Swiftpack.co - facemoji/mocap4face as Swift Package

Swiftpack.co is a collection of thousands of indexed Swift packages. Search packages.
See all packages published by facemoji.
facemoji/mocap4face 0.1.0
A free, multiplatform SDK for real-time facial motion capture using blendshapes, and rigid head pose in 3D space from any RGB camera, photo, or video.
⭐️ 204
🕓 4 weeks ago
iOS macOS
.package(url: "https://github.com/facemoji/mocap4face.git", from: "0.1.0")


mocap4face by Facemoji
mocap4face by Facemoji

mocap4face by Facemoji 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, 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!

📋 Table of Content

🤓 Tech Specs

✨ Key Features

  • 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

🤳 Input

  • All RGB camera
  • Photo
  • Video

📦 Output

  • ARKit-compatible blendshapes
  • Head position and scale in 2D and 3D
  • Head rotation in world coordinates

⚡ Performance

  • 50 FPS on Pixel 4
  • 60 FPS on iPhone SE (1st gen)
  • 90 FPS on iPhone X or newer

💿 Installation

Prerequisites

  1. Get a new developer account at studio.facemoji.co
  2. Generate a unique API key for your app
  3. Paste the API key to your source code

iOS

  1. Open the sample XCode project and run the demo on your iOS device
  2. 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)

Android

  1. Open the sample project in Android Studio and run the demo on your Android device
  2. 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/")
        }
    }
}
  1. To use the SDK in your project, add implementation 'co.facemoji:mocap4face:0.1.0' to your Gradle dependencies

🚀 Use Cases

  • 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

❤️ Links

📄 License

This library is provided under the Facemoji SDK License Agreement—see LICENSE.

The sample code in this repository is provided under the Facemoji Samples License

Notices

OSS used in mocap4face SDK:

GitHub

link
Stars: 205
Last commit: 2 weeks ago
jonrohan Something's broken? Yell at me @ptrpavlik. Praise and feedback (and money) is also welcome.

Release Notes

0.1.0
4 weeks ago

Initial release for iOS 13+ and Android. See our blog post for details about this release.

Swiftpack is being maintained by Petr Pavlik | @ptrpavlik | @swiftpackco | API | Analytics