precise

package module

v0.0.0-...-e05d7e5 Latest Latest Go to latest Published: Jan 15, 2023 License: Apache-2.0 Imports: 7 Imported by: 0

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Repository

git.meow.tf/astra/precise

Documentation ¶

Index ¶

Variables
func LinSpace(start, stop float32, num int) (res *tensor.Dense)
type ActivationFunc
type ExitFunc
type Listener
- func NewListener(model Model, p Params) (*Listener, error)
- func (p *Listener) Close() error
- func (p *Listener) Update(audio []int16) (float32, error)
type Model
- func NewTFLiteModel(modelPath string) (Model, error)
type MuStd
- func (m MuStd) Calculate(value float32) []float32
- func (m MuStd) Max(maxZ float32) float32
- func (m MuStd) Min(minZ float32) float32
type Option
- func WithActivationFunc(f ActivationFunc) Option
- func WithDetectorOpts(opts ...TriggerOption) Option
- func WithExitFunc(f ExitFunc) Option
- func WithPredictionFunc(f PredictionFunc) Option
type Params
- func NewParams() Params
- func (p Params) BufferSamples() int
- func (p Params) HopSamples() int
- func (p Params) NFeatures() int
- func (p Params) WindowSamples() int
type PredictionFunc
type Runner
- func NewRunner(listener *Listener, chunkSize int, opts ...Option) *Runner
- func (r *Runner) Close() error
- func (r *Runner) Queue(samples []int16)
- func (r *Runner) ReadFrom(reader io.Reader) (int64, error)
- func (r *Runner) Start()
- func (r *Runner) Stop()
- func (r *Runner) Write(b []byte) (int, error)
type TFLiteModel
- func (m *TFLiteModel) Close() error
- func (m *TFLiteModel) Predict(inputData tensor.Tensor) (float32, error)
type ThresholdDecoder
- func NewThresholdDecoder(muStds MuStd, options ThresholdOptions) *ThresholdDecoder
- func (t *ThresholdDecoder) Decode(rawOutput float32) float32
type ThresholdOptions
type TriggerDetector
- func NewTriggerDetector(chunkSize int, opts ...TriggerOption) *TriggerDetector
- func (t *TriggerDetector) Update(prob float32) bool
type TriggerOption
- func WithSensitivity(sensitivity float32) TriggerOption
- func WithTriggerLevel(triggerLevel int) TriggerOption

Constants ¶

This section is empty.

Variables ¶

View Source

var DefaultThreshold = ThresholdOptions{
	MinZ:       -4.0,
	MaxZ:       4.0,
	Center:     0.5,
	Resolution: 200,
}

DefaultThreshold is the default set of options for the decoder.

View Source

var (
	ErrModelClosed = errors.New("model closed")
)

View Source

var (
	ErrUnexpectedType = errors.New("unexpected tensor type")
)

Functions ¶

func LinSpace ¶

func LinSpace(start, stop float32, num int) (res *tensor.Dense)

LinSpace returns evenly spaced numbers over a specified closed interval.

Types ¶

type ActivationFunc ¶

type ActivationFunc func()

type ExitFunc ¶

type ExitFunc func(err error)

type Listener ¶

type Listener struct {
	// contains filtered or unexported fields
}

func NewListener ¶

func NewListener(model Model, p Params) (*Listener, error)

func (*Listener) Close ¶

func (p *Listener) Close() error

func (*Listener) Update ¶

func (p *Listener) Update(audio []int16) (float32, error)

type Model ¶

type Model interface {
	Predict(inputData tensor.Tensor) (float32, error)
	Close() error
}

func NewTFLiteModel ¶

func NewTFLiteModel(modelPath string) (Model, error)

NewTFLiteModel creates a new tensorflow lite model

type MuStd ¶

type MuStd [][]float32

MuStd represents threshold configs with easy to use functions.

func (MuStd) Calculate ¶

func (m MuStd) Calculate(value float32) []float32

Calculate applies the value to the configuration

func (MuStd) Max ¶

func (m MuStd) Max(maxZ float32) float32

Max calculates the maximum with maxZ, then sorts and returns the highest value

func (MuStd) Min ¶

func (m MuStd) Min(minZ float32) float32

Min calculates the minimum with minZ, then sorts and returns the lowest value

type Option ¶

type Option func(*Runner)

func WithActivationFunc ¶

func WithActivationFunc(f ActivationFunc) Option

WithActivationFunc sets the func called when activated

func WithExitFunc ¶

func WithExitFunc(f ExitFunc) Option

WithPredictionFunc sets the func called after prediction

func WithPredictionFunc ¶

func WithPredictionFunc(f PredictionFunc) Option

WithPredictionFunc sets the func called after prediction

type Params ¶

type Params struct {
	WindowT         float32 `json:"window_t" default:"0.1"`
	HopT            float32 `json:"hop_t" default:"0.05"`
	BufferT         float32 `json:"buffer_t" default:"1.5"`
	SampleRate      int     `json:"sample_rate" default:"16000"`
	SampleDepth     int     `json:"sample_depth" default:"2"`
	NMFCC           int     `json:"n_mfcc" default:"13"`
	NFilt           int     `json:"n_filt" default:"20"`
	NFft            int     `json:"n_fft" default:"512"`
	UseDelta        bool    `json:"use_delta" default:"false"`
	ThresholdConfig MuStd   `json:"threshold_config" default:"[[6,4]]"`
	ThresholdCenter float32 `json:"threshold_center" default:"0.2"`
}

Params is the Precise model parameter list. This can be loaded from JSON, however for tflite models these are hardcoded. Defaults are set for these elsewhere via NewParams, not using the tags, but they are there for reference

func NewParams ¶

func NewParams() Params

func (Params) BufferSamples ¶

func (p Params) BufferSamples() int

func (Params) HopSamples ¶

func (p Params) HopSamples() int

func (Params) NFeatures ¶

func (p Params) NFeatures() int

func (Params) WindowSamples ¶

func (p Params) WindowSamples() int

type PredictionFunc ¶

type PredictionFunc func(prob float32)

type Runner ¶

type Runner struct {
	OnPrediction PredictionFunc
	OnActivation ActivationFunc
	OnExit       ExitFunc
	// contains filtered or unexported fields
}

func NewRunner ¶

func NewRunner(listener *Listener, chunkSize int, opts ...Option) *Runner

NewRunner creates a new network runner

func (*Runner) Close ¶

func (r *Runner) Close() error

Close stops the neural network runner

func (*Runner) Queue ¶

func (r *Runner) Queue(samples []int16)

Queue passes in samples directly to the channel

func (*Runner) ReadFrom ¶

func (r *Runner) ReadFrom(reader io.Reader) (int64, error)

ReadFrom allows the Runner to simply read from a reader

func (*Runner) Start ¶

func (r *Runner) Start()

Start will start the runner and the goroutine

func (*Runner) Stop ¶

func (r *Runner) Stop()

Stop will stop the runner without closing it.

func (*Runner) Write ¶

func (r *Runner) Write(b []byte) (int, error)

Write allows a Runner to act as an io.Writer

type TFLiteModel ¶

type TFLiteModel struct {
	// contains filtered or unexported fields
}

TFLiteModel represents a tensorflow lite model

func (*TFLiteModel) Close ¶

func (m *TFLiteModel) Close() error

Close cleans up the model after use

func (*TFLiteModel) Predict ¶

func (m *TFLiteModel) Predict(inputData tensor.Tensor) (float32, error)

Predict sends the input data into the input tensor, then invokes the model

type ThresholdDecoder ¶

type ThresholdDecoder struct {
	MinOut   int
	MaxOut   int
	OutRange int
	// contains filtered or unexported fields
}

ThresholdDecoder decodes raw neural network output

func NewThresholdDecoder ¶

func NewThresholdDecoder(muStds MuStd, options ThresholdOptions) *ThresholdDecoder

NewThresholdDecoder creates a new ThresholdDecoder with calculated distributions.

func (*ThresholdDecoder) Decode ¶

func (t *ThresholdDecoder) Decode(rawOutput float32) float32

Decode takes raw neural network output and normalizes it using probability distribution

type ThresholdOptions ¶

type ThresholdOptions struct {
	MinZ       float32
	MaxZ       float32
	Center     float32
	Resolution int
}

type TriggerDetector ¶

type TriggerDetector struct {
	// contains filtered or unexported fields
}

func NewTriggerDetector ¶

func NewTriggerDetector(chunkSize int, opts ...TriggerOption) *TriggerDetector

NewTriggerDetector creates a new TriggerDetector

func (*TriggerDetector) Update ¶

func (t *TriggerDetector) Update(prob float32) bool

Update adds the current probability to the detection history

type TriggerOption ¶

type TriggerOption func(*TriggerDetector)

func WithSensitivity ¶

func WithSensitivity(sensitivity float32) TriggerOption

WithSensitivity sets the detector sensitivity

func WithTriggerLevel ¶

func WithTriggerLevel(triggerLevel int) TriggerOption

WithTriggerLevel sets the number of triggers required to return a valid trigger

Source Files ¶

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Documentation ¶

Index ¶

Constants ¶

Variables ¶

Functions ¶

func LinSpace ¶

Types ¶

type ActivationFunc ¶

type ExitFunc ¶

type Listener ¶

func NewListener ¶

func (*Listener) Close ¶

func (*Listener) Update ¶

type Model ¶

func NewTFLiteModel ¶

type MuStd ¶

func (MuStd) Calculate ¶

func (MuStd) Max ¶

func (MuStd) Min ¶

type Option ¶

func WithActivationFunc ¶

func WithDetectorOpts ¶

func WithExitFunc ¶

func WithPredictionFunc ¶

type Params ¶

func NewParams ¶

func (Params) BufferSamples ¶

func (Params) HopSamples ¶

func (Params) NFeatures ¶

func (Params) WindowSamples ¶

type PredictionFunc ¶

type Runner ¶

func NewRunner ¶

func (*Runner) Close ¶

func (*Runner) Queue ¶

func (*Runner) ReadFrom ¶

func (*Runner) Start ¶

func (*Runner) Stop ¶

func (*Runner) Write ¶

type TFLiteModel ¶

func (*TFLiteModel) Close ¶

func (*TFLiteModel) Predict ¶

type ThresholdDecoder ¶

func NewThresholdDecoder ¶

func (*ThresholdDecoder) Decode ¶

type ThresholdOptions ¶

type TriggerDetector ¶

func NewTriggerDetector ¶

func (*TriggerDetector) Update ¶

type TriggerOption ¶

func WithSensitivity ¶

func WithTriggerLevel ¶

Source Files ¶