DlibFaceLandmarkDetector can Object Detection and Shape Prediction using Dlib C++ Library. You can detect frontal human faces and face landmark (68 points, 17points, 6points) in Texture2D, WebCamTexture and Image byte array.
For more detail this asset from the Unity Asset Store: Click Here
This is a paid asset, but now you can download Dlib FaceLandmark Detector for FREE, Please keep in mind this package is provided only for learning purposes or to be able to test before buying the product, NOT FOR COMMERCIAL PURPOSES.
Dlib FaceLandmark Detector v1.4.1 (Latest version)
Dlib FaceLandmark Detector v1.4.0
Dlib FaceLandmark Detector v1.3.4
Dlib FaceLandmark Detector v1.3.2
“If possible, please buy the package to support the developer”
Works with Unity Cloud Build
iOS & Android support
Windows10 UWP support
Lumin ( MagicLeap ) support support
WebGL support
Win & Mac & Linux Standalone support
Preview support in the Editor
DlibFaceLandmarkDetector can ObjectDetection and ShapePrediction using Dlib19.7 C++ Library.
Official Site | ExampleCode | Android Demo WebGL Demo | Tutorial & Demo Video | Forum | API Reference
Features:
– You can detect frontal human faces and face landmark (68 points, 17points, 6points) in Texture2D, WebCamTexture and Image byte array. In addition, You can detect a different objects by changing trained data file.
– ObjectDetector is made using the now classic Histogram of Oriented Gradients (HOG) feature combined with a linear classifier, an image pyramid, and sliding window detection scheme. You can train your own detector in addition to human faces detector. If you want to train your own detector, please refer to this page.
– ShapePredictor is created by using dlib’s implementation of the paper(One Millisecond Face Alignment with an Ensemble of Regression Trees by Vahid Kazemi and Josephine Sullivan, CVPR 2014). You can train your own models in addition to human face landmark model using dlib’s machine learning tools. If you want to train your own models, please refer to this page.
– Advanced examples using “OpenCV for Unity” are Included. (The execution of this examples are required “OpenCV for Unity”.)
– PlayMakerActions for DlibFaceLandmarkDetector is available.
Examples:
Texture2DExample
WebCamTextureExample
CatDetectionExample
Advanced Examples:
(require OpenCV for Unity)
Texture2DToMatExample
WebCamTextureToMatHelperExample
VideoCaptureExample
ARHeadWebCamTextureExample
VideoCaptureARHeadExample
FrameOptimizationExample
NoiseFilterWebCamTextureExample
NoiseFilterVideoCaptureExample
ExampleCode using Dlib FaceLandmark Detector is available.
FaceSwapper Example
FaceMask Example
HoloLens with DlibFaceLandmarkDetector Example
MagicLeap with DlibFaceLandmarkDetector Example
DlibFaceLandmarkDetector uses Dlib under Boost Software License ; see Third-Party Notices.txt file in package for details.
The Shape Predictor model files included with this asset are available for commercial use.
System Requirements
Build Win Standalone & Preview Editor : Windows 8 or later
Build Mac Standalone & Preview Editor : OSX 10.9 or later
Build Linux Standalone & Preview Editor : Ubuntu16.04 or later
Add WebGL platform Supports!
A new target platform has been added to our Unity Asset “OpenCVForUnity” and “DlibFaceLandmarkDetector“. With this update, it is now possible to develop WebGL applications that users can easily play with web browsers. Although it is currently in beta version, it seems that the main functions are working without problems. It works with Unity 5.3 or later. Demo Application Click To Start Development Tips Put a file that you want to use for the Utils.getFilePathAsync() in the “Aseets/StreamingAssets/” folder. In Case of WebGL platform, you need to use the Utils.getFilePathAsync() instead of the Utils.getFilePath(). (The haarcascade_frontalface_alt.xml is for OpenCVForUnityExample’s scenes. Please copy only when necessary) On the WebGL platform (asm.js), the calculation result of Float type may be significantly different from other platforms. When using the OpenCV’s method that use the Mat class (CvType is CV_32F) as an argument, you need to pay attention to the calculation precision. Please try experiencing WebGL development.
