face

package

v0.0.0-...-c8acfb9 Latest Latest Go to latest Published: Apr 25, 2024 License: AGPL-3.0 Imports: 25 Imported by: 0

Details

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Repository

github.com/photoprism/photoprism

Links

Open Source Insights

Documentation ¶

Overview ¶

Package face provides face recognition.

This program is free software: you can redistribute it and/or modify
it under Version 3 of the GNU Affero General Public License (the "AGPL"):
<https://docs.photoprism.app/license/agpl>

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

The AGPL is supplemented by our Trademark and Brand Guidelines,
which describe how our Brand Assets may be used:
<https://www.photoprism.app/trademark>

Feel free to send an email to hello@photoprism.app if you have questions, want to support our work, or just want to say hello.

Additional information can be found in our Developer Guide: <https://docs.photoprism.app/developer-guide/>

Index ¶

Variables
func QualityThreshold(scale int) (score float32)
func RandomDist() float64
func RandomFloat64(f, d float64) float64
func ReadCascadeDir(plc *pigo.PuplocCascade, path string) (result map[string][]*FlpCascade, err error)
type Area
- func NewArea(name string, row, col, scale int) Area
- func (a Area) Relative(r Area, rows, cols float32) crop.Area
- func (a Area) String() string
- func (a Area) TopLeft() (int, int)
type Areas
- func (pts Areas) Relative(r Area, rows, cols float32) (result crop.Areas)
type Detector
- func (d *Detector) Detect(fileName string) (faces []pigo.Detection, params pigo.CascadeParams, err error)
- func (d *Detector) Faces(det []pigo.Detection, params pigo.CascadeParams, findLandmarks bool) (results Faces, err error)
type Embedding
- func EmbeddingsMidpoint(embeddings Embeddings) (result Embedding, radius float64, count int)
- func NewEmbedding(inference []float32) Embedding
- func RandomEmbedding() (result Embedding)
- func RandomIgnoredEmbedding() (result Embedding)
- func RandomKidsEmbedding() (result Embedding)
- func UnmarshalEmbedding(s string) (result Embedding, err error)
- func (m Embedding) CanMatch() bool
- func (m Embedding) Dist(other Embedding) float64
- func (m Embedding) Ignored() bool
- func (m Embedding) JSON() []byte
- func (m Embedding) KidsFace() bool
- func (m Embedding) Kind() Kind
- func (m Embedding) Magnitude() float64
- func (m Embedding) SkipMatching() bool
type Embeddings
- func NewEmbeddings(inference [][]float32) Embeddings
- func RandomEmbeddings(n int, k Kind) (result Embeddings)
- func UnmarshalEmbeddings(s string) (result Embeddings, err error)
- func (embeddings Embeddings) Contains(other Embedding, radius float64) bool
- func (embeddings Embeddings) Count() int
- func (embeddings Embeddings) Dist(other Embedding) (dist float64)
- func (embeddings Embeddings) Empty() bool
- func (embeddings Embeddings) First() Embedding
- func (embeddings Embeddings) Float64() [][]float64
- func (embeddings Embeddings) JSON() []byte
- func (embeddings Embeddings) Kind() (result Kind)
- func (embeddings Embeddings) One() bool
type Face
- func (f *Face) CropArea() crop.Area
- func (f *Face) Dim() float32
- func (f *Face) EmbeddingsJSON() (b []byte)
- func (f *Face) EyesMidpoint() Area
- func (f *Face) HasEmbedding() bool
- func (f *Face) NoEmbedding() bool
- func (f *Face) RelativeLandmarks() crop.Areas
- func (f *Face) RelativeLandmarksJSON() (b []byte)
- func (f *Face) Size() int
type Faces
- func Detect(fileName string, findLandmarks bool, minSize int) (faces Faces, err error)
- func (faces *Faces) Append(f Face)
- func (faces Faces) Contains(other Face) bool
- func (faces Faces) Count() int
- func (faces Faces) Uncertainty() int
type FlpCascade
type Kind
type Net
- func NewNet(modelPath, cachePath string, disabled bool) *Net
- func (t *Net) Detect(fileName string, minSize int, cacheCrop bool, expected int) (faces Faces, err error)
- func (t *Net) ModelLoaded() bool

Constants ¶

This section is empty.

Variables ¶

View Source

var ClusterCore = 4 // Min number of faces forming a cluster core.

View Source

var ClusterDist = 0.64 // Similarity distance threshold of faces forming a cluster core.

View Source

var ClusterScoreThreshold = 15 // Min score for faces forming a cluster.

View Source

var ClusterSizeThreshold = 80 // Min size for faces forming a cluster in pixels.

View Source

var CropSize = crop.Sizes[crop.Tile160] // Face image crop size for FaceNet.

View Source

var IgnoredDist = 0.86

IgnoredDist is the distance threshold for matching IgnoredEmbeddings.

View Source

var IgnoredEmbeddings = Embeddings{
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}

IgnoredEmbeddings contains known bad embeddings to be excluded from results.

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var KidsDist = 0.695

KidsDist is the distance threshold for matching KidsEmbeddings.

View Source

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}

KidsEmbeddings contains embeddings of children's faces that are (currently) too generic to be properly matched.

View Source

var MatchDist = 0.46 // Dist offset threshold for matching new faces with clusters.

View Source

var NullEmbedding = make(Embedding, 512)

View Source

var OverlapThreshold = 42 // Face area overlap threshold in percent.

View Source

var OverlapThresholdFloor = OverlapThreshold - 1 // Reduced overlap area to avoid rounding inconsistencies.

View Source

var SampleThreshold = 2 * ClusterCore // Threshold for automatic clustering to start.

View Source

var ScoreThreshold = 9.0 // Min face score.

View Source

var SizeThreshold = 50 // Min face size in pixels.

Functions ¶

func QualityThreshold ¶

func QualityThreshold(scale int) (score float32)

QualityThreshold returns the scale adjusted quality score threshold.

func RandomDist ¶

func RandomDist() float64

RandomDist returns a distance threshold for matching RandomDEmbeddings.

func RandomFloat64 ¶

func RandomFloat64(f, d float64) float64

RandomFloat64 adds a random distance offset to a float64.

func ReadCascadeDir ¶

func ReadCascadeDir(plc *pigo.PuplocCascade, path string) (result map[string][]*FlpCascade, err error)

ReadCascadeDir reads the facial landmark points cascade files from the provided directory.

Types ¶

type Area ¶

type Area struct {
	Name  string `json:"name,omitempty"`
	Row   int    `json:"x,omitempty"`
	Col   int    `json:"y,omitempty"`
	Scale int    `json:"size,omitempty"`
}

Area represents a face landmark position.

func NewArea ¶

func NewArea(name string, row, col, scale int) Area

NewArea returns new face landmark coordinates.

func (Area) Relative ¶

func (a Area) Relative(r Area, rows, cols float32) crop.Area

Relative returns the area with relative coordinates.

func (Area) String ¶

func (a Area) String() string

String returns the face landmark position as string.

func (Area) TopLeft ¶

func (a Area) TopLeft() (int, int)

TopLeft returns the top left position of the area.

type Areas ¶

type Areas []Area

Areas is a list of face landmark areas.

func (Areas) Relative ¶

func (pts Areas) Relative(r Area, rows, cols float32) (result crop.Areas)

Relative returns all areas with relative coordinates.

type Detector ¶

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

Detector struct contains Pigo face detector general settings.

func (*Detector) Detect ¶

func (d *Detector) Detect(fileName string) (faces []pigo.Detection, params pigo.CascadeParams, err error)

Detect runs the detection algorithm over the provided source image.

func (*Detector) Faces ¶

func (d *Detector) Faces(det []pigo.Detection, params pigo.CascadeParams, findLandmarks bool) (results Faces, err error)

Faces adds landmark coordinates to detected faces and returns the results.

type Embedding ¶

type Embedding []float64

Embedding represents a face embedding.

func EmbeddingsMidpoint ¶

func EmbeddingsMidpoint(embeddings Embeddings) (result Embedding, radius float64, count int)

EmbeddingsMidpoint returns the embeddings vector midpoint.

func NewEmbedding ¶

func NewEmbedding(inference []float32) Embedding

NewEmbedding creates a new embedding from an inference result.

func RandomEmbedding ¶

func RandomEmbedding() (result Embedding)

RandomEmbedding returns a random embedding for testing.

func RandomIgnoredEmbedding ¶

func RandomIgnoredEmbedding() (result Embedding)

RandomIgnoredEmbedding returns a random ignored embedding for testing.

func RandomKidsEmbedding ¶

func RandomKidsEmbedding() (result Embedding)

RandomKidsEmbedding returns a random kids embedding for testing.

func UnmarshalEmbedding ¶

func UnmarshalEmbedding(s string) (result Embedding, err error)

UnmarshalEmbedding parses a single face embedding JSON.

func (Embedding) CanMatch ¶

func (m Embedding) CanMatch() bool

CanMatch tests if the face embedding is not blacklisted.

func (Embedding) Dist ¶

func (m Embedding) Dist(other Embedding) float64

Dist calculates the distance to another face embedding.

func (Embedding) Ignored ¶

func (m Embedding) Ignored() bool

Ignored tests whether the embedding is generally unsuitable for matching.

func (Embedding) JSON ¶

func (m Embedding) JSON() []byte

JSON returns the face embedding as JSON bytes.

func (Embedding) KidsFace ¶

func (m Embedding) KidsFace() bool

KidsFace tests if the embedded face belongs to a baby or young child.

func (Embedding) Kind ¶

func (m Embedding) Kind() Kind

Kind returns the type of face e.g. regular, kids, or ignored.

func (Embedding) Magnitude ¶

func (m Embedding) Magnitude() float64

Magnitude returns the face embedding vector length (magnitude).

func (Embedding) SkipMatching ¶

func (m Embedding) SkipMatching() bool

SkipMatching checks if the face embedding seems unsuitable for matching.

type Embeddings ¶

type Embeddings []Embedding

Embeddings represents a face embedding cluster.

func NewEmbeddings ¶

func NewEmbeddings(inference [][]float32) Embeddings

NewEmbeddings creates a new embeddings from inference results.

func RandomEmbeddings ¶

func RandomEmbeddings(n int, k Kind) (result Embeddings)

RandomEmbeddings returns random embeddings for testing.

func UnmarshalEmbeddings ¶

func UnmarshalEmbeddings(s string) (result Embeddings, err error)

UnmarshalEmbeddings parses face embedding JSON.

func (Embeddings) Contains ¶

func (embeddings Embeddings) Contains(other Embedding, radius float64) bool

Contains tests if another embeddings is contained within a radius.

func (Embeddings) Count ¶

func (embeddings Embeddings) Count() int

Count returns the number of embeddings.

func (Embeddings) Dist ¶

func (embeddings Embeddings) Dist(other Embedding) (dist float64)

Dist returns the minimum distance to an embedding.

func (Embeddings) Empty ¶

func (embeddings Embeddings) Empty() bool

Empty tests if embeddings are empty.

func (Embeddings) First ¶

func (embeddings Embeddings) First() Embedding

First returns the first face embedding.

func (Embeddings) Float64 ¶

func (embeddings Embeddings) Float64() [][]float64

Float64 returns embeddings as a float64 slice.

func (Embeddings) JSON ¶

func (embeddings Embeddings) JSON() []byte

JSON returns the embeddings as JSON bytes.

func (Embeddings) Kind ¶

func (embeddings Embeddings) Kind() (result Kind)

Kind returns the type of face e.g. regular, kids, or ignored.

func (Embeddings) One ¶

func (embeddings Embeddings) One() bool

One tests if there is exactly one embedding.

type Face ¶

type Face struct {
	Rows       int        `json:"rows,omitempty"`
	Cols       int        `json:"cols,omitempty"`
	Score      int        `json:"score,omitempty"`
	Area       Area       `json:"face,omitempty"`
	Eyes       Areas      `json:"eyes,omitempty"`
	Landmarks  Areas      `json:"landmarks,omitempty"`
	Embeddings Embeddings `json:"embeddings,omitempty"`
}

Face represents a face detected.

func (*Face) CropArea ¶

func (f *Face) CropArea() crop.Area

CropArea returns the relative image area for cropping.

func (*Face) Dim ¶

func (f *Face) Dim() float32

Dim returns the max number of rows and cols as float32 to calculate relative coordinates.

func (*Face) EmbeddingsJSON ¶

func (f *Face) EmbeddingsJSON() (b []byte)

EmbeddingsJSON returns detected face embeddings as JSON array.

func (*Face) EyesMidpoint ¶

func (f *Face) EyesMidpoint() Area

EyesMidpoint returns the point in between the eyes.

func (*Face) HasEmbedding ¶

func (f *Face) HasEmbedding() bool

HasEmbedding tests if the face has at least one embedding.

func (*Face) NoEmbedding ¶

func (f *Face) NoEmbedding() bool

NoEmbedding tests if the face has no embeddings.

func (*Face) RelativeLandmarks ¶

func (f *Face) RelativeLandmarks() crop.Areas

RelativeLandmarks returns relative face areas.

func (*Face) RelativeLandmarksJSON ¶

func (f *Face) RelativeLandmarksJSON() (b []byte)

RelativeLandmarksJSON returns relative face areas as JSON.

func (*Face) Size ¶

func (f *Face) Size() int

Size returns the absolute face size in pixels.

type Faces ¶

type Faces []Face

Faces represents a list of faces detected.

func Detect ¶

func Detect(fileName string, findLandmarks bool, minSize int) (faces Faces, err error)

Detect runs the detection algorithm over the provided source image.

func (*Faces) Append ¶

func (faces *Faces) Append(f Face)

Append adds a face.

func (Faces) Contains ¶

func (faces Faces) Contains(other Face) bool

Contains returns true if the face conflicts with existing faces.

func (Faces) Count ¶

func (faces Faces) Count() int

Count returns the number of faces detected.

func (Faces) Uncertainty ¶

func (faces Faces) Uncertainty() int

Uncertainty return the max face detection uncertainty in percent.

type FlpCascade ¶

type FlpCascade struct {
	*pigo.PuplocCascade
	// contains filtered or unexported fields
}

FlpCascade holds the binary representation of the facial landmark points cascade files

type Kind ¶

type Kind int

const (
	RegularFace Kind = iota + 1
	KidsFace
	IgnoredFace
	AmbiguousFace
)

type Net ¶

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

Net is a wrapper for the TensorFlow Facenet model.

func NewNet ¶

func NewNet(modelPath, cachePath string, disabled bool) *Net

NewNet returns a new TensorFlow Facenet instance.

func (*Net) Detect ¶

func (t *Net) Detect(fileName string, minSize int, cacheCrop bool, expected int) (faces Faces, err error)

Detect runs the detection and facenet algorithms over the provided source image.

func (*Net) ModelLoaded ¶

func (t *Net) ModelLoaded() bool

ModelLoaded tests if the TensorFlow model is loaded.

Source Files ¶

View all Source files

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