photoprism/internal/face/face.go

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/*
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Package face provides facial recognition.
Copyright (c) 2018 - 2021 Michael Mayer <hello@photoprism.org>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
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.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
PhotoPrism® is a registered trademark of Michael Mayer. You may use it as required
to describe our software, run your own server, for educational purposes, but not for
offering commercial goods, products, or services without prior written permission.
In other words, please ask.
Feel free to send an e-mail to hello@photoprism.org 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.org/developer-guide/
*/
package face
import (
"encoding/json"
"github.com/photoprism/photoprism/internal/crop"
"github.com/photoprism/photoprism/internal/event"
)
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var log = event.Log
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var CropSize = crop.Sizes[crop.Tile160]
var ClusterCore = 4
var ClusterRadius = 0.6
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var ClusterMinScore = 15
var ClusterMinSize = 100
var SampleThreshold = 2 * ClusterCore
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var OverlapThreshold = 40
var OverlapThresholdFloor = OverlapThreshold - 1
var ScoreThreshold = float32(8.5)
// Faces is a list of face detection results.
type Faces []Face
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// Contains returns true if the face conflicts with existing faces.
func (faces Faces) Contains(other Face) bool {
cropArea := other.CropArea()
for _, f := range faces {
if f.CropArea().OverlapPercent(cropArea) > OverlapThresholdFloor {
return true
}
}
return false
}
// Append adds a face.
func (faces *Faces) Append(f Face) {
*faces = append(*faces, f)
}
// Count returns the number of faces detected.
func (faces Faces) Count() int {
return len(faces)
}
// Uncertainty return the max face detection uncertainty in percent.
func (faces Faces) Uncertainty() int {
if len(faces) < 1 {
return 100
}
maxScore := 0
for _, f := range faces {
if f.Score > maxScore {
maxScore = f.Score
}
}
switch {
case maxScore > 300:
return 1
case maxScore > 200:
return 5
case maxScore > 100:
return 10
case maxScore > 80:
return 15
case maxScore > 65:
return 20
case maxScore > 50:
return 25
case maxScore > 40:
return 30
case maxScore > 30:
return 35
case maxScore > 20:
return 40
case maxScore > 10:
return 45
}
return 50
}
// Face represents a face detection result.
type Face struct {
Rows int `json:"rows,omitempty"`
Cols int `json:"cols,omitempty"`
Score int `json:"score,omitempty"`
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Area Area `json:"face,omitempty"`
Eyes Areas `json:"eyes,omitempty"`
Landmarks Areas `json:"landmarks,omitempty"`
Embeddings [][]float32 `json:"embeddings,omitempty"`
}
// Size returns the absolute face size in pixels.
func (f *Face) Size() int {
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return f.Area.Scale
}
// Dim returns the max number of rows and cols as float32 to calculate relative coordinates.
func (f *Face) Dim() float32 {
if f.Cols > 0 {
return float32(f.Cols)
}
return float32(1)
}
// CropArea returns the relative image area for cropping.
func (f *Face) CropArea() crop.Area {
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if f.Rows < 1 {
f.Cols = 1
}
if f.Cols < 1 {
f.Cols = 1
}
x := float32(f.Area.Col-f.Area.Scale/2) / float32(f.Cols)
y := float32(f.Area.Row-f.Area.Scale/2) / float32(f.Rows)
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return crop.NewArea(
f.Area.Name,
x,
y,
float32(f.Area.Scale)/float32(f.Cols),
float32(f.Area.Scale)/float32(f.Rows),
)
}
// EyesMidpoint returns the point in between the eyes.
func (f *Face) EyesMidpoint() Area {
if len(f.Eyes) != 2 {
return Area{
Name: "midpoint",
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Row: f.Area.Row,
Col: f.Area.Col,
Scale: f.Area.Scale,
}
}
return Area{
Name: "midpoint",
Row: (f.Eyes[0].Row + f.Eyes[1].Row) / 2,
Col: (f.Eyes[0].Col + f.Eyes[1].Col) / 2,
Scale: (f.Eyes[0].Scale + f.Eyes[1].Scale) / 2,
}
}
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// RelativeLandmarks returns relative face areas.
func (f *Face) RelativeLandmarks() crop.Areas {
p := f.EyesMidpoint()
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m := f.Landmarks.Relative(p, float32(f.Rows), float32(f.Cols))
m = append(m, f.Eyes.Relative(p, float32(f.Rows), float32(f.Cols))...)
return m
}
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// RelativeLandmarksJSON returns relative face areas as JSON.
func (f *Face) RelativeLandmarksJSON() (b []byte) {
var noResult = []byte("")
l := f.RelativeLandmarks()
if len(l) < 1 {
return noResult
}
if result, err := json.Marshal(l); err != nil {
log.Errorf("faces: %s", err)
return noResult
} else {
return result
}
}
// EmbeddingsJSON returns detected face embeddings as JSON array.
func (f *Face) EmbeddingsJSON() (b []byte) {
var noResult = []byte("")
if result, err := json.Marshal(f.Embeddings); err != nil {
return noResult
} else {
return result
}
}