pb2.HairSwapResponse.FromString,
+                _registered_method=True)
+
+
+class HairSwapServiceServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def swap(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_HairSwapServiceServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'swap': grpc.unary_unary_rpc_method_handler(
+                    servicer.swap,
+                    request_deserializer=inference__pb2.HairSwapRequest.FromString,
+                    response_serializer=inference__pb2.HairSwapResponse.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'inference.HairSwapService', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+
+
+ # This class is part of an EXPERIMENTAL API.
+class HairSwapService(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def swap(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,
+            '/inference.HairSwapService/swap',
+            inference__pb2.HairSwapRequest.SerializeToString,
+            inference__pb2.HairSwapResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True)