added face angle calculations
Vladimir Mandic
parent
3d7007f13d
commit
8b6d1b76df
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@ -38,6 +38,7 @@ Unfortunately, changes ended up being too large for a simple pull request on ori
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- Added test/dev built-in HTTP & HTTPS Web server
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- Removed `mtcnn` and `tinyYolov2` models as they were non-functional in latest public version of `Face-API`
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*If there is a demand, I can re-implement them back.*
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- Added `face angle` calculations that returns `roll`, `yaw` and `pitch`
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Which means valid models are **tinyFaceDetector** and **mobileNetv1**
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@ -388,7 +389,7 @@ npm run build
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## Face Mesh
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`FaceAPI` returns 68-point face mesh as detailed in the image below:
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`FaceAPI` landmark model returns 68-point face mesh as detailed in the image below:
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"src/factories/WithFaceLandmarks.ts": {
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"imports": [
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"path": "src/classes/FaceDetection.ts",
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},
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"bytesInOutput": 443
|
||||
}
|
||||
},
|
||||
"bytes": 82860
|
||||
"bytes": 83303
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Binary file not shown.
|
Before Width: | Height: | Size: 32 KiB After Width: | Height: | Size: 14 KiB |
|
|
@ -28,7 +28,7 @@ function drawFaces(canvas, data, fps) {
|
|||
if (!ctx) return;
|
||||
ctx.clearRect(0, 0, canvas.width, canvas.height);
|
||||
// draw title
|
||||
ctx.font = '1.4rem sans-serif';
|
||||
ctx.font = '1.2rem sans-serif';
|
||||
ctx.fillStyle = 'white';
|
||||
ctx.fillText(`FPS: ${fps}`, 10, 25);
|
||||
for (const person of data) {
|
||||
|
|
@ -43,16 +43,18 @@ function drawFaces(canvas, data, fps) {
|
|||
ctx.globalAlpha = 1;
|
||||
// const expression = person.expressions.sort((a, b) => Object.values(a)[0] - Object.values(b)[0]);
|
||||
const expression = Object.entries(person.expressions).sort((a, b) => b[1] - a[1]);
|
||||
ctx.fillText(`gender ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 45);
|
||||
ctx.fillText(`expression ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 25);
|
||||
ctx.fillText(`age ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 5);
|
||||
ctx.fillText(`gender ${Math.round(100 * person.genderProbability)}% ${person.gender}`, person.detection.box.x, person.detection.box.y - 60);
|
||||
ctx.fillText(`expression ${Math.round(100 * expression[0][1])}% ${expression[0][0]}`, person.detection.box.x, person.detection.box.y - 42);
|
||||
ctx.fillText(`age ${Math.round(person.age)} years`, person.detection.box.x, person.detection.box.y - 24);
|
||||
ctx.fillText(`roll:${Math.trunc(1000 * person.angle.roll) / 1000} pitch:${Math.trunc(1000 * person.angle.pitch) / 1000} yaw:${Math.trunc(1000 * person.angle.yaw) / 1000}`, person.detection.box.x, person.detection.box.y - 6);
|
||||
// draw face points for each face
|
||||
ctx.fillStyle = 'lightblue';
|
||||
ctx.globalAlpha = 0.5;
|
||||
const pointSize = 2;
|
||||
for (const pt of person.landmarks.positions) {
|
||||
for (let i = 0; i < person.landmarks.positions.length; i++) {
|
||||
ctx.beginPath();
|
||||
ctx.arc(pt.x, pt.y, pointSize, 0, 2 * Math.PI);
|
||||
ctx.arc(person.landmarks.positions[i].x, person.landmarks.positions[i].y, pointSize, 0, 2 * Math.PI);
|
||||
ctx.fillText(`${i}`, person.landmarks.positions[i].x + 4, person.landmarks.positions[i].y + 4);
|
||||
ctx.fill();
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -205,7 +205,6 @@ function compile(fileNames, options) {
|
|||
async function build(f, msg) {
|
||||
log.info('Build: file', msg, f, 'target:', common.target);
|
||||
if (!es) es = await esbuild.startService();
|
||||
// common build options
|
||||
try {
|
||||
// rebuild all target groups and types
|
||||
for (const [targetGroupName, targetGroup] of Object.entries(targets)) {
|
||||
|
|
|
|||
|
|
@ -14,6 +14,7 @@ const http2 = require('http2');
|
|||
const path = require('path');
|
||||
// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
|
||||
const chokidar = require('chokidar');
|
||||
// eslint-disable-next-line node/no-unpublished-require, import/no-extraneous-dependencies
|
||||
const log = require('@vladmandic/pilogger');
|
||||
const build = require('./build.js');
|
||||
|
||||
|
|
|
|||
|
|
@ -21,6 +21,36 @@ export function isWithFaceLandmarks(obj: any): obj is WithFaceLandmarks<WithFace
|
|||
&& obj['alignedRect'] instanceof FaceDetection;
|
||||
}
|
||||
|
||||
function calculateFaceAngle(mesh) {
|
||||
const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);
|
||||
|
||||
const angle = { roll: <number | undefined>undefined, pitch: <number | undefined>undefined, yaw: <number | undefined>undefined };
|
||||
|
||||
if (!mesh || !mesh._positions || mesh._positions.length !== 68) return angle;
|
||||
const pt = mesh._positions;
|
||||
|
||||
// roll is face lean left/right
|
||||
// comparing x,y of outside corners of leftEye and rightEye
|
||||
angle.roll = radians(pt[36]._x, pt[36]._y, pt[45]._x, pt[45]._y);
|
||||
|
||||
// yaw is face turn left/right
|
||||
// comparing x distance of bottom of nose to left and right edge of face
|
||||
// and y distance of top of nose to left and right edge of face
|
||||
// precision is lacking since coordinates are not precise enough
|
||||
angle.pitch = radians(pt[30]._x - pt[0]._x, pt[27]._y - pt[0]._y, pt[16]._x - pt[30]._x, pt[27]._y - pt[16]._y);
|
||||
|
||||
// pitch is face move up/down
|
||||
// comparing size of the box around the face with top and bottom of detected landmarks
|
||||
// silly hack, but this gives us face compression on y-axis
|
||||
// e.g., tilting head up hides the forehead that doesn't have any landmarks so ratio drops
|
||||
// value is normalized to range, but is not in actual radians
|
||||
const bottom = pt.reduce((prev, cur) => (prev < cur._y ? prev : cur._y), +Infinity);
|
||||
const top = pt.reduce((prev, cur) => (prev > cur._y ? prev : cur._y), -Infinity);
|
||||
angle.yaw = 10 * (mesh._imgDims._height / (top - bottom) / 1.45 - 1);
|
||||
|
||||
return angle;
|
||||
}
|
||||
|
||||
export function extendWithFaceLandmarks<
|
||||
TSource extends WithFaceDetection<{}>,
|
||||
TFaceLandmarks extends FaceLandmarks = FaceLandmarks68 >(sourceObj: TSource, unshiftedLandmarks: TFaceLandmarks): WithFaceLandmarks<TSource, TFaceLandmarks> {
|
||||
|
|
@ -30,11 +60,13 @@ export function extendWithFaceLandmarks<
|
|||
const rect = landmarks.align();
|
||||
const { imageDims } = sourceObj.detection;
|
||||
const alignedRect = new FaceDetection(sourceObj.detection.score, rect.rescale(imageDims.reverse()), imageDims);
|
||||
const angle = calculateFaceAngle(unshiftedLandmarks);
|
||||
|
||||
const extension = {
|
||||
landmarks,
|
||||
unshiftedLandmarks,
|
||||
alignedRect,
|
||||
angle,
|
||||
};
|
||||
|
||||
return { ...sourceObj, ...extension };
|
||||
|
|
|
|||
|
|
@ -27,28 +27,13 @@ export class DetectAllFacesTask extends DetectFacesTaskBase<FaceDetection[]> {
|
|||
public async run(): Promise<FaceDetection[]> {
|
||||
const { input, options } = this;
|
||||
|
||||
// eslint-disable-next-line no-nested-ternary
|
||||
const faceDetectionFunction = options instanceof TinyFaceDetectorOptions
|
||||
// eslint-disable-next-line no-shadow
|
||||
? (input: TNetInput) => nets.tinyFaceDetector.locateFaces(input, options)
|
||||
: (
|
||||
// eslint-disable-next-line no-nested-ternary
|
||||
options instanceof SsdMobilenetv1Options
|
||||
// eslint-disable-next-line no-shadow
|
||||
? (input: TNetInput) => nets.ssdMobilenetv1.locateFaces(input, options)
|
||||
: (
|
||||
options instanceof TinyYolov2Options
|
||||
// eslint-disable-next-line no-shadow
|
||||
? (input: TNetInput) => nets.tinyYolov2.locateFaces(input, options)
|
||||
: null
|
||||
)
|
||||
);
|
||||
let result;
|
||||
if (options instanceof TinyFaceDetectorOptions) result = nets.tinyFaceDetector.locateFaces(input, options);
|
||||
else if (options instanceof SsdMobilenetv1Options) result = nets.ssdMobilenetv1.locateFaces(input, options);
|
||||
else if (options instanceof TinyYolov2Options) result = nets.tinyYolov2.locateFaces(input, options);
|
||||
else throw new Error('detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options');
|
||||
|
||||
if (!faceDetectionFunction) {
|
||||
throw new Error('detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | MtcnnOptions | TinyYolov2Options');
|
||||
}
|
||||
|
||||
return faceDetectionFunction(input);
|
||||
return result;
|
||||
}
|
||||
|
||||
private runAndExtendWithFaceDetections(): Promise<WithFaceDetection<{}>[]> {
|
||||
|
|
@ -87,9 +72,7 @@ export class DetectSingleFaceTask extends DetectFacesTaskBase<FaceDetection | un
|
|||
const faceDetections = await new DetectAllFacesTask(this.input, this.options);
|
||||
let faceDetectionWithHighestScore = faceDetections[0];
|
||||
faceDetections.forEach((faceDetection) => {
|
||||
if (faceDetection.score > faceDetectionWithHighestScore.score) {
|
||||
faceDetectionWithHighestScore = faceDetection;
|
||||
}
|
||||
if (faceDetection.score > faceDetectionWithHighestScore.score) faceDetectionWithHighestScore = faceDetection;
|
||||
});
|
||||
return faceDetectionWithHighestScore;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -3,16 +3,10 @@ import { SsdMobilenetv1Options } from '../ssdMobilenetv1/SsdMobilenetv1Options';
|
|||
import { DetectAllFacesTask, DetectSingleFaceTask } from './DetectFacesTasks';
|
||||
import { FaceDetectionOptions } from './types';
|
||||
|
||||
export function detectSingleFace(
|
||||
input: TNetInput,
|
||||
options: FaceDetectionOptions = new SsdMobilenetv1Options(),
|
||||
): DetectSingleFaceTask {
|
||||
export function detectSingleFace(input: TNetInput, options: FaceDetectionOptions = new SsdMobilenetv1Options()): DetectSingleFaceTask {
|
||||
return new DetectSingleFaceTask(input, options);
|
||||
}
|
||||
|
||||
export function detectAllFaces(
|
||||
input: TNetInput,
|
||||
options: FaceDetectionOptions = new SsdMobilenetv1Options(),
|
||||
): DetectAllFacesTask {
|
||||
export function detectAllFaces(input: TNetInput, options: FaceDetectionOptions = new SsdMobilenetv1Options()): DetectAllFacesTask {
|
||||
return new DetectAllFacesTask(input, options);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -30,10 +30,7 @@ export class SsdMobilenetv1 extends NeuralNetwork<NetParams> {
|
|||
const x = tf.sub(tf.mul(batchTensor, tf.scalar(0.007843137718737125)), tf.scalar(1)) as tf.Tensor4D;
|
||||
const features = mobileNetV1(x, params.mobilenetv1);
|
||||
|
||||
const {
|
||||
boxPredictions,
|
||||
classPredictions,
|
||||
} = predictionLayer(features.out, features.conv11, params.prediction_layer);
|
||||
const { boxPredictions, classPredictions } = predictionLayer(features.out, features.conv11, params.prediction_layer);
|
||||
|
||||
return outputLayer(boxPredictions, classPredictions, params.output_layer);
|
||||
});
|
||||
|
|
|
|||
Loading…
Reference in New Issue