Hello Alter family,
We will be discontinuing code access and archiving our Github repositories on November 29, 2022. After that date, developers will be able to use previously downloaded copies of mocap4face as long as they continue to comply with the terms of service. Please note that after November 29, 2022, all of our SDKs will no longer be updated or supported and all package hosting (NPM and Gradle) will be shut down.
We are grateful for your understanding.
Alter
mocap4face by alter
mocap4face by alter is a free, multiplatform SDK for real time facial motion capture based on Facial Action Coding System or (FACS). It provides real-time FACS-derived blendshape coefficients, and rigid head pose in 3D space from any mobile camera, webcam, photo, or video enabling live animation of 3D avatars, digital characters, and more.
After fetching the input from one of the mentioned sources, mocap4face SDK produces data in ARKit-compatible blendshapes, i.e., morph targets weight values as a per-frame expression shown in the video below. Useful for, e.g., animating a 2D or 3D avatar in a way that mimics the user's facial expressions in real-time à la Apple Memoji but without the need of a hardware-based TrueDepth Camera.
With mocap4face, you can drive live avatars or NFT PFPs, build Snapchat-like lenses, AR experiences, face filters that trigger actions, VTubing apps, and more with as little energy impact and CPU/GPU use as possible. As an example, check out how the popular avatar live-streaming app REALITY is using our SDK.
Please star us ⭐⭐⭐ on GitHub—it motivates us a lot!
- Platforms
-
- iOS
-
- Android
-
- Web
- 3D reprojection to the input photo/video
- Platform-suited API and packaging with internal optimizations
- Simultaneous back and front camera support
42
tracked facial expressions via blendshapes- Eye tracking including eye gaze vector
- Tongue tracking
- Light & fast, just
3MB
ML model size ≤ ±50°
pitch,≤ ±40°
yaw and≤ ±30°
roll tracking coverage
- All RGB camera
- Photo
- Video
- ARKit-compatible blendshapes
- Head position and scale in 2D and 3D
- Head rotation in world coordinates
50 FPS
on Pixel 460 FPS
on iPhone SE (1st gen)90 FPS
on iPhone X or newer
- Create a dev account at studio.facemoji.co
- Generate a unique API key for your app
- Paste the API key to your source code
- Open the sample XCode project and run the demo on your iOS device
- To use the SDK in your project, either use the bundled XCFramework directly or use the Swift Package manager (this repository also serves as a Swift PM repository)
- Open the sample project in Android Studio and run the demo on your Android device
- Add this repository to the list of your Maven repositories in your root
build.gradle
, for example:
allprojects {
repositories {
google()
mavenCentral()
// Any other repositories here...
maven {
name = "Facemoji"
url = uri("https://facemoji.jfrog.io/artifactory/default-maven-local/")
}
}
}
- To use the SDK in your project, add
implementation 'co.facemoji:mocap4face:0.5.1'
to your Gradle dependencies
- Open the sample project under js-example in an editor of your choice
- Run
npm install && npm run dev
to start a local server with the demo - Run
npm install && npm run dev_https
to start a local server with self-signed HTTPS support - Run
npm install @facemoji/mocap4face
in your own project to add mocap4face as a dependency
If the webcamera button is not working, you might need to use HTTPS for the local dev server.
Run npm run dev_https
and allow the self-signed certificate in the browser to start the demo in HTTPS mode.
You can also run npm run build
to create a production bundle of the demo app.
- AR for NFTs profile pics
- Live avatar experiences
- Snapchat-like lense
- AR experiences
- VTubing apps
- Live streaming apps
- Face filters
- AR games with facial triggers
- Beauty AR
- Virtual try-on
- Play to earn games
This library is provided under the Facemoji SDK License Agreement—see LICENSE. Also make sure to check out our FAQ for more details.
The sample code in this repository is provided under the Facemoji Samples License
OSS used in mocap4face SDK:
- Tensorflow + Tensorflow Lite
- kotlinx-collections-immutable
- kotlinx-serialization
- kotlinx-coroutine
- benasher44/uuid
- Stately
- okhttp
Original video by LaBeouf, Rönkkö & Turner.
This library transitively uses open source software, see the full list of our OSS dependencies and license notices.