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This commit is contained in:
landaiqing
2025-01-23 15:24:59 +08:00
parent c6af9a0461
commit fc95d73adb
27 changed files with 5117 additions and 269 deletions
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24
app/aisvc/rpc/aisvc.proto
View File

@@ -4,15 +4,35 @@ package ai;
option go_package = "./pb";
// 人脸识别
message FaceRecognitionRequest {
bytes face = 1;
string user_id = 2;
}
message FaceRecognitionResponse {
int64 face_id = 1;
int64 face_id = 3;
}
// tf分类识别
message TfClassificationRequest {
bytes image = 1;
}
message TfClassificationResponse {
string class_name = 2;
float score = 3;
}
// caffe分类识别
message CaffeClassificationRequest {
bytes image = 1;
}
message CaffeClassificationResponse {
string class_name = 2;
float score = 3;
}
service AiService {
// FaceRecognition
rpc FaceRecognition (FaceRecognitionRequest) returns (FaceRecognitionResponse);
// TfClassification
rpc TfClassification (TfClassificationRequest) returns (TfClassificationResponse);
// CaffeClassification
rpc CaffeClassification (CaffeClassificationRequest) returns (CaffeClassificationResponse);
}

24
app/aisvc/rpc/client/aiservice/ai_service.go
View File

@@ -14,12 +14,20 @@ import (
)
type (
FaceRecognitionRequest = pb.FaceRecognitionRequest
FaceRecognitionResponse = pb.FaceRecognitionResponse
CaffeClassificationRequest = pb.CaffeClassificationRequest
CaffeClassificationResponse = pb.CaffeClassificationResponse
FaceRecognitionRequest = pb.FaceRecognitionRequest
FaceRecognitionResponse = pb.FaceRecognitionResponse
TfClassificationRequest = pb.TfClassificationRequest
TfClassificationResponse = pb.TfClassificationResponse
AiService interface {
// FaceRecognition
FaceRecognition(ctx context.Context, in *FaceRecognitionRequest, opts ...grpc.CallOption) (*FaceRecognitionResponse, error)
// TfClassification
TfClassification(ctx context.Context, in *TfClassificationRequest, opts ...grpc.CallOption) (*TfClassificationResponse, error)
// CaffeClassification
CaffeClassification(ctx context.Context, in *CaffeClassificationRequest, opts ...grpc.CallOption) (*CaffeClassificationResponse, error)
}
defaultAiService struct {
@@ -38,3 +46,15 @@ func (m *defaultAiService) FaceRecognition(ctx context.Context, in *FaceRecognit
client := pb.NewAiServiceClient(m.cli.Conn())
return client.FaceRecognition(ctx, in, opts...)
}
// TfClassification
func (m *defaultAiService) TfClassification(ctx context.Context, in *TfClassificationRequest, opts ...grpc.CallOption) (*TfClassificationResponse, error) {
client := pb.NewAiServiceClient(m.cli.Conn())
return client.TfClassification(ctx, in, opts...)
}
// CaffeClassification
func (m *defaultAiService) CaffeClassification(ctx context.Context, in *CaffeClassificationRequest, opts ...grpc.CallOption) (*CaffeClassificationResponse, error) {
client := pb.NewAiServiceClient(m.cli.Conn())
return client.CaffeClassification(ctx, in, opts...)
}

6
app/aisvc/rpc/etc/aisvc.yaml
View File

@@ -1,9 +1,11 @@
Name: aisvc.rpc
ListenOn: 0.0.0.0:8080
ListenOn: 0.0.0.0:8888
Etcd:
Hosts:
- 127.0.0.1:2379
- 1.95.0.111:2379
Key: aisvc.rpc
User: root
Pass: LDQ20020618xxx
# MySQL 配置
Mysql:
# 数据源dsn

31
app/aisvc/rpc/internal/logic/aiservice/caffe_classification_logic.go Normal file
View File

@@ -0,0 +1,31 @@
package aiservicelogic
import (
"context"
"schisandra-album-cloud-microservices/app/aisvc/rpc/internal/svc"
"schisandra-album-cloud-microservices/app/aisvc/rpc/pb"
"github.com/zeromicro/go-zero/core/logx"
)
type CaffeClassificationLogic struct {
ctx context.Context
svcCtx *svc.ServiceContext
logx.Logger
}
func NewCaffeClassificationLogic(ctx context.Context, svcCtx *svc.ServiceContext) *CaffeClassificationLogic {
return &CaffeClassificationLogic{
ctx: ctx,
svcCtx: svcCtx,
Logger: logx.WithContext(ctx),
}
}
// CaffeClassification
func (l *CaffeClassificationLogic) CaffeClassification(in *pb.CaffeClassificationRequest) (*pb.CaffeClassificationResponse, error) {
// todo: add your logic here and delete this line
return &pb.CaffeClassificationResponse{}, nil
}

28
app/aisvc/rpc/internal/logic/aiservice/face_recognition_logic.go
View File

@@ -43,8 +43,12 @@ func NewFaceRecognitionLogic(ctx context.Context, svcCtx *svc.ServiceContext) *F
// FaceRecognition 人脸识别
func (l *FaceRecognitionLogic) FaceRecognition(in *pb.FaceRecognitionRequest) (*pb.FaceRecognitionResponse, error) {
toJPEG, err := l.ConvertImageToJPEG(in.GetFace())
if err != nil {
return nil, err
}
// 提取人脸特征
faceFeatures, err := l.svcCtx.FaceRecognizer.RecognizeSingle(in.GetFace())
faceFeatures, err := l.svcCtx.FaceRecognizer.RecognizeSingle(toJPEG)
if err != nil {
return nil, err
}
@@ -82,7 +86,7 @@ func (l *FaceRecognitionLogic) FaceRecognition(in *pb.FaceRecognitionRequest) (*
// 人脸分类
classify := l.svcCtx.FaceRecognizer.ClassifyThreshold(faceFeatures.Descriptor, 0.6)
if classify >= 0 {
if classify >= 0 && classify < len(ids) {
return &pb.FaceRecognitionResponse{
FaceId: int64(ids[classify]),
}, nil
@@ -92,6 +96,26 @@ func (l *FaceRecognitionLogic) FaceRecognition(in *pb.FaceRecognitionRequest) (*
return l.saveNewFace(in, faceFeatures, hashKey)
}
// ConvertImageToJPEG 将非 JPEG 格式的图片字节数据转换为 JPEG
func (l *FaceRecognitionLogic) ConvertImageToJPEG(imageData []byte) ([]byte, error) {
// 使用 image.Decode 解码图像数据
img, _, err := image.Decode(bytes.NewReader(imageData))
if err != nil {
return nil, fmt.Errorf("failed to decode image: %v", err)
}
// 创建一个缓冲区来存储 JPEG 格式的数据
var jpegBuffer bytes.Buffer
// 将图片编码为 JPEG 格式
err = jpeg.Encode(&jpegBuffer, img, nil)
if err != nil {
return nil, fmt.Errorf("failed to encode image to JPEG: %v", err)
}
return jpegBuffer.Bytes(), nil
}
// 保存新的人脸样本到数据库和 Redis
func (l *FaceRecognitionLogic) saveNewFace(in *pb.FaceRecognitionRequest, faceFeatures *face.Face, hashKey string) (*pb.FaceRecognitionResponse, error) {
// 人脸有效性判断 (大小必须大于50)

79
app/aisvc/rpc/internal/logic/aiservice/tf_classification_logic.go Normal file
View File

@@ -0,0 +1,79 @@
package aiservicelogic
import (
"context"
"fmt"
"gocv.io/x/gocv"
"image"
"schisandra-album-cloud-microservices/app/aisvc/rpc/internal/svc"
"schisandra-album-cloud-microservices/app/aisvc/rpc/pb"
"github.com/zeromicro/go-zero/core/logx"
)
type TfClassificationLogic struct {
ctx context.Context
svcCtx *svc.ServiceContext
logx.Logger
}
func NewTfClassificationLogic(ctx context.Context, svcCtx *svc.ServiceContext) *TfClassificationLogic {
return &TfClassificationLogic{
ctx: ctx,
svcCtx: svcCtx,
Logger: logx.WithContext(ctx),
}
}
// TfClassification is a server endpoint to classify an image using TensorFlow.
func (l *TfClassificationLogic) TfClassification(in *pb.TfClassificationRequest) (*pb.TfClassificationResponse, error) {
className, source, err := l.ClassifyImage(in.GetImage())
if err != nil {
return nil, err
}
return &pb.TfClassificationResponse{
Score: source,
ClassName: className,
}, nil
}
// ClassifyImage 从字节数据分类图像，返回分类标签和最大概率值
func (l *TfClassificationLogic) ClassifyImage(imageBytes []byte) (string, float32, error) {
// 解码字节数据为图像
img, err := gocv.IMDecode(imageBytes, gocv.IMReadColor)
if err != nil || img.Empty() {
return "", 0, fmt.Errorf("failed to decode image: %v", err)
}
defer func(img *gocv.Mat) {
_ = img.Close()
}(&img)
// 将图像 Mat 转换为 224x224 blob，以便分类器分析
blob := gocv.BlobFromImage(img, 1.0, image.Pt(224, 224), gocv.NewScalar(0, 0, 0, 0), true, false)
// 将 blob 输入分类器
l.svcCtx.TfNet.SetInput(blob, "input")
// 运行网络的正向传递
prob := l.svcCtx.TfNet.Forward("softmax2")
// 将结果重塑为 1x1000 矩阵
probMat := prob.Reshape(1, 1)
// 确定最可能的分类
_, maxVal, _, maxLoc := gocv.MinMaxLoc(probMat)
// 获取分类描述
desc := ""
if maxLoc.X < 1000 {
desc = l.svcCtx.TfDesc[maxLoc.X]
}
// 清理资源
_ = blob.Close()
_ = prob.Close()
_ = probMat.Close()
return desc, maxVal, nil
}

12
app/aisvc/rpc/internal/server/aiservice/ai_service_server.go
View File

@@ -28,3 +28,15 @@ func (s *AiServiceServer) FaceRecognition(ctx context.Context, in *pb.FaceRecogn
l := aiservicelogic.NewFaceRecognitionLogic(ctx, s.svcCtx)
return l.FaceRecognition(in)
}
// TfClassification
func (s *AiServiceServer) TfClassification(ctx context.Context, in *pb.TfClassificationRequest) (*pb.TfClassificationResponse, error) {
l := aiservicelogic.NewTfClassificationLogic(ctx, s.svcCtx)
return l.TfClassification(in)
}
// CaffeClassification
func (s *AiServiceServer) CaffeClassification(ctx context.Context, in *pb.CaffeClassificationRequest) (*pb.CaffeClassificationResponse, error) {
l := aiservicelogic.NewCaffeClassificationLogic(ctx, s.svcCtx)
return l.CaffeClassification(in)
}

13
app/aisvc/rpc/internal/svc/service_context.go
View File

@@ -3,11 +3,14 @@ package svc
import (
"github.com/Kagami/go-face"
"github.com/redis/go-redis/v9"
"gocv.io/x/gocv"
"schisandra-album-cloud-microservices/app/aisvc/model/mysql"
"schisandra-album-cloud-microservices/app/aisvc/model/mysql/query"
"schisandra-album-cloud-microservices/app/aisvc/rpc/internal/config"
"schisandra-album-cloud-microservices/common/caffe_classifier"
"schisandra-album-cloud-microservices/common/face_recognizer"
"schisandra-album-cloud-microservices/common/redisx"
"schisandra-album-cloud-microservices/common/tf_classifier"
)
type ServiceContext struct {
@@ -15,15 +18,25 @@ type ServiceContext struct {
FaceRecognizer *face.Recognizer
DB *query.Query
RedisClient *redis.Client
TfNet *gocv.Net
TfDesc []string
CaffeNet *gocv.Net
CaffeDesc []string
}
func NewServiceContext(c config.Config) *ServiceContext {
redisClient := redisx.NewRedis(c.RedisConf.Host, c.RedisConf.Pass, c.RedisConf.DB)
_, queryDB := mysql.NewMySQL(c.Mysql.DataSource, c.Mysql.MaxOpenConn, c.Mysql.MaxIdleConn, redisClient)
tfClassifier, tfDesc := tf_classifier.NewTFClassifier()
caffeClassifier, caffeDesc := caffe_classifier.NewCaffeClassifier()
return &ServiceContext{
Config: c,
FaceRecognizer: face_recognizer.NewFaceRecognition(),
DB: queryDB,
RedisClient: redisClient,
TfNet: tfClassifier,
TfDesc: tfDesc,
CaffeNet: caffeClassifier,
CaffeDesc: caffeDesc,
}
}

268
app/aisvc/rpc/pb/aisvc.pb.go
View File

@@ -20,6 +20,7 @@ const (
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
// 人脸识别
type FaceRecognitionRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
@@ -78,7 +79,7 @@ type FaceRecognitionResponse struct {
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
FaceId int64 `protobuf:"varint,1,opt,name=face_id,json=faceId,proto3" json:"face_id,omitempty"`
FaceId int64 `protobuf:"varint,3,opt,name=face_id,json=faceId,proto3" json:"face_id,omitempty"`
}
func (x *FaceRecognitionResponse) Reset() {
@@ -118,6 +119,204 @@ func (x *FaceRecognitionResponse) GetFaceId() int64 {
return 0
}
// tf分类识别
type TfClassificationRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Image []byte `protobuf:"bytes,1,opt,name=image,proto3" json:"image,omitempty"`
}
func (x *TfClassificationRequest) Reset() {
*x = TfClassificationRequest{}
mi := &file_aisvc_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
func (x *TfClassificationRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*TfClassificationRequest) ProtoMessage() {}
func (x *TfClassificationRequest) ProtoReflect() protoreflect.Message {
mi := &file_aisvc_proto_msgTypes[2]
if x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use TfClassificationRequest.ProtoReflect.Descriptor instead.
func (*TfClassificationRequest) Descriptor() ([]byte, []int) {
return file_aisvc_proto_rawDescGZIP(), []int{2}
}
func (x *TfClassificationRequest) GetImage() []byte {
if x != nil {
return x.Image
}
return nil
}
type TfClassificationResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
ClassName string `protobuf:"bytes,2,opt,name=class_name,json=className,proto3" json:"class_name,omitempty"`
Score float32 `protobuf:"fixed32,3,opt,name=score,proto3" json:"score,omitempty"`
}
func (x *TfClassificationResponse) Reset() {
*x = TfClassificationResponse{}
mi := &file_aisvc_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
func (x *TfClassificationResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*TfClassificationResponse) ProtoMessage() {}
func (x *TfClassificationResponse) ProtoReflect() protoreflect.Message {
mi := &file_aisvc_proto_msgTypes[3]
if x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use TfClassificationResponse.ProtoReflect.Descriptor instead.
func (*TfClassificationResponse) Descriptor() ([]byte, []int) {
return file_aisvc_proto_rawDescGZIP(), []int{3}
}
func (x *TfClassificationResponse) GetClassName() string {
if x != nil {
return x.ClassName
}
return ""
}
func (x *TfClassificationResponse) GetScore() float32 {
if x != nil {
return x.Score
}
return 0
}
// caffe分类识别
type CaffeClassificationRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
Image []byte `protobuf:"bytes,1,opt,name=image,proto3" json:"image,omitempty"`
}
func (x *CaffeClassificationRequest) Reset() {
*x = CaffeClassificationRequest{}
mi := &file_aisvc_proto_msgTypes[4]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
func (x *CaffeClassificationRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CaffeClassificationRequest) ProtoMessage() {}
func (x *CaffeClassificationRequest) ProtoReflect() protoreflect.Message {
mi := &file_aisvc_proto_msgTypes[4]
if x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use CaffeClassificationRequest.ProtoReflect.Descriptor instead.
func (*CaffeClassificationRequest) Descriptor() ([]byte, []int) {
return file_aisvc_proto_rawDescGZIP(), []int{4}
}
func (x *CaffeClassificationRequest) GetImage() []byte {
if x != nil {
return x.Image
}
return nil
}
type CaffeClassificationResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
ClassName string `protobuf:"bytes,2,opt,name=class_name,json=className,proto3" json:"class_name,omitempty"`
Score float32 `protobuf:"fixed32,3,opt,name=score,proto3" json:"score,omitempty"`
}
func (x *CaffeClassificationResponse) Reset() {
*x = CaffeClassificationResponse{}
mi := &file_aisvc_proto_msgTypes[5]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
func (x *CaffeClassificationResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CaffeClassificationResponse) ProtoMessage() {}
func (x *CaffeClassificationResponse) ProtoReflect() protoreflect.Message {
mi := &file_aisvc_proto_msgTypes[5]
if x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use CaffeClassificationResponse.ProtoReflect.Descriptor instead.
func (*CaffeClassificationResponse) Descriptor() ([]byte, []int) {
return file_aisvc_proto_rawDescGZIP(), []int{5}
}
func (x *CaffeClassificationResponse) GetClassName() string {
if x != nil {
return x.ClassName
}
return ""
}
func (x *CaffeClassificationResponse) GetScore() float32 {
if x != nil {
return x.Score
}
return 0
}
var File_aisvc_proto protoreflect.FileDescriptor
var file_aisvc_proto_rawDesc = []byte{
@@ -128,15 +327,42 @@ var file_aisvc_proto_rawDesc = []byte{
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}
var (
@@ -151,16 +377,24 @@ func file_aisvc_proto_rawDescGZIP() []byte {
return file_aisvc_proto_rawDescData
}
var file_aisvc_proto_msgTypes = make([]protoimpl.MessageInfo, 2)
var file_aisvc_proto_msgTypes = make([]protoimpl.MessageInfo, 6)
var file_aisvc_proto_goTypes = []any{
(*FaceRecognitionRequest)(nil), // 0: ai.FaceRecognitionRequest
(*FaceRecognitionResponse)(nil), // 1: ai.FaceRecognitionResponse
(*FaceRecognitionRequest)(nil), // 0: ai.FaceRecognitionRequest
(*FaceRecognitionResponse)(nil), // 1: ai.FaceRecognitionResponse
(*TfClassificationRequest)(nil), // 2: ai.TfClassificationRequest
(*TfClassificationResponse)(nil), // 3: ai.TfClassificationResponse
(*CaffeClassificationRequest)(nil), // 4: ai.CaffeClassificationRequest
(*CaffeClassificationResponse)(nil), // 5: ai.CaffeClassificationResponse
}
var file_aisvc_proto_depIdxs = []int32{
0, // 0: ai.AiService.FaceRecognition:input_type -> ai.FaceRecognitionRequest
1, // 1: ai.AiService.FaceRecognition:output_type -> ai.FaceRecognitionResponse
1, // [1:2] is the sub-list for method output_type
0, // [0:1] is the sub-list for method input_type
2, // 1: ai.AiService.TfClassification:input_type -> ai.TfClassificationRequest
4, // 2: ai.AiService.CaffeClassification:input_type -> ai.CaffeClassificationRequest
1, // 3: ai.AiService.FaceRecognition:output_type -> ai.FaceRecognitionResponse
3, // 4: ai.AiService.TfClassification:output_type -> ai.TfClassificationResponse
5, // 5: ai.AiService.CaffeClassification:output_type -> ai.CaffeClassificationResponse
3, // [3:6] is the sub-list for method output_type
0, // [0:3] is the sub-list for method input_type
0, // [0:0] is the sub-list for extension type_name
0, // [0:0] is the sub-list for extension extendee
0, // [0:0] is the sub-list for field type_name
@@ -177,7 +411,7 @@ func file_aisvc_proto_init() {
GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_aisvc_proto_rawDesc,
NumEnums: 0,
NumMessages: 2,
NumMessages: 6,
NumExtensions: 0,
NumServices: 1,
},

82
app/aisvc/rpc/pb/aisvc_grpc.pb.go
View File

@@ -19,7 +19,9 @@ import (
const _ = grpc.SupportPackageIsVersion9
const (
AiService_FaceRecognition_FullMethodName = "/ai.AiService/FaceRecognition"
AiService_FaceRecognition_FullMethodName = "/ai.AiService/FaceRecognition"
AiService_TfClassification_FullMethodName = "/ai.AiService/TfClassification"
AiService_CaffeClassification_FullMethodName = "/ai.AiService/CaffeClassification"
)
// AiServiceClient is the client API for AiService service.
@@ -28,6 +30,10 @@ const (
type AiServiceClient interface {
// FaceRecognition
FaceRecognition(ctx context.Context, in *FaceRecognitionRequest, opts ...grpc.CallOption) (*FaceRecognitionResponse, error)
// TfClassification
TfClassification(ctx context.Context, in *TfClassificationRequest, opts ...grpc.CallOption) (*TfClassificationResponse, error)
// CaffeClassification
CaffeClassification(ctx context.Context, in *CaffeClassificationRequest, opts ...grpc.CallOption) (*CaffeClassificationResponse, error)
}
type aiServiceClient struct {
@@ -48,12 +54,36 @@ func (c *aiServiceClient) FaceRecognition(ctx context.Context, in *FaceRecogniti
return out, nil
}
func (c *aiServiceClient) TfClassification(ctx context.Context, in *TfClassificationRequest, opts ...grpc.CallOption) (*TfClassificationResponse, error) {
cOpts := append([]grpc.CallOption{grpc.StaticMethod()}, opts...)
out := new(TfClassificationResponse)
err := c.cc.Invoke(ctx, AiService_TfClassification_FullMethodName, in, out, cOpts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *aiServiceClient) CaffeClassification(ctx context.Context, in *CaffeClassificationRequest, opts ...grpc.CallOption) (*CaffeClassificationResponse, error) {
cOpts := append([]grpc.CallOption{grpc.StaticMethod()}, opts...)
out := new(CaffeClassificationResponse)
err := c.cc.Invoke(ctx, AiService_CaffeClassification_FullMethodName, in, out, cOpts...)
if err != nil {
return nil, err
}
return out, nil
}
// AiServiceServer is the server API for AiService service.
// All implementations must embed UnimplementedAiServiceServer
// for forward compatibility.
type AiServiceServer interface {
// FaceRecognition
FaceRecognition(context.Context, *FaceRecognitionRequest) (*FaceRecognitionResponse, error)
// TfClassification
TfClassification(context.Context, *TfClassificationRequest) (*TfClassificationResponse, error)
// CaffeClassification
CaffeClassification(context.Context, *CaffeClassificationRequest) (*CaffeClassificationResponse, error)
mustEmbedUnimplementedAiServiceServer()
}
@@ -67,6 +97,12 @@ type UnimplementedAiServiceServer struct{}
func (UnimplementedAiServiceServer) FaceRecognition(context.Context, *FaceRecognitionRequest) (*FaceRecognitionResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method FaceRecognition not implemented")
}
func (UnimplementedAiServiceServer) TfClassification(context.Context, *TfClassificationRequest) (*TfClassificationResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method TfClassification not implemented")
}
func (UnimplementedAiServiceServer) CaffeClassification(context.Context, *CaffeClassificationRequest) (*CaffeClassificationResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method CaffeClassification not implemented")
}
func (UnimplementedAiServiceServer) mustEmbedUnimplementedAiServiceServer() {}
func (UnimplementedAiServiceServer) testEmbeddedByValue() {}
@@ -106,6 +142,42 @@ func _AiService_FaceRecognition_Handler(srv interface{}, ctx context.Context, de
return interceptor(ctx, in, info, handler)
}
func _AiService_TfClassification_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(TfClassificationRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(AiServiceServer).TfClassification(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: AiService_TfClassification_FullMethodName,
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(AiServiceServer).TfClassification(ctx, req.(*TfClassificationRequest))
}
return interceptor(ctx, in, info, handler)
}
func _AiService_CaffeClassification_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(CaffeClassificationRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(AiServiceServer).CaffeClassification(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: AiService_CaffeClassification_FullMethodName,
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(AiServiceServer).CaffeClassification(ctx, req.(*CaffeClassificationRequest))
}
return interceptor(ctx, in, info, handler)
}
// AiService_ServiceDesc is the grpc.ServiceDesc for AiService service.
// It's only intended for direct use with grpc.RegisterService,
// and not to be introspected or modified (even as a copy)
@@ -117,6 +189,14 @@ var AiService_ServiceDesc = grpc.ServiceDesc{
MethodName: "FaceRecognition",
Handler: _AiService_FaceRecognition_Handler,
},
{
MethodName: "TfClassification",
Handler: _AiService_TfClassification_Handler,
},
{
MethodName: "CaffeClassification",
Handler: _AiService_CaffeClassification_Handler,
},
},
Streams: []grpc.StreamDesc{},
Metadata: "aisvc.proto",