本文提供两种实现方案，接口设计完全一致（人员登记、多样本、单人/多人识别、统计等）：
方案一：基于 go-face （dlib），需要编译 CGO 依赖，特征为 128 维，使用欧氏距离分类 方案二（推荐，效果更好）：基于 go-insightface （SCRFD 检测 + ArcFace 特征提取），纯 Go + ONNX Runtime 动态加载，无需 CGO/OpenCV，特征为 512 维，使用余弦相似度 + Top-1/Top-2 margin 精确匹配，识别精度显著更高 方案一：基于 go-face（dlib） 需要下载相关的模型 https://github.com/Kagami/go-face-testdata 下面的models
代码如下
package main import ( "encoding/base64" "encoding/json" "errors" "fmt" "io" "log" "math" "net/http" "os" "path/filepath" "strconv" "sync" "time" "unsafe" "github.com/Kagami/go-face" "github.com/gorilla/mux" ) // Config 配置结构 type Config struct { Port string `json:"port"` ModelsDir string `json:"models_dir"` UploadsDir string `json:"uploads_dir"` TempDir string `json:"temp_dir"` DataFile string `json:"data_file"` MaxFileSize int64 `json:"max_file_size"` DefaultThreshold float32 `json:"default_threshold"` LogLevel string `json:"log_level"` } // Person 人员结构（支持多样本） type Person struct { ID int `json:"id"` Name string `json:"name"` Samples []FaceSample `json:"samples"` Created time.Time `json:"created"` Updated time.Time `json:"updated"` } // FaceSample 人脸样本 type FaceSample struct { ID int `json:"id"` PersonID int `json:"person_id"` Descriptor string `json:"descriptor"` // base64编码的特征向量 ImagePath string `json:"image_path"` ImageURL string `json:"image_url"` Quality float32 `json:"quality"` // 人脸质量评分 Created time.Time `json:"created"` } // RecognitionResult 识别结果 type RecognitionResult struct { PersonID int `json:"person_id"` PersonName string `json:"person_name"` Confidence float32 `json:"confidence"` Distance float32 `json:"distance"` SampleID int `json:"sample_id"` } // FaceDetection 人脸检测结果 type FaceDetection struct { Index int `json:"index"` Rectangle map[string]int `json:"rectangle"` Recognized bool `json:"recognized"` Result *RecognitionResult `json:"result,omitempty"` Message string `json:"message,omitempty"` } // Response 通用响应结构 type Response struct { Success bool `json:"success"` Message string `json:"message"` Data interface{} `json:"data,omitempty"` Timestamp time.Time `json:"timestamp"` } // Statistics 统计信息 type Statistics struct { TotalPersons int `json:"total_persons"` TotalSamples int `json:"total_samples"` RecognitionCount int `json:"recognition_count"` RegistrationCount int `json:"registration_count"` } // FaceService 人脸识别服务 type FaceService struct { config *Config recognizer *face.Recognizer persons map[int]*Person samples map[int]*FaceSample mu sync.RWMutex nextPersonID int nextSampleID int stats Statistics // 用于分类的数据 classifierSamples []face.Descriptor classifierCats []int32 classifierLabels []string } // NewFaceService 初始化人脸识别服务 func NewFaceService(config *Config) (*FaceService, error) { // 初始化人脸识别器 rec, err := face.NewRecognizer(config.ModelsDir) if err != nil { return nil, fmt.Errorf("无法初始化人脸识别器: %v", err) } // 创建必要的目录 dirs := []string{config.UploadsDir, config.TempDir} for _, dir := range dirs { if err := os.MkdirAll(dir, 0755); err != nil { return nil, fmt.Errorf("创建目录 %s 失败: %v", dir, err) } } fs := &FaceService{ config: config, recognizer: rec, persons: make(map[int]*Person), samples: make(map[int]*FaceSample), nextPersonID: 1, nextSampleID: 1, classifierSamples: make([]face.Descriptor, 0), classifierCats: make([]int32, 0), classifierLabels: make([]string, 0), } // 加载已保存的数据 if err := fs.loadData(); err != nil { log.Printf("加载数据失败: %v", err) } return fs, nil } // Close 关闭资源 func (fs *FaceService) Close() { fs.recognizer.Close() } // 数据持久化相关方法 func (fs *FaceService) saveData() error { fs.mu.RLock() defer fs.mu.RUnlock() data := struct { Persons map[int]*Person `json:"persons"` Samples map[int]*FaceSample `json:"samples"` NextPersonID int `json:"next_person_id"` NextSampleID int `json:"next_sample_id"` Stats Statistics `json:"stats"` }{ Persons: fs.persons, Samples: fs.samples, NextPersonID: fs.nextPersonID, NextSampleID: fs.nextSampleID, Stats: fs.stats, } file, err := os.Create(fs.config.DataFile) if err != nil { return err } defer file.Close() encoder := json.NewEncoder(file) encoder.SetIndent("", " ") return encoder.Encode(data) } func (fs *FaceService) loadData() error { if _, err := os.Stat(fs.config.DataFile); os.IsNotExist(err) { return nil // 文件不存在，使用默认值 } file, err := os.Open(fs.config.DataFile) if err != nil { return err } defer file.Close() var data struct { Persons map[int]*Person `json:"persons"` Samples map[int]*FaceSample `json:"samples"` NextPersonID int `json:"next_person_id"` NextSampleID int `json:"next_sample_id"` Stats Statistics `json:"stats"` } if err := json.NewDecoder(file).Decode(&data); err != nil { return err } fs.mu.Lock() fs.persons = data.Persons fs.samples = data.Samples fs.nextPersonID = data.NextPersonID fs.nextSampleID = data.NextSampleID fs.stats = data.Stats fs.mu.Unlock() // 重建分类器 fs.updateClassifier() log.Printf("加载数据成功: %d个人员, %d个样本", len(fs.persons), len(fs.samples)) return nil } // 特征向量转换方法 func descriptorToString(d face.Descriptor) string { b := (*[128 * 4]byte)(unsafe.Pointer(&d)) return base64.StdEncoding.EncodeToString(b[:]) } func stringToDescriptor(s string) (face.Descriptor, error) { b, err := base64.StdEncoding.DecodeString(s) if err != nil { return face.Descriptor{}, err } if len(b) != 128*4 { return face.Descriptor{}, fmt.Errorf("invalid descriptor length: %d", len(b)) } return *(*face.Descriptor)(unsafe.Pointer(&b[0])), nil } // 计算人脸质量评分（简单实现） func (fs *FaceService) calculateFaceQuality(faceData face.Face) float32 { // 基于人脸区域大小和位置计算质量评分 rect := faceData.Rectangle width := rect.Max.X - rect.Min.X height := rect.Max.Y - rect.Min.Y area := width * height // 面积越大，质量越高（简化评分） quality := float32(area) / 10000.0 if quality > 1.0 { quality = 1.0 } return quality } // 更新分类器 func (fs *FaceService) updateClassifier() { fs.classifierSamples = make([]face.Descriptor, 0) fs.classifierCats = make([]int32, 0) fs.classifierLabels = make([]string, 0) catID := int32(0) for _, person := range fs.persons { for _, sample := range person.Samples { descriptor, err := stringToDescriptor(sample.Descriptor) if err != nil { log.Printf("解析样本 %d 的特征向量失败: %v", sample.ID, err) continue } fs.classifierSamples = append(fs.classifierSamples, descriptor) fs.classifierCats = append(fs.classifierCats, catID) fs.classifierLabels = append(fs.classifierLabels, fmt.Sprintf("%d:%d", person.ID, sample.ID)) catID++ } } if len(fs.classifierSamples) > 0 { fs.recognizer.SetSamples(fs.classifierSamples, fs.classifierCats) log.Printf("分类器更新完成: %d个样本", len(fs.classifierSamples)) } } // RegisterPerson 人员登记接口 func (fs *FaceService) RegisterPerson(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPost { fs.sendErrorResponse(w, "只支持POST方法", http.StatusMethodNotAllowed) return } // 解析表单数据 err := r.ParseMultipartForm(fs.config.MaxFileSize) if err != nil { fs.sendErrorResponse(w, "解析表单失败", http.StatusBadRequest) return } // 获取姓名 name := r.FormValue("name") if name == "" { fs.sendErrorResponse(w, "姓名不能为空", http.StatusBadRequest) return } // 检查姓名是否已存在 fs.mu.RLock() for _, person := range fs.persons { if person.Name == name { fs.mu.RUnlock() fs.sendErrorResponse(w, "该姓名已存在", http.StatusConflict) return } } fs.mu.RUnlock() // 获取上传的图片文件 file, handler, err := r.FormFile("image") if err != nil { fs.sendErrorResponse(w, "获取图片文件失败", http.StatusBadRequest) return } defer file.Close() // 处理图片并创建样本 sample, err := fs.processImageFile(file, handler, 0) // personID为0，稍后更新 if err != nil { fs.sendErrorResponse(w, err.Error(), http.StatusBadRequest) return } // 创建人员记录 fs.mu.Lock() person := &Person{ ID: fs.nextPersonID, Name: name, Samples: []FaceSample{*sample}, Created: time.Now(), Updated: time.Now(), } // 更新样本的人员ID sample.PersonID = person.ID fs.persons[person.ID] = person fs.samples[sample.ID] = sample fs.nextPersonID++ fs.stats.TotalPersons++ fs.stats.TotalSamples++ fs.stats.RegistrationCount++ // 更新分类器 fs.updateClassifier() fs.mu.Unlock() // 保存数据 go fs.saveData() fs.sendSuccessResponse(w, "人员登记成功", map[string]interface{}{ "person_id": person.ID, "name": person.Name, "sample_id": sample.ID, "image_url": sample.ImageURL, "quality": sample.Quality, }) } // AddSample 为已存在人员添加样本 func (fs *FaceService) AddSample(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPost { fs.sendErrorResponse(w, "只支持POST方法", http.StatusMethodNotAllowed) return } vars := mux.Vars(r) personIDStr := vars["person_id"] personID, err := strconv.Atoi(personIDStr) if err != nil { fs.sendErrorResponse(w, "无效的人员ID", http.StatusBadRequest) return } // 检查人员是否存在 fs.mu.RLock() person, exists := fs.persons[personID] if !exists { fs.mu.RUnlock() fs.sendErrorResponse(w, "人员不存在", http.StatusNotFound) return } fs.mu.RUnlock() // 解析表单数据 err = r.ParseMultipartForm(fs.config.MaxFileSize) if err != nil { fs.sendErrorResponse(w, "解析表单失败", http.StatusBadRequest) return } // 获取上传的图片文件 file, handler, err := r.FormFile("image") if err != nil { fs.sendErrorResponse(w, "获取图片文件失败", http.StatusBadRequest) return } defer file.Close() // 处理图片并创建样本 sample, err := fs.processImageFile(file, handler, personID) if err != nil { fs.sendErrorResponse(w, err.Error(), http.StatusBadRequest) return } // 添加样本 fs.mu.Lock() person.Samples = append(person.Samples, *sample) person.Updated = time.Now() fs.samples[sample.ID] = sample fs.stats.TotalSamples++ // 更新分类器 fs.updateClassifier() fs.mu.Unlock() // 保存数据 go fs.saveData() fs.sendSuccessResponse(w, "样本添加成功", map[string]interface{}{ "person_id": personID, "sample_id": sample.ID, "image_url": sample.ImageURL, "quality": sample.Quality, "total_samples": len(person.Samples), }) } // processImageFile 处理上传的图片文件 func (fs *FaceService) processImageFile(file io.Reader, handler *multipart.FileHeader, personID int) (*FaceSample, error) { // 生成文件名 ext := filepath.Ext(handler.Filename) if ext == "" { ext = ".jpg" } fs.mu.Lock() sampleID := fs.nextSampleID fs.nextSampleID++ fs.mu.Unlock() savedImagePath := filepath.Join(fs.config.UploadsDir, fmt.Sprintf("sample_%d%s", sampleID, ext)) imageURL := fmt.Sprintf("/uploads/sample_%d%s", sampleID, ext) // 保存图片文件 dst, err := os.Create(savedImagePath) if err != nil { return nil, fmt.Errorf("保存图片失败: %v", err) } defer dst.Close() _, err = io.Copy(dst, file) if err != nil { os.Remove(savedImagePath) return nil, fmt.Errorf("保存图片失败: %v", err) } // 人脸识别 faceResult, err := fs.recognizer.RecognizeSingleFile(savedImagePath) if err != nil { os.Remove(savedImagePath) var imageLoadError face.ImageLoadError if errors.As(err, &imageLoadError) { return nil, fmt.Errorf("图片格式不支持或已损坏") } return nil, fmt.Errorf("人脸识别失败: %v", err) } if faceResult == nil { os.Remove(savedImagePath) return nil, fmt.Errorf("未检测到人脸") } // 计算人脸质量 quality := fs.calculateFaceQuality(*faceResult) // 创建样本 sample := &FaceSample{ ID: sampleID, PersonID: personID, Descriptor: descriptorToString(faceResult.Descriptor), ImagePath: savedImagePath, ImageURL: imageURL, Quality: quality, Created: time.Now(), } return sample, nil } // RecognizeFace 人脸识别接口 func (fs *FaceService) RecognizeFace(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPost { fs.sendErrorResponse(w, "只支持POST方法", http.StatusMethodNotAllowed) return } // 解析表单数据 err := r.ParseMultipartForm(fs.config.MaxFileSize) if err != nil { fs.sendErrorResponse(w, "解析表单失败", http.StatusBadRequest) return } // 获取阈值参数 threshold := fs.config.DefaultThreshold if thresholdStr := r.FormValue("threshold"); thresholdStr != "" { if t, err := strconv.ParseFloat(thresholdStr, 32); err == nil { threshold = float32(t) } } // 处理上传的图片 tempFile, err := fs.saveTemporaryFile(r) if err != nil { fs.sendErrorResponse(w, err.Error(), http.StatusBadRequest) return } defer os.Remove(tempFile) fs.mu.RLock() if len(fs.persons) == 0 { fs.mu.RUnlock() fs.sendErrorResponse(w, "暂无已登记的人脸数据", http.StatusBadRequest) return } fs.mu.RUnlock() // 识别人脸 detectedFace, err := fs.recognizer.RecognizeSingleFile(tempFile) if err != nil { var imageLoadError face.ImageLoadError if errors.As(err, &imageLoadError) { fs.sendErrorResponse(w, "图片格式不支持或已损坏", http.StatusBadRequest) } else { fs.sendErrorResponse(w, "人脸识别失败", http.StatusInternalServerError) } return } if detectedFace == nil { fs.sendErrorResponse(w, "未检测到人脸", http.StatusBadRequest) return } // 执行分类 result := fs.classifyFace(detectedFace.Descriptor, threshold) fs.mu.Lock() fs.stats.RecognitionCount++ fs.mu.Unlock() go fs.saveData() if result == nil { fs.sendSuccessResponse(w, "未找到匹配的人脸", map[string]interface{}{ "recognized": false, }) } else { fs.sendSuccessResponse(w, "人脸识别成功", map[string]interface{}{ "recognized": true, "result": result, }) } } // RecognizeMultipleFaces 多人脸识别接口 func (fs *FaceService) RecognizeMultipleFaces(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPost { fs.sendErrorResponse(w, "只支持POST方法", http.StatusMethodNotAllowed) return } // 解析表单数据 err := r.ParseMultipartForm(fs.config.MaxFileSize) if err != nil { fs.sendErrorResponse(w, "解析表单失败", http.StatusBadRequest) return } // 获取阈值参数 threshold := fs.config.DefaultThreshold if thresholdStr := r.FormValue("threshold"); thresholdStr != "" { if t, err := strconv.ParseFloat(thresholdStr, 32); err == nil { threshold = float32(t) } } // 处理上传的图片 tempFile, err := fs.saveTemporaryFile(r) if err != nil { fs.sendErrorResponse(w, err.Error(), http.StatusBadRequest) return } defer os.Remove(tempFile) fs.mu.RLock() if len(fs.persons) == 0 { fs.mu.RUnlock() fs.sendErrorResponse(w, "暂无已登记的人脸数据", http.StatusBadRequest) return } fs.mu.RUnlock() // 识别所有人脸 faces, err := fs.recognizer.RecognizeFile(tempFile) if err != nil { var imageLoadError face.ImageLoadError if errors.As(err, &imageLoadError) { fs.sendErrorResponse(w, "图片格式不支持或已损坏", http.StatusBadRequest) } else { fs.sendErrorResponse(w, "人脸识别失败", http.StatusInternalServerError) } return } if len(faces) == 0 { fs.sendErrorResponse(w, "未检测到人脸", http.StatusBadRequest) return } // 处理每个检测到的人脸 var detections []FaceDetection for i, detectedFace := range faces { detection := FaceDetection{ Index: i, Rectangle: map[string]int{ "left": detectedFace.Rectangle.Min.X, "top": detectedFace.Rectangle.Min.Y, "right": detectedFace.Rectangle.Max.X, "bottom": detectedFace.Rectangle.Max.Y, }, } // 尝试识别 result := fs.classifyFace(detectedFace.Descriptor, threshold) if result != nil { detection.Recognized = true detection.Result = result } else { detection.Recognized = false detection.Message = "未找到匹配的人脸" } detections = append(detections, detection) } fs.mu.Lock() fs.stats.RecognitionCount++ fs.mu.Unlock() go fs.saveData() fs.sendSuccessResponse(w, fmt.Sprintf("检测到%d张人脸", len(faces)), detections) } // classifyFace 分类人脸 func (fs *FaceService) classifyFace(descriptor face.Descriptor, threshold float32) *RecognitionResult { fs.mu.RLock() defer fs.mu.RUnlock() if len(fs.classifierSamples) == 0 { return nil } catID := fs.recognizer.ClassifyThreshold(descriptor, threshold) if catID < 0 || catID >= len(fs.classifierLabels) { return nil } // 解析标签（格式：personID:sampleID） label := fs.classifierLabels[catID] var personID, sampleID int if n, err := fmt.Sscanf(label, "%d:%d", &personID, &sampleID); n != 2 || err != nil { return nil } person, personExists := fs.persons[personID] sample, sampleExists := fs.samples[sampleID] if !personExists || !sampleExists { return nil } // 计算相似度 sampleDescriptor, err := stringToDescriptor(sample.Descriptor) if err != nil { return nil } distance := fs.calculateDistance(descriptor, sampleDescriptor) confidence := (1 - distance) * 100 if confidence < 0 { confidence = 0 } return &RecognitionResult{ PersonID: person.ID, PersonName: person.Name, Confidence: confidence, Distance: distance, SampleID: sample.ID, } } // calculateDistance 计算欧几里得距离 func (fs *FaceService) calculateDistance(desc1, desc2 face.Descriptor) float32 { var sum float64 for i := 0; i < len(desc1); i++ { diff := float64(desc1[i] - desc2[i]) sum += diff * diff } return float32(math.Sqrt(sum)) } // saveTemporaryFile 保存临时文件 func (fs *FaceService) saveTemporaryFile(r *http.Request) (string, error) { file, handler, err := r.FormFile("image") if err != nil { return "", fmt.Errorf("获取图片文件失败: %v", err) } defer file.Close() tempFile := filepath.Join(fs.config.TempDir, fmt.Sprintf("temp_%d_%s", time.Now().UnixNano(), handler.Filename)) dst, err := os.Create(tempFile) if err != nil { return "", fmt.Errorf("创建临时文件失败: %v", err) } defer dst.Close() _, err = io.Copy(dst, file) if err != nil { os.Remove(tempFile) return "", fmt.Errorf("保存图片失败: %v", err) } return tempFile, nil } // GetPersonList 获取人员列表 func (fs *FaceService) GetPersonList(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodGet { fs.sendErrorResponse(w, "只支持GET方法", http.StatusMethodNotAllowed) return } fs.mu.RLock() defer fs.mu.RUnlock() var personList []map[string]interface{} for _, person := range fs.persons { personInfo := map[string]interface{}{ "id": person.ID, "name": person.Name, "sample_count": len(person.Samples), "created": person.Created, "updated": person.Updated, } // 添加样本信息 var samples []map[string]interface{} for _, sample := range person.Samples { samples = append(samples, map[string]interface{}{ "id": sample.ID, "image_url": sample.ImageURL, "quality": sample.Quality, "created": sample.Created, }) } personInfo["samples"] = samples personList = append(personList, personInfo) } fs.sendSuccessResponse(w, "获取成功", personList) } // DeletePerson 删除人员 func (fs *FaceService) DeletePerson(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodDelete { fs.sendErrorResponse(w, "只支持DELETE方法", http.StatusMethodNotAllowed) return } vars := mux.Vars(r) personIDStr := vars["person_id"] personID, err := strconv.Atoi(personIDStr) if err != nil { fs.sendErrorResponse(w, "无效的人员ID", http.StatusBadRequest) return } fs.mu.Lock() defer fs.mu.Unlock() person, exists := fs.persons[personID] if !exists { fs.sendErrorResponse(w, "人员不存在", http.StatusNotFound) return } // 删除所有样本文件和数据 for _, sample := range person.Samples { if sample.ImagePath != "" { if err := os.Remove(sample.ImagePath); err != nil { log.Printf("删除图片文件失败: %v", err) } } delete(fs.samples, sample.ID) fs.stats.TotalSamples-- } // 删除人员数据 delete(fs.persons, personID) fs.stats.TotalPersons-- // 更新分类器 fs.updateClassifier() // 保存数据 go fs.saveData() fs.sendSuccessResponse(w, "删除成功", nil) } // DeleteSample 删除样本 func (fs *FaceService) DeleteSample(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodDelete { fs.sendErrorResponse(w, "只支持DELETE方法", http.StatusMethodNotAllowed) return } vars := mux.Vars(r) sampleIDStr := vars["sample_id"] sampleID, err := strconv.Atoi(sampleIDStr) if err != nil { fs.sendErrorResponse(w, "无效的样本ID", http.StatusBadRequest) return } fs.mu.Lock() defer fs.mu.Unlock() sample, exists := fs.samples[sampleID] if !exists { fs.sendErrorResponse(w, "样本不存在", http.StatusNotFound) return } person, personExists := fs.persons[sample.PersonID] if !personExists { fs.sendErrorResponse(w, "关联的人员不存在", http.StatusNotFound) return } // 检查是否为最后一个样本 if len(person.Samples) <= 1 { fs.sendErrorResponse(w, "不能删除最后一个样本，请删除整个人员", http.StatusBadRequest) return } // 删除图片文件 if sample.ImagePath != "" { if err := os.Remove(sample.ImagePath); err != nil { log.Printf("删除图片文件失败: %v", err) } } // 从人员的样本列表中移除 for i, s := range person.Samples { if s.ID == sampleID { person.Samples = append(person.Samples[:i], person.Samples[i+1:]...) break } } person.Updated = time.Now() // 删除样本数据 delete(fs.samples, sampleID) fs.stats.TotalSamples-- // 更新分类器 fs.updateClassifier() // 保存数据 go fs.saveData() fs.sendSuccessResponse(w, "样本删除成功", nil) } // GetStatistics 获取统计信息 func (fs *FaceService) GetStatistics(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodGet { fs.sendErrorResponse(w, "只支持GET方法", http.StatusMethodNotAllowed) return } fs.mu.RLock() stats := fs.stats fs.mu.RUnlock() fs.sendSuccessResponse(w, "获取统计信息成功", stats) } // GetPersonDetail 获取人员详情 func (fs *FaceService) GetPersonDetail(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodGet { fs.sendErrorResponse(w, "只支持GET方法", http.StatusMethodNotAllowed) return } vars := mux.Vars(r) personIDStr := vars["person_id"] personID, err := strconv.Atoi(personIDStr) if err != nil { fs.sendErrorResponse(w, "无效的人员ID", http.StatusBadRequest) return } fs.mu.RLock() person, exists := fs.persons[personID] fs.mu.RUnlock() if !exists { fs.sendErrorResponse(w, "人员不存在", http.StatusNotFound) return } // 构建详细信息 personDetail := map[string]interface{}{ "id": person.ID, "name": person.Name, "sample_count": len(person.Samples), "created": person.Created, "updated": person.Updated, } // 添加样本详情 var samples []map[string]interface{} for _, sample := range person.Samples { samples = append(samples, map[string]interface{}{ "id": sample.ID, "image_url": sample.ImageURL, "quality": sample.Quality, "created": sample.Created, }) } personDetail["samples"] = samples fs.sendSuccessResponse(w, "获取人员详情成功", personDetail) } // UpdatePersonName 更新人员姓名 func (fs *FaceService) UpdatePersonName(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodPut { fs.sendErrorResponse(w, "只支持PUT方法", http.StatusMethodNotAllowed) return } vars := mux.Vars(r) personIDStr := vars["person_id"] personID, err := strconv.Atoi(personIDStr) if err != nil { fs.sendErrorResponse(w, "无效的人员ID", http.StatusBadRequest) return } // 解析JSON请求体 var requestData struct { Name string `json:"name"` } if err := json.NewDecoder(r.Body).Decode(&requestData); err != nil { fs.sendErrorResponse(w, "解析请求数据失败", http.StatusBadRequest) return } if requestData.Name == "" { fs.sendErrorResponse(w, "姓名不能为空", http.StatusBadRequest) return } fs.mu.Lock() defer fs.mu.Unlock() person, exists := fs.persons[personID] if !exists { fs.sendErrorResponse(w, "人员不存在", http.StatusNotFound) return } // 检查新姓名是否已存在 for _, p := range fs.persons { if p.ID != personID && p.Name == requestData.Name { fs.sendErrorResponse(w, "该姓名已存在", http.StatusConflict) return } } // 更新姓名 person.Name = requestData.Name person.Updated = time.Now() // 保存数据 go fs.saveData() fs.sendSuccessResponse(w, "姓名更新成功", map[string]interface{}{ "id": person.ID, "name": person.Name, }) } // HealthCheck 健康检查 func (fs *FaceService) HealthCheck(w http.ResponseWriter, r *http.Request) { if r.Method != http.MethodGet { fs.sendErrorResponse(w, "只支持GET方法", http.StatusMethodNotAllowed) return } fs.mu.RLock() totalPersons := len(fs.persons) totalSamples := len(fs.samples) fs.mu.RUnlock() fs.sendSuccessResponse(w, "服务正常", map[string]interface{}{ "status": "healthy", "total_persons": totalPersons, "total_samples": totalSamples, "timestamp": time.Now(), }) } // 响应辅助方法 func (fs *FaceService) sendSuccessResponse(w http.ResponseWriter, message string, data interface{}) { fs.sendResponse(w, true, message, data, http.StatusOK) } func (fs *FaceService) sendErrorResponse(w http.ResponseWriter, message string, statusCode int) { fs.sendResponse(w, false, message, nil, statusCode) } func (fs *FaceService) sendResponse(w http.ResponseWriter, success bool, message string, data interface{}, statusCode int) { w.Header().Set("Content-Type", "application/json") w.WriteHeader(statusCode) response := Response{ Success: success, Message: message, Data: data, Timestamp: time.Now(), } json.NewEncoder(w).Encode(response) } // 加载配置 func loadConfig(configPath string) (*Config, error) { // 默认配置 config := &Config{ Port: ":8080", ModelsDir: "models", UploadsDir: "uploads", TempDir: "temp", DataFile: "face_data.json", MaxFileSize: 10 << 20, // 10MB DefaultThreshold: 0.6, LogLevel: "info", } // 如果配置文件存在，则加载配置 if _, err := os.Stat(configPath); err == nil { file, err := os.Open(configPath) if err != nil { return nil, fmt.Errorf("打开配置文件失败: %v", err) } defer file.Close() if err := json.NewDecoder(file).Decode(config); err != nil { return nil, fmt.Errorf("解析配置文件失败: %v", err) } } return config, nil } // 定期保存数据的后台任务 func (fs *FaceService) startAutoSave() { go func() { ticker := time.NewTicker(5 * time.Minute) // 每5分钟保存一次 defer ticker.Stop() for range ticker.C { if err := fs.saveData(); err != nil { log.Printf("自动保存数据失败: %v", err) } } }() } func main() { // 加载配置 configPath := "config.json" if len(os.Args) > 1 { configPath = os.Args[1] } config, err := loadConfig(configPath) if err != nil { log.Printf("加载配置失败，使用默认配置: %v", err) config = &Config{ Port: ":8080", ModelsDir: "models", UploadsDir: "uploads", TempDir: "temp", DataFile: "face_data.json", MaxFileSize: 10 << 20, DefaultThreshold: 0.6, LogLevel: "info", } } // 初始化人脸识别服务 faceService, err := NewFaceService(config) if err != nil { log.Fatal("初始化人脸识别服务失败:", err) } defer faceService.Close() // 启动自动保存 faceService.startAutoSave() // 创建路由 r := mux.NewRouter() // API路由 api := r.PathPrefix("/api/v1").Subrouter() // 人员管理 api.HandleFunc("/person/register", faceService.RegisterPerson).Methods("POST") api.HandleFunc("/person/list", faceService.GetPersonList).Methods("GET") api.HandleFunc("/person/{person_id}", faceService.GetPersonDetail).Methods("GET") api.HandleFunc("/person/{person_id}", faceService.UpdatePersonName).Methods("PUT") api.HandleFunc("/person/{person_id}", faceService.DeletePerson).Methods("DELETE") // 样本管理 api.HandleFunc("/person/{person_id}/sample", faceService.AddSample).Methods("POST") api.HandleFunc("/sample/{sample_id}", faceService.DeleteSample).Methods("DELETE") // 识别接口 api.HandleFunc("/face/recognize", faceService.RecognizeFace).Methods("POST") api.HandleFunc("/face/recognize-multiple", faceService.RecognizeMultipleFaces).Methods("POST") // 统计和健康检查 api.HandleFunc("/statistics", faceService.GetStatistics).Methods("GET") api.HandleFunc("/health", faceService.HealthCheck).Methods("GET") // 静态文件服务 r.PathPrefix("/uploads/").Handler(http.StripPrefix("/uploads/", http.FileServer(http.Dir(config.UploadsDir)))) // CORS中间件 r.Use(func(next http.Handler) http.Handler { return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) { w.Header().Set("Access-Control-Allow-Origin", "*") w.Header().Set("Access-Control-Allow-Methods", "GET, POST, PUT, DELETE, OPTIONS") w.Header().Set("Access-Control-Allow-Headers", "Content-Type, Authorization") if r.Method == "OPTIONS" { w.WriteHeader(http.StatusOK) return } next.ServeHTTP(w, r) }) }) // 启动服务 fmt.Printf("=== 人脸识别服务启动 ===\n") fmt.Printf("端口: %s\n", config.Port) fmt.Printf("模型路径: %s\n", config.ModelsDir) fmt.Printf("上传目录: %s\n", config.UploadsDir) fmt.Printf("数据文件: %s\n", config.DataFile) fmt.Printf("默认阈值: %.2f\n", config.DefaultThreshold) fmt.Printf("最大文件大小: %d MB\n", config.MaxFileSize/(1024*1024)) fmt.Println("\n=== API接口列表 ===") fmt.Println("人员管理:") fmt.Println(" POST /api/v1/person/register - 人员登记") fmt.Println(" GET /api/v1/person/list - 获取人员列表") fmt.Println(" GET /api/v1/person/{id} - 获取人员详情") fmt.Println(" PUT /api/v1/person/{id} - 更新人员姓名") fmt.Println(" DELETE /api/v1/person/{id} - 删除人员") fmt.Println("\n样本管理:") fmt.Println(" POST /api/v1/person/{id}/sample - 添加样本") fmt.Println(" DELETE /api/v1/sample/{id} - 删除样本") fmt.Println("\n识别接口:") fmt.Println(" POST /api/v1/face/recognize - 单人脸识别") fmt.Println(" POST /api/v1/face/recognize-multiple - 多人脸识别") fmt.Println("\n系统接口:") fmt.Println(" GET /api/v1/statistics - 获取统计信息") fmt.Println(" GET /api/v1/health - 健康检查") fmt.Println("\n静态文件:") fmt.Println(" GET /uploads/* - 图片文件访问") log.Fatal(http.ListenAndServe(config.Port, r)) 配置文件 (config.json)
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