General¶
Before you can call the SDK functions, you must first initialize the SDK with your desired configuration options. These configuration options will ultimately impact the behaviour of the SDK, so be sure to read through what each one does carefully.
Once you have initialized the SDK, then proceed to the the License section.
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class SDK¶
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Trueface::SDK::SDK()¶
Initialize the SDK using default ConfigurationOptions.
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Trueface::SDK::SDK(const ConfigurationOptions &options)¶
Initialize the SDK using custom ConfigurationOptions.
- Parameters
options – custom configuration options.
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static std::string Trueface::SDK::getVersion()¶
Gets the version-build number of the SDK.
- Returns
Version Number as a string.
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enum Trueface::FacialRecognitionModel¶
Facial recognition models. Refer to our ROC curves to compare model accuracy and our benchmarks page to compare inference speed. The current most accurate model is TFV7.
Values:
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enumerator LITE¶
Our most lightweight model with fastest inference time but lowest accuracy, ideal for embedded systems or lightweight CPU only deployments, prototyping, and some 1 to 1 matching use cases.
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enumerator LITE_V2¶
Lightweight model which has improved accuracy over the LITE model, though does have slightly greater inference time. Ideal for embedded systems or lightweight CPU only deployments, prototyping, and some 1 to 1 matching use cases.
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enumerator TFV5_2¶
TFV5_2 is a substitute for our TFV5 model which was available up until SDK version 1.8. This substitution was required due to model incompatibility with our new inference framework. The accuracy and inference speed are both comparable to TFV5. However, Faceprints are not compatible between the two models; if you would like to upgrade a collection containing TFV5 Faceprints to TFV5_2 Faceprints, you will need to regenerate and re-enroll Faceprints for all your images. TFV5_2 is currently the second highest accuracy model for unmasked face images. Inference time is faster than TFV7, but comparable to TFV6. Ideal for GPU deployments and for 1 to N use cases.
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enumerator TFV6¶
TFV6 is currently the second highest accuracy model for masked face images. Use TFV6 in situations where it is anticipated that the probe image contains a masked face (for 1 to N search), or where one or both face images are masked (for 1 to 1 comparisons). TFV6 has comparable inference time to TFV5_2, and is faster than TFV7.
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enumerator TFV7¶
TFV7 is currently our overall highest accuracy model, but it is also our slowest model. Ideal for GPU deployments and for 1 to N use cases.
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enumerator LITE¶
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enum Trueface::ObjectDetectionModel¶
Object detection models.
Values:
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enumerator ACCURATE¶
Resizes the input image to 1280x1280 (uses letterbox padding to maintain aspect ratio). Should be used for image where one or both dimensions are greater than 1280, and images with small objects.
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enumerator FAST¶
Resizes the input image to 640x640 (uses letterbox padding to maintain aspect ratio). Should be used for smaller images, or images with large objects.
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enumerator ACCURATE¶
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enum Trueface::FaceDetectionFilter¶
Filters the detected faces based on face detection score.
Values:
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enumerator HIGH_RECALL¶
Filter the detected faces based on a low score threshold. Limits false negatives (does not detect a face), but may have more false positives (classifies a non-face as a face).
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enumerator HIGH_PRECISION¶
Filter the detected faces based on a high score threshold. Limits false positives (classifies a non-face as a face), but may have more false negatives (does not detect a face).
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enumerator BALANCED¶
Filter the detected faces based on a medium score threshold to balance false positives and false negatives. We advise using this option most of the time.
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enumerator UNFILTERED¶
Do not filter the detected faces by score. Will have a large number of false positives (classifies a non-face as a face).
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enumerator HIGH_RECALL¶
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enum Trueface::Precision¶
Precision to use for GPU inference.
Values:
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enumerator FP32¶
32 bit floating point. Allows for highest accuracy but slower inference.
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enumerator FP16¶
16 bit floating point. Allows for faster inference but lower accuracy.
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enumerator FP32¶
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enum Trueface::DatabaseManagementSystem¶
Database Management System for storing Faceprints.
Values:
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enumerator SQLITE¶
Use sqlite backend. Write Faceprints to local disk. Ideal for embedded systems or use cases where only one process connects to the database.
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enumerator POSTGRESQL¶
Use a PostgreSQL 12.5 backend. Ideal for distributed systems requiring synchronization.
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enumerator NONE¶
Do not write Faceprints to disk, only store in ram. Warning, enrolled Faceprints will not be saved after the program terminates. Switching to a new collections will also delete all enrolled templates.
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enumerator SQLITE¶
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struct Trueface::GPUModuleOptions¶
GPU options for a specific module (ex. face detector).
Public Members
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int32_t maxBatchSize = 4¶
The maximum batch size which will be used.
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int32_t optBatchSize = 1¶
The batch size which should be optimized for. Must be less than or equal to
Trueface::GPUModuleOptions.maxBatchSize
.
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int32_t maxBatchSize = 4¶
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struct Trueface::GPUOptions¶
GPU options for the SDK. Note, GPU support requires a different version of the SDK. Default uses CPU for inference.
Public Functions
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inline GPUOptions(bool val)¶
Enable or disable GPU inference for all supported modules.
Public Members
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bool enableGPU = false¶
Enable GPU inference for all supported modules.
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unsigned int deviceIndex = 0¶
GPU device index.
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GPUModuleOptions faceDetectorGPUOptions = {}¶
Options for face detector GPU inference.
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GPUModuleOptions faceLandmarkDetectorGPUOptions = {}¶
Options for 106 face landmark detector GPU inference.
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GPUModuleOptions faceRecognizerGPUOptions = {}¶
Options for face recognizer GPU inference.
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GPUModuleOptions maskDetectorGPUOptions = {}¶
Options for mask detector GPU inference.
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GPUModuleOptions objectDetectorGPUOptions = {}¶
Options for object detector GPU inference.
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GPUModuleOptions faceOrientationDetectorGPUOptions = {}¶
Options for face orientation detector GPU inference.
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GPUModuleOptions faceBlurDetectorGPUOptions = {}¶
Options for face blur detector GPU inference.
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GPUModuleOptions spoofDetectorGPUOptions = {}¶
Options for spoof detector GPU inference.
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GPUModuleOptions blinkDetectorGPUOptions = {}¶
Options for blink detector GPU inference
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inline GPUOptions(bool val)¶
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Trueface::GPUOptions::GPUOptions() = default¶
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inline Trueface::GPUOptions::GPUOptions(bool val)
Enable or disable GPU inference for all supported modules.
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struct Trueface::InitializeModule¶
Initialize module in SDK constructor. By default, the SDK uses lazy initialization, meaning modules are only initialized when they are first used (on first inference). This is done so that modules which are not used do not load their models into memory, and hence do not utilize memory. The downside to this is that the first inference will be much slower as the model file is being decrypted and loaded into memory. Therefore, if you know you will use a module, choose to pre-initialize the module, which reads the model file into memory in the SDK constructor.
Public Members
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bool faceDetector = false¶
Face detector.
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bool faceRecognizer = false¶
Face recognizer.
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bool objectDetector = false¶
Object detector.
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bool bodyposeEstimator = false¶
Bodypose estimator.
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bool blinkDetector = false¶
Blink detector.
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bool activeSpoof = false¶
Active spoof.
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bool passiveSpoof = false¶
Passive spoof.
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bool landmarkDetector = false¶
106 face point landmark detector.
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bool maskDetector = false¶
Mask detector.
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bool faceOrientationDetector = false¶
Face orientation detector.
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bool faceBlurDetector = false¶
Face blur detector.
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bool eyeglassDetector = false¶
Eyeglass detector.
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bool faceDetector = false¶
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struct Trueface::EncryptDatabase¶
Encrypt the biometric templates and identity strings when storing in the database using AES encryption. Note, enabling this option does add overhead to Faceprint enrollment as well as loading a collection from a database into memory. Enabling encryption does not increase the 1 to N identification time.
Public Members
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bool enableEncryption = false¶
Enable database encryption. Must provide encryption key if encryption is enabled. If enabling encryption with PostgreSQL backend, it is strongly advised to require SSL for PostgreSQL connection.
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std::string key¶
Encryption key. The key is hashed to a fixed length before being used for encryption.
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bool enableEncryption = false¶
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struct Trueface::ConfigurationOptions¶
SDK configuration options.
Public Members
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int mobilePowerSave = 0¶
Android Only Power saving mode. 0 = all cores enabled (default). 1 = only little clusters enabled. 2 = only big clusters enabled.
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int mobileThreads = 4¶
Mobile Only Set the number of threads used for inference. For non-mobile platforms, should use the
OMP_NUM_THREADS
environment variable.
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size_t mobileAvailableMemory = 0¶
iOS Only SDK user must define how much memory is available for iOS application. Should be set using the following code:
#include <os/proc.h>
options.mobileAvailableMemory = os_proc_available_memory();
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FacialRecognitionModel frModel = FacialRecognitionModel::TFV5_2¶
The model to be used for facial recognition (default is TFV5_2).
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FaceDetectionModel fdModel = FaceDetectionModel::FAST¶
The model to be used for face detection (default is FAST).
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ObjectDetectionModel objModel = ObjectDetectionModel::ACCURATE¶
The model to be used for object detection (default is ACCURATE model).
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int smallestFaceHeight = 40¶
Filter the detected faces based on face height. (default is 40 pixels). You may choose to filter on size to reject faces which are too small as they may cause false positives. Note, the detector itself has inherent restrictions and can only detect faces in the following dynamic height range. Smallest detectable face = ((the larger of your image dimensions) / 640 * 20) pixels. Largest detectable face = (your image height) pixels.
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FaceDetectionFilter fdFilter = FaceDetectionFilter::BALANCED¶
The face detection filter (default is BALANCED).
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DatabaseManagementSystem dbms = DatabaseManagementSystem::SQLITE¶
Database management system for storing Faceprints (default is SQLITE).
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std::string modelsPath = "./"¶
Path specifying the directory which contains the model files.
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bool frVectorCompression = false¶
Improves 1 to 1 Faceprint comparison times and 1 to N search speeds by compressing the feature vector and enabling additional optimizations. Also reduces the memory required to store each Faceprint. (default is false)
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GPUOptions gpuOptions = GPUOptions{false}¶
Options for enabling and configuring GPU inference. Default uses CPU inference. Note, GPU support requires a different version of the SDK. You can easily enable GPU inference for all supported modules by setting this option to true.
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InitializeModule initializeModule = {}¶
Initialize specified modules in the SDK constructor (default uses lazy initialization).
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EncryptDatabase encryptDatabase = {}¶
Encrypt the biometric templates and identity strings when storing in the database using AES encryption (default is disabled).
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int mobilePowerSave = 0¶
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enum Trueface::ErrorCode¶
Error codes returned by methods.
Values:
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enumerator NO_ERROR¶
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enumerator INVALID_LICENSE¶
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enumerator FILE_READ_FAIL¶
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enumerator UNSUPPORTED_IMAGE_FORMAT¶
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enumerator UNSUPPORTED_MODEL¶
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enumerator NO_FACE_IN_FRAME¶
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enumerator FAILED¶
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enumerator COLLECTION_CREATION_ERROR¶
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enumerator DATABASE_CONNECTION_ERROR¶
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enumerator ENROLLMENT_ERROR¶
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enumerator MAX_COLLECTION_SIZE_EXCEEDED¶
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enumerator NO_RECORD_FOUND¶
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enumerator NO_COLLECTION_FOUND¶
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enumerator COLLECTION_DELETION_ERROR¶
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enumerator EXTREME_FACE_ANGLE¶
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enumerator FACE_TOO_CLOSE¶
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enumerator FACE_TOO_FAR¶
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enumerator FACE_TOO_SMALL¶
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enumerator FACE_NOT_CENTERED¶
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enumerator EYES_CLOSED¶
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enumerator MASK_DETECTED¶
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enumerator TOO_DARK¶
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enumerator TOO_BRIGHT¶
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enumerator DATABASE_NOT_CONNECTED¶
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enumerator COLLECTION_NOT_LOADED¶
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enumerator FEATURE_NOT_SUPPORTED¶
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enumerator COLLECTION_IS_EMPTY¶
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enumerator INPUT_IS_EMPTY¶
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enumerator STRING_CANNOT_CONTAIN_HYPHEN¶
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enumerator NO_ERROR¶