Kalidokit is a blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models

Related tags

Deep Learningvtubertfjsmediapipe-facemeshmediapipe-handsmediapipe-pose
Overview

KalidoKit - Face, Pose, and Hand Tracking Kinematics

Kalidokit Template

Kalidokit is a blendshape and kinematics solver for Mediapipe/Tensorflow.js face, eyes, pose, and hand tracking models, compatible with Facemesh, Blazepose, Handpose, and Holistic. It takes predicted 3D landmarks and calculates simple euler rotations and blendshape face values.

As the core to Vtuber web apps, Kalidoface and Kalidoface 3D, KalidoKit is designed specifically for rigging 3D VRM models and Live2D avatars!

Kalidokit Template

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Install

Via NPM

npm install kalidokit

import * as Kalidokit from "kalidokit";

// or only import the class you need

import { Face, Pose, Hand } from "kalidokit";

Via CDN

"> 
<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/kalidokit.umd.js"></script>

Methods

Kalidokit is composed of 3 classes for Face, Pose, and Hand calculations. They accept landmark outputs from models like Facemesh, Blazepose, Handpose, and Holistic.

// Accepts an array(468 or 478 with iris tracking) of vectors
Kalidokit.Face.solve(facelandmarkArray, {
    runtime: "tfjs", // `mediapipe` or `tfjs`
    video: HTMLVideoElement,
    imageSize: { height: 0, width: 0 },
    smoothBlink: false, // smooth left and right eye blink delays
    blinkSettings: [0.25, 0.75], // adjust upper and lower bound blink sensitivity
});

// Accepts arrays(33) of Pose keypoints and 3D Pose keypoints
Kalidokit.Pose.solve(poseWorld3DArray, poseLandmarkArray, {
    runtime: "tfjs", // `mediapipe` or `tfjs`
    video: HTMLVideoElement,
    imageSize: { height: 0, width: 0 },
    enableLegs: true,
});

// Accepts array(21) of hand landmark vectors; specify 'Right' or 'Left' side
Kalidokit.Hand.solve(handLandmarkArray, "Right");

// Using exported classes directly
Face.solve(facelandmarkArray);
Pose.solve(poseWorld3DArray, poseLandmarkArray);
Hand.solve(handLandmarkArray, "Right");

Additional Utils

// Stabilizes left/right blink delays + wink by providing blenshapes and head rotation
Kalidokit.Face.stabilizeBlink(
    { r: 0, l: 1 }, // left and right eye blendshape values
    headRotationY, // head rotation in radians
    {
        noWink = false, // disables winking
        maxRot = 0.5 // max head rotation in radians before interpolating obscured eyes
    });

// The internal vector math class
Kalidokit.Vector();

Remixable VRM Template with KalidoKit

Quick-start your Vtuber app with this simple remixable example on Glitch. Face, full-body, and hand tracking in under 350 lines of javascript. This demo uses Mediapipe Holistic for body tracking, Three.js + Three-VRM for rendering models, and KalidoKit for the kinematic calculations. This demo uses a minimal amount of easing to smooth animations, but feel free to make it your own!

Remix on Glitch

Basic Usage

Kalidokit Template

The implementation may vary depending on what pose and face detection model you choose to use, but the principle is still the same. This example uses Mediapipe Holistic which concisely combines them together.

{ await holistic.send({image: HTMLVideoElement}); }, width: 640, height: 480 }); camera.start(); "> 
import * as Kalidokit from 'kalidokit'
import '@mediapipe/holistic/holistic';
import '@mediapipe/camera_utils/camera_utils';

let holistic = new Holistic({locateFile: (file) => {
    return `https://cdn.jsdelivr.net/npm/@mediapipe/[email protected]/${file}`;
}});

holistic.onResults(results=>{
    // do something with prediction results
    // landmark names may change depending on TFJS/Mediapipe model version
    let facelm = results.faceLandmarks;
    let poselm = results.poseLandmarks;
    let poselm3D = results.ea;
    let rightHandlm = results.rightHandLandmarks;
    let leftHandlm = results.leftHandLandmarks;

    let faceRig = Kalidokit.Face.solve(facelm,{runtime:'mediapipe',video:HTMLVideoElement})
    let poseRig = Kalidokit.Pose.solve(poselm3d,poselm,{runtime:'mediapipe',video:HTMLVideoElement})
    let rightHandRig = Kalidokit.Hand.solve(rightHandlm,"Right")
    let leftHandRig = Kalidokit.Hand.solve(leftHandlm,"Left")

    };
});

// use Mediapipe's webcam utils to send video to holistic every frame
const camera = new Camera(HTMLVideoElement, {
  onFrame: async () => {
    await holistic.send({image: HTMLVideoElement});
  },
  width: 640,
  height: 480
});
camera.start();

Slight differences with Mediapipe and Tensorflow.js

Due to slight differences in the results from Mediapipe and Tensorflow.js, it is recommended to specify which runtime version you are using as well as the video input/image size as a reference.

Kalidokit.Pose.solve(poselm3D,poselm,{
    runtime:'tfjs', // default is 'mediapipe'
    video: HTMLVideoElement,// specify an html video or manually set image size
    imageSize:{
        width: 640,
        height: 480,
    };
})

Kalidokit.Face.solve(facelm,{
    runtime:'mediapipe', // default is 'tfjs'
    video: HTMLVideoElement,// specify an html video or manually set image size
    imageSize:{
        width: 640,
        height: 480,
    };
})

Outputs

Below are the expected results from KalidoKit solvers.

// Kalidokit.Face.solve()
// Head rotations in radians
// Degrees and normalized rotations also available
{
    eye: {l: 1,r: 1},
    mouth: {
        x: 0,
        y: 0,
        shape: {A:0, E:0, I:0, O:0, U:0}
    },
    head: {
        x: 0,
        y: 0,
        z: 0,
        width: 0.3,
        height: 0.6,
        position: {x: 0.5, y: 0.5, z: 0}
    },
    brow: 0,
    pupil: {x: 0, y: 0}
}
// Kalidokit.Pose.solve()
// Joint rotations in radians, leg calculators are a WIP
{
    RightUpperArm: {x: 0, y: 0, z: -1.25},
    LeftUpperArm: {x: 0, y: 0, z: 1.25},
    RightLowerArm: {x: 0, y: 0, z: 0},
    LeftLowerArm: {x: 0, y: 0, z: 0},
    LeftUpperLeg: {x: 0, y: 0, z: 0},
    RightUpperLeg: {x: 0, y: 0, z: 0},
    RightLowerLeg: {x: 0, y: 0, z: 0},
    LeftLowerLeg: {x: 0, y: 0, z: 0},
    LeftHand: {x: 0, y: 0, z: 0},
    RightHand: {x: 0, y: 0, z: 0},
    Spine: {x: 0, y: 0, z: 0},
    Hips: {
        worldPosition: {x: 0, y: 0, z: 0},
        position: {x: 0, y: 0, z: 0},
        rotation: {x: 0, y: 0, z: 0},
    }
}
// Kalidokit.Hand.solve()
// Joint rotations in radians
// only wrist and thumb have 3 degrees of freedom
// all other finger joints move in the Z axis only
{
    RightWrist: {x: -0.13, y: -0.07, z: -1.04},
    RightRingProximal: {x: 0, y: 0, z: -0.13},
    RightRingIntermediate: {x: 0, y: 0, z: -0.4},
    RightRingDistal: {x: 0, y: 0, z: -0.04},
    RightIndexProximal: {x: 0, y: 0, z: -0.24},
    RightIndexIntermediate: {x: 0, y: 0, z: -0.25},
    RightIndexDistal: {x: 0, y: 0, z: -0.06},
    RightMiddleProximal: {x: 0, y: 0, z: -0.09},
    RightMiddleIntermediate: {x: 0, y: 0, z: -0.44},
    RightMiddleDistal: {x: 0, y: 0, z: -0.06},
    RightThumbProximal: {x: -0.23, y: -0.33, z: -0.12},
    RightThumbIntermediate: {x: -0.2, y: -0.19, z: -0.01},
    RightThumbDistal: {x: -0.2, y: 0.002, z: 0.15},
    RightLittleProximal: {x: 0, y: 0, z: -0.09},
    RightLittleIntermediate: {x: 0, y: 0, z: -0.22},
    RightLittleDistal: {x: 0, y: 0, z: -0.1}
}

Community Showcase

If you'd like to share a creative use of KalidoKit, we would love to hear about it! Feel free to also use our Twitter hashtag, #kalidokit.

Kalidoface virtual webcam Kalidoface Pose Demo

Open to Contributions

The current library is a work in progress and contributions to improve it are very welcome. Our goal is to make character face and pose animation even more accessible to creatives regardless of skill level!

Owner
Rich
Making Vtuber apps with Mediapipe and Tensorflow.js
Rich
GitHub Repository https://kit.kalidoface.com
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