Unity
Dlib FaceLandmark Detector
$19.99
Rated 5.0/5 from 49 ratings on Unity.
Price history
Recorded standalone sale prices and the latest available store price, in USD. Historical dots use the sale start date and its recorded offer price. Prices can change during a sale; this is not a daily price log. Bundle prices and upcoming offers are excluded. History covers up to the 100 most recent recorded offers.
Lowest recorded standalone price in this history: $19.99. The latest store price is $19.99, matching the lowest recorded price shown here.
View 4 recorded prices
| Sale start / price check | Price | Observation |
|---|---|---|
| $19.99 | Latest store price | |
| $19.99 | Unity Permanent Decrease 2026-09-27 2026-10-04 | |
| $20 | Unity Discount 2026-07-29 2026-08-12 | |
| $40 | Unity First Price 2026-07-29 2026-08-05 |
Sale and bundle history
The 3 most recent recorded offers including this asset. Past offers may no longer be available. Bundle prices cover a package, not this asset alone.
About Dlib FaceLandmark Detector
Dlib FaceLandmark Detector is a Unity plugin that lets you use Dlib19.7 C++ Library in Unity for object detection and shape prediction.
Cross Platform support. iOS & Android & Windows10 UWP support. Win & Mac & Linux Standalone support. WebGL support. ChromeOS support. visionOS support (beta). Support for preview in the Editor.
Object Detection & Shape Prediction: Detect frontal human faces and other objects using Histogram of Oriented Gradients (HOG) feature combined with a linear classifier, an image pyramid, and sliding window detection scheme. Shape Prediction: Detect face landmarks (68 points, 17 points, 6 points) 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). Custom Training: You can train your own object detector and shape predictor models using dlib's machine learning tools (Object Detector Training Tool, Shape Predictor Training Tool).
Easy to Use: Support for Texture2D, WebCamTexture, and Image byte array input. When combined with OpenCV for Unity, you can also input from OpenCV's Mat class for enhanced image processing capabilities. Helper functions for easy integration with Unity. FaceLandmarkDetector class implement Mat class for IDisposable, allowing you to manage resources using the using statement.
Include Many Examples: Includes a wide variety of example usage scenarios, which consist of scene files and script codes. By running these example applications, you can learn how to develop Dlib applications effectively. Basic Examples: Texture2D Example, WebCamTexture Example, Benchmark Example. Advanced Examples: Advanced examples using OpenCV for Unity (requires OpenCV for Unity).
Visual Scripting Support: You can take full advantage of all the features of DlibFaceLandmarkDetector in Unity's Visual Scripting. You can learn how to integrate them through the VisualScripting 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.
Cross Platform support. iOS & Android & Windows10 UWP support. Win & Mac & Linux Standalone support. WebGL support. ChromeOS support. visionOS support (beta). Support for preview in the Editor.
Object Detection & Shape Prediction: Detect frontal human faces and other objects using Histogram of Oriented Gradients (HOG) feature combined with a linear classifier, an image pyramid, and sliding window detection scheme. Shape Prediction: Detect face landmarks (68 points, 17 points, 6 points) 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). Custom Training: You can train your own object detector and shape predictor models using dlib's machine learning tools (Object Detector Training Tool, Shape Predictor Training Tool).
Easy to Use: Support for Texture2D, WebCamTexture, and Image byte array input. When combined with OpenCV for Unity, you can also input from OpenCV's Mat class for enhanced image processing capabilities. Helper functions for easy integration with Unity. FaceLandmarkDetector class implement Mat class for IDisposable, allowing you to manage resources using the using statement.
Include Many Examples: Includes a wide variety of example usage scenarios, which consist of scene files and script codes. By running these example applications, you can learn how to develop Dlib applications effectively. Basic Examples: Texture2D Example, WebCamTexture Example, Benchmark Example. Advanced Examples: Advanced examples using OpenCV for Unity (requires OpenCV for Unity).
Visual Scripting Support: You can take full advantage of all the features of DlibFaceLandmarkDetector in Unity's Visual Scripting. You can learn how to integrate them through the VisualScripting 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.