node-seeta

Node.js wrap for SeetaFaceEngine.

• Examples
• How to install
• Usage

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Examples

See examples for more implementations.

How to install

System require

	Ubuntu	Windows
version	16.04/18.04	7/8/8.1/10
arch	x64	x86/x86_64
minimum	1 GB	1 GB
recommend	2+GB	2+GB
build status

Download

• Git tree: https://github.com/Mitscherlich/node-seeta.git
  • Clone with git clone https://github.com/Mitscherlich/node-seeta.git 🔨 Build instructions.

Usage

Face detection

Detect face(s) in a image.

const FaceDetection = require('seeta').FaceDetection
const path = require('path')
// 1. name face detection model path.
const fdModel = path.join('path', 'to', 'models/SeetaFaceDetector2.0.ats')
// 2. create a detector
const detector = new FaceDetection(fdModel)
// 3. detect face(s) in a image
const results = detector.detect(path.join('path', 'to', 'image/test.png'))
console.log({ result })
// result will in this form:
// {
//   "count": Number,     // count of face(s)
//   "data": {
//     "faces": [{
//       "x": Number,     // face left-upper point x
//       "y": Number,     // face left-upper point y
//       "width": Number, // face bounding box width
//       "height": Number // face bounding box height
//     }]
//   }
// }

Facial points detection

Mark facial points for compare and recognize.

const { FaceDetection, PointDetector } = require('seeta')
const path = require('path')
// 1. name detector models path.
const fdModel = path.join('path', 'to', 'models/SeetaFaceDetector2.0.ats')
const faModel = path.join('path', 'to', 'models/SeetaPointDetector2.0.pts5.ats')
// 2. create a point detector
const detector = new FaceDetection(fdModel)
const pointer = new PointDetector(faModel)
// 3. detect face(s) in a image
const faces = detector.detect(path.join('path', 'to', 'image/test.png'))
if (faces.data && face.data.faces.length) {
  const points = pointer.detect(path.join('path', 'to', 'image/test.png', faces.data.faces[0]))
  console.log({ result })
}
// result will in this form:
// {
//   "data": {
//     "points": [{
//       "x": Number,     // facial point x
//       "y": Number,     // facial point y
//     }]
//   }
// }

Face recognize

1. 1 vs 1 compare

compare two image contains face and compare for its similar.

const { FaceDetector, PointDetector, FaceRecognizer } = require('seeta')
const path = require('path')
// 1. name detector models path.
const fdModel = path.join('path', 'to', 'models/SeetaFaceDetector2.0.ats')
const faModel = path.join('path', 'to', 'models/SeetaPointDetector2.0.pts5.ats')
const frModel = path.join('path', 'to', 'models/SeetaFaceRecognizer2.0.ats')
// 2. create detectors
console.time('initailize')
const detector = new FaceDetector(fdModel)
const pointer = new PointDetector(faModel)
const recognizer = new FaceRecognizer(frModel)
console.timeEnd('initailize')
// 3. detect face(s) in a image
const imagePath = join('path', 'to', 'data/test.png')

const faces = detector.detect(imagePath)
const face1 = faces.data.faces[0]
const face2 = faces.data.faces[1]

const points1 = pointer.detect(imagePath, face1).data.points
const points2 = pointer.detect(imagePath, face2).data.points
// 4. compare face(s) in two images
const similar = recognizer.compare(
  { path: imagePath, points: points1 }, { path: imagePath, points: points1 }
)
console.log({ similar })

2. 1 vs n compare

• first: register a image

const { FaceDetector, PointDetector, FaceRecognizer } = require('seeta')
const path = require('path')
// 1. name detector models path.
const fdModel = path.join('path', 'to', 'models/SeetaFaceDetector2.0.ats')
const faModel = path.join('path', 'to', 'models/SeetaPointDetector2.0.pts5.ats')
const frModel = path.join('path', 'to', 'models/SeetaFaceRecognizer2.0.ats')
// 2. create detectors
console.time('initailize')
const detector = new FaceDetector(fdModel)
const pointer = new PointDetector(faModel)
const recognizer = new FaceRecognizer(frModel)
console.timeEnd('initailize')
// 3. detect face(s) in a image
const imagePath = path.join('path', 'to', 'data/test.png')

const faces = detector.detect(imagePath)
const face = faces.data.faces[0]

const points = pointer.detect(imagePath, face1).data.points
// 4. register a face
const index = recognizer.register(imagePath, points)
console.log({ index }) // ==> the index in recognizer face database

• find all similar in database

// 5. detect face(s) in a image
const newImage = path.join('path', 'to', 'data/another_image.png')
const faces1 = detector.detect(newImage)
const face1 = faces1.data.faces[0]

const points1 = pointer.detect(newImage, face1).data.points
// 6. find all similar in database
const results = recognizer.recognition(newImage, face1)
if (result.data && result.data.length) {
  console.log({ similars: result.data }) // ==> all similars in face databse
}

License

MIT