noteVisage Technologies strives to minimize changes in API and configuration files when releasing new versions of the SDK. The inevitable changes are listed here, together with specific instructions for developers who have the existing applications built with older versions.
For each visage|SDK release, the incremental changes in relation to the previous release are listed. To apply the changes correctly, apply them in order from the older version to the newer version without skipping intermediary versions.
Visage Technologies strives to minimize changes in API and configuration files when releasing new versions of the SDK. The inevitable changes are listed here, together with specific instructions for developers who have the existing applications built with older versions.
For each visage|SDK release, the incremental changes in relation to the previous release are listed. To apply the changes correctly, apply them in order from the older version to the newer version without skipping intermediary versions.
Contents
visage|SDK 8.7
General
The in-house developed runner is no longer available and is being replaced by OpenVINO™ toolkit, which is now the only and default neural network runner. OpenVINO™ toolkit significantly improves the performance of visage|SDK algorithms. |
It is implemented in the following libraries: OVPlugin.dll, inference_engine.dll, MKLDNNPlugin.dll, mkl_tiny_tbb.dll, tbb.dll libmmd.dll, svml_dispmd.dll
These libraries are dependencies of libVisageVision64.dll and should now be included in projects along with other visage|SDK libraries. Additionally, OpenVINO™ toolkit requires its own set of data files with extensions .vino.bin and .vino.xml provided in Samples/data/bdtsdata. |
OpenVINO is a trademark of Intel Corporation or its subsidiaries. |
The old face recognition model is being replaced by a smaller, faster and more accurate face recognition model. |
Introducing a more accurate and robust face detection model. The new model is used in face tracking and face detection when use_vnn configuration parameter is set to 1. Otherwise, the previous face detection model will be used. For more information about using VNN detection algorithm, please consult VisageTracker Configuration Manual, paragraph 2.1.Configuration parameters and VisageFeaturesDetector documentation. |
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VNN algorithm can now be configured for better performance, at the cost of feature points precision. This mode is enabled by setting use_vnn parameter in configuration file to 1. Recommended for usage when performance is preferred over feature points precision, e.g. when interested in fast performing head pose (head rotation and translation) estimation. |
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API changes
Added support for multiple image format for extractDescriptor() and addDescriptor() methods. extractDescriptor()
| In addition to RGB and grayscale, now accepts RGBA input image | addDescriptor()
| In addition to RGB, now accepts RGBA and grayscale input image |
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Changes in configuration file
use_vnn configuration parameter added to VisageFeaturesDetector configuration file FaceDetector.cfg (located in Samples/data/bdstdata) and set to value 1. VNN algorithm will be used in VisageFeaturesDetector API by default. |
use_vnn configuration parameter values changed and additional value added: Parameter value | Effect |
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0 | VNN algorithm is disabled, default tracking algorithm and detection model are used | 1 | VNN algorithm enabled in fast mode, at the cost of feature points precision | 2 | VNN algorithm enabled, improved precision, accuracy and robustness |
For detailed description of these changes, consult VisageTracker Configuration Manual, paragraph 2.1.Configuration parameters. VisageTracker Configuration Manual If you want to update your existing configuration files, it is recommended to copy the parameters values from Facial Features Tracker - Ultra.cfg configuration file supplied in this package. |
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Data files changes
As a consequence of improving algorithms, removing in-house developed runner, and improving VNN algorithm, there are certain changes in the data files. API | Status | Location | Files/Folders |
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VisageFaceRecognition
| | bdtsdata/NN/ | fr.bin | VisageFaceAnalyser
| | bdtsdata/LBF/vfadata/ad/ | ae.bin | VisageTracker
VisageFeaturesDetector
| | bdtsdata/NN/ | pr.bin, model.bin | VisageFaceRecognition
| | bdtsdata/FF/vnn/ | fr.vino.bin, fr.vino.xml | VisageTracker
VisageFeaturesDetector
| | bdtsdata/FF/vnn/ | ff.vino.bin, ff.vino.xml | VisageTracker
VisageFeaturesDetector
| | bdtsdata/NN/vnn | bdtsdata/NN/vnn |
Projects using older versions of these files should be updated to contain the newest data files from the bdtsdata folder. |
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Sample changes
VisageTrackerUnityPlugin Function _grabFrame() captures RGB image, instead of BGR image. VisageTrackerUnityDemo The previously used BGRATex texture shader for applying captured frame image data was replaced with RGBATex texture shader (Tracker.cs script). |
visage|SDK 8.6.1
General
To improve the performance of our algorithms and to support a wider variety of neural network models, we are introducing a configurable framework for choosing between different neural network runners. As a result, additional configuration file NeuralNet.cfg is now included in visage|SDK (located in Samples/data). This file allows the users to configure which runner will be used by visage|SDK. Users can choose between: For more information on the parameters of NeuralNet.cfg file see the API page. OpenVINO is a trademark of Intel Corporation or its subsidiaries. |
New experimental algorithm for face tracking and alignment introduced - VNN algorithm. For the price of slightly reduced tracking speed/performance, it significantly improves tracking quality and robustness. VisageTracker and VisageFeaturesDetector can be configured to use VNN algorithm via configuration parameter - use_vnn. For more information on use_vnn parameter, please consult VisageTracker Configuration Manual, paragraph 2.1.Configuration parameters and VisageTracker class documentation. |
It is recommended to use VNN algorithm with OpenVINO™ toolkit which significantly improves the speed of running neural networks, thus mitigating any performance reductions. OpenVINO is a trademark of Intel Corporation or its subsidiaries. |
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API changes
Introducing new C++ and C# API for programmatically changing VisageTracker configuration parameters, including new additional classes and templates: VisageConfiguration
| Modify configuration parameters on the fly | VsCfgArr
| Helper template structure for storing various VisageConfiguration array data types |
The aforementioned classes are used in conjunction with new VisageTracker methods: C++ | VisageConfiguration VisageTracker::getTrackerConfiguration()
| void VisageTracker::setTrackerConfiguration(VisageConfiguration &configuration)
| C# | VisageConfiguration VisageCSWrapper.VisageTracker.GetTrackerConfiguration()
| void VisageCSWrapper.VisageTracker.SetTrackerConfiguration(VisageConfiguration configuration)
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There are slight differences in usage between C++ and C#. For example, C++ API uses helper structure VsCfgArr to return specific data types where C# uses native C# types. |
VisageConfiguration and VsCfgArr class documentation contains more details and examples of usage in code.
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FDP group 10 (ears) has been extended from 10 to 24 points (12 points per ear) as part of the ear tracking feature. FDP files saved with visage|SDK 8.6 will not be backwards compatible with the previous versions due to the addition of new FDP points. Using FDP::readFromFile() to load an 8.6 FDP file in an earlier version of the visage|SDK will lead to undefined behavior. |
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VisageTracker method stop has been deprecated from both APIs.
C++ | VisageTracker::stop()
| C# | VisageCSWrapper.VisageTracker.Stop()
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Prototype of method void initializeLicenseManager(const char *licenseKeyFileName)
changed to int initializeLicenseManager(const char *licenseKeyFileName)
It is no longer necessary to declare the licensing function prototype explicitly within your code. Including any of the following headers will also include the licensing prototype: VisageTracker.h VisageFeaturesDetector.h VisageFaceRecognition.h VisageFaceAnalyser.h
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FeaturePoint class and FDP class have additional property and functions, respectively to conform with the C++ API.
FeaturePoint
| FeaturePoint.detected
| FDP
| bool FDP::FPIsDetected(int group, int n)
bool FDP::FPIsDetected(String name)
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1 indicates that the feature point is obtained from a 2D image using the tracking algorithm. 0 indicates that the feature point is estimated from fitting a 3D model onto the detected feature points of the face. |
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Changes in configuration file
Two additional configuration files have been added. One for the ear tracking feature and one for the novel tracking algorithm. Configuration name | Parameter changed/added | Parameter value |
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Facial Features Tracker - High - With Ears.cfg | efine_ears *_fitting_model *_fitting_fdp | 1 jk_300_wEars.wfm jk_300_wEars.fdp | Facial Features Tracker - Ultra.cfg | use_vnn | 1 |
For detailed description of these changes consult VisageTracker Configuration Manual, paragraph 1.1.Standard configuration files If you want to update your existing configuration files, it is recommended to copy the parameters values from Facial Features Tracker - Ultra.cfg configuration file supplied in this package. |
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Used together with ears 3D model - jk_300_wEars.wfm |
If you want to update your existing configuration files, it is recommended to copy the parameters values from Facial Features Tracker - High.cfg configuration file supplied in this package. |
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3D Model changes
A new model file has been added for ear tracking functionality - jk_300_wEars.wfm. The model contains an additional 334 polygons and its vertices are mapped to 14 new FDP points in group 10 (10.11 - 10.24). |
Data files changes
New data files and model files for ear tracking added Location | Files |
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Samples/data/bdtsdata/NN | efa.lbf efc.lbf | Samples/data/ | jk_300_wEars.wfm jk_300_wEars.fdp |
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New data folder and data files added for VNN algorithm in Samples/data/bdtsdata/NN/vnn Projects using older versions of these files should be updated to contain the newest data files from the bdtsdata folder. |
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Sample changes
FacialAnimationUnityDemo sample application has been removed and will no longer be distributed. |
VisageTrackerUnityDemo sample application is distributed as a Unity project, not as a prebuilt application. Build and run instructions are provided in the VisageTrackerUnityDemo sample documentation. Instructions on visage|SDK integration with Unity can be found here |
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visage|SDK 8.5
Changes in configuration file
If you want to update your existing configuration files, it is recommended to copy the parameters values from Facial Features Tracker - High.cfg configuration file supplied in this package. |
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Sample changes
VisageRendering.cs: Methods DisplayEmotion() and DisplayAgeGenderName() have changed the prototypes from: public void DisplayEmotion(FaceData trackingData, float[] emotions, int width, int height,
bool face_recognition_mode=false)
public void DisplayAgeGenderName(FaceData trackingData, float age, int gender, string name,
int width, int height, int drawingOptions,
bool face_recognition_mode=false) |
to: public void DisplayEmotion(FaceData trackingData, float[] emotions, int width, int height,
bool display_background = false)
public void DisplayAgeGenderName(FaceData trackingData, float age, int gender, string name,
int width, int height, bool display_background = true) |
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Build tools changes
Libraries built with msvc100 are no longer supported within the package.
Data files changes
visage|SDK data files located in Samples/data/bdtsdata folder have been updated.
Copy all files located in the Samples/data/bdtsdata folder to appropriate folders in any existing application.