package localai import ( "cmp" "net/http" "github.com/labstack/echo/v4" "github.com/mudler/LocalAI/core/backend" "github.com/mudler/LocalAI/core/config" "github.com/mudler/LocalAI/core/http/middleware" "github.com/mudler/LocalAI/core/schema" "github.com/mudler/LocalAI/core/services/facerecognition" "github.com/mudler/LocalAI/pkg/model" "github.com/mudler/xlog" ) // defaultIdentifyThreshold is the cosine-distance cutoff applied when // the client does not specify one. Tuned for buffalo_l ArcFace R50; // other recognizers (e.g. SFace) should override it explicitly. const defaultIdentifyThreshold = float32(0.35) // FaceIdentifyEndpoint runs 1:N identification against the registered store. // @Summary Identify a face against the registered database (1:N recognition). // @Tags face-recognition // @Param request body schema.FaceIdentifyRequest true "query params" // @Success 200 {object} schema.FaceIdentifyResponse "Response" // @Router /v1/face/identify [post] func FaceIdentifyEndpoint(cl *config.ModelConfigLoader, ml *model.ModelLoader, appConfig *config.ApplicationConfig, registry facerecognition.Registry) echo.HandlerFunc { return func(c echo.Context) error { input, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_LOCALAI_REQUEST).(*schema.FaceIdentifyRequest) if !ok || input.Model == "" { return echo.ErrBadRequest } cfg, ok := c.Get(middleware.CONTEXT_LOCALS_KEY_MODEL_CONFIG).(*config.ModelConfig) if !ok || cfg == nil { return echo.ErrBadRequest } img, err := decodeImageInput(input.Img) if err != nil { return err } topK := cmp.Or(input.TopK, 5) threshold := cmp.Or(input.Threshold, defaultIdentifyThreshold) xlog.Debug("FaceIdentify", "model", cfg.Name, "topK", topK, "threshold", threshold) probe, err := backend.FaceEmbed(c.Request().Context(), img, ml, appConfig, *cfg) if err != nil { return mapBackendError(err) } matches, err := registry.Identify(c.Request().Context(), probe, topK) if err != nil { return err } response := schema.FaceIdentifyResponse{ Matches: make([]schema.FaceIdentifyMatch, len(matches)), } for i, m := range matches { confidence := (1 - m.Distance/threshold) * 100 if confidence < 0 { confidence = 0 } if confidence > 100 { confidence = 100 } response.Matches[i] = schema.FaceIdentifyMatch{ ID: m.ID, Name: m.Metadata.Name, Labels: m.Metadata.Labels, Distance: m.Distance, Confidence: confidence, Match: m.Distance <= threshold, } } return c.JSON(http.StatusOK, response) } }