wehub-resource-sync
89 lines
2.7 KiB
Go
89 lines
2.7 KiB
Go
package backend
|
|
|
|
import (
|
|
"context"
|
|
"fmt"
|
|
"sort"
|
|
|
|
"github.com/mudler/LocalAI/core/config"
|
|
"github.com/mudler/LocalAI/core/schema"
|
|
|
|
grpcPkg "github.com/mudler/LocalAI/pkg/grpc"
|
|
"github.com/mudler/LocalAI/pkg/grpc/proto"
|
|
"github.com/mudler/LocalAI/pkg/model"
|
|
)
|
|
|
|
// SoundDetectionRequest carries the knobs the HTTP layer collects for an
|
|
// audio-tagging / sound-event-classification call. Audio is the path to the
|
|
// uploaded clip on disk; TopK and Threshold are optional (0 = backend default).
|
|
type SoundDetectionRequest struct {
|
|
Audio string
|
|
TopK int32
|
|
Threshold float32
|
|
}
|
|
|
|
func (r *SoundDetectionRequest) toProto() *proto.SoundDetectionRequest {
|
|
return &proto.SoundDetectionRequest{
|
|
Src: r.Audio,
|
|
TopK: r.TopK,
|
|
Threshold: r.Threshold,
|
|
}
|
|
}
|
|
|
|
func loadSoundDetectionModel(ml *model.ModelLoader, modelConfig config.ModelConfig, appConfig *config.ApplicationConfig) (grpcPkg.Backend, error) {
|
|
if modelConfig.Backend == "" {
|
|
return nil, fmt.Errorf("sound classification: model %q has no backend set; supported backends include ced", modelConfig.Name)
|
|
}
|
|
opts := ModelOptions(modelConfig, appConfig)
|
|
m, err := ml.Load(opts...)
|
|
if err != nil {
|
|
recordModelLoadFailure(appConfig, modelConfig.Name, modelConfig.Backend, err, nil)
|
|
return nil, err
|
|
}
|
|
if m == nil {
|
|
return nil, fmt.Errorf("could not load sound classification model")
|
|
}
|
|
return m, nil
|
|
}
|
|
|
|
// ModelSoundDetection runs the SoundDetection RPC against the configured
|
|
// backend and returns a normalized schema.SoundClassificationResult.
|
|
func ModelSoundDetection(ctx context.Context, req SoundDetectionRequest, ml *model.ModelLoader, modelConfig config.ModelConfig, appConfig *config.ApplicationConfig) (*schema.SoundClassificationResult, error) {
|
|
m, err := loadSoundDetectionModel(ml, modelConfig, appConfig)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
|
|
r, err := m.SoundDetection(ctx, req.toProto())
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return soundClassificationResultFromProto(modelConfig.Name, r), nil
|
|
}
|
|
|
|
// soundClassificationResultFromProto maps the backend detections to the
|
|
// HTTP-facing schema, keeping the backend's score-descending order.
|
|
func soundClassificationResultFromProto(modelName string, r *proto.SoundDetectionResponse) *schema.SoundClassificationResult {
|
|
out := &schema.SoundClassificationResult{
|
|
Model: modelName,
|
|
Detections: []schema.SoundClassification{},
|
|
}
|
|
if r == nil {
|
|
return out
|
|
}
|
|
for _, d := range r.Detections {
|
|
if d == nil {
|
|
continue
|
|
}
|
|
out.Detections = append(out.Detections, schema.SoundClassification{
|
|
Index: int(d.Index),
|
|
Label: d.Label,
|
|
Score: d.Score,
|
|
})
|
|
}
|
|
sort.SliceStable(out.Detections, func(i, j int) bool {
|
|
return out.Detections[i].Score > out.Detections[j].Score
|
|
})
|
|
return out
|
|
}
|