Face SDK v3.19.2

Bug Fixes and Improvements

• Fixed app_id generation for Android 11+.
• Resolved a licensing error when running multiple Face SDK processes from different users.
• Fixed improper functioning of VideoWorker in Flutter.
• Fixed an error when using online licenses on Android 9.

Face SDK v3.18.2

Bug Fixes and Improvements

• Fixed app_id generation for Android 11+.
• Resolved a licensing error when running multiple Face SDK processes under different users.
• Fixed an error when using online licenses on Android 9.

Face SDK v3.20.0

What's new

• Updated Flutter version, now SDK supports versions 3.0.0 - 3.16.6
• Updated C# API, now SDK supports .NET 6
• Processing Blocks API is now available as part of C# API
• Processing Block API now has all the blocks needed for face recognition
• New model for gender estimation, which allows you to get slightly more accurate results

Bug Fixes and Improvements

• Fixed a bug with licensing on Android 9

Face SDK v3.19.1

Bug Fixes and Improvements

• Fixed bug with using Tensorflow libraries on Nvidia Jetson.
• Added new VideoWorker configurations with ssyv detectors.
• Minor fixes for Flutter API.
• Addition of FaceAttributesEstimator to Flutter API.
• Added support for use_legacy flag for gender, age, and emotion estimators.
• Fixed a bug that caused the VideoWorker store_original_image flag to not work.

Face SDK v3.18.1

Bug Fixes and Improvements

• Fixed incorrect hash sum of tensorflow libraries for jetpack 4.4, 4.3.
• Fixed excessive RAM consumption when using ONNX models in VideoWorker.
• Fixed memory allocation defect for recognition method 12v50.
• Improved performance of face detectors when used in multithreaded mode.

Face SDK v3.17.3

Bug Fixes and Improvements

• Fixed incorrect hash sum of tensorflow libraries for jetpack 4.4, 4.3.
• Fixed excessive RAM consumption when using ONNX models in VideoWorker.
• Fixed memory allocation defect for recognition method 12v50.
• Improved performance of face detectors when used in multithreaded mode.

Face SDK v3.19.0

What's new

• Added new improved versions of Liveness Detection and Quality Assurance Assessment (QAA) modules
• Accelerated template comparison procedure. Now it will be faster to work with huge databases of faces.
• Added Capturer configurations for different business cases. Now the user can get a face detector configured for a specific task without wasting time on selecting the best detector and its parameters.
• Processing Block API has been significantly extended. Proven detectors from the old API (ULD and BLF) have been added to the new API, and a number of new ones have been added. A Fitter block has been added. Facial recognition blocks are available in beta mode.
• Added Processing Block demo for the Flutter API.
• Updated the default versions of CUDA and ONNX used by Face SDK.

Bug Fixes and Improvements

• Fixed a bug causing excessive RAM consumption when using the REFA detector
• Fixed a bug causing a memory segmentation error when using an empty template_index in the Python API
• Improved performance of face detectors when used in multithreaded mode

Face SDK v3.18.0

What's new

• Added CUDA 11 version support
• Added Flutter API documentation

Bug Fixes and Improvements

• Updated Flutter support to 3.3.0 ≤ versions ≤ 3.10.0

Face SDK v3.17.2

Bug Fixes and Improvements:

• Updated "score" formula for Recognizers
• Fixed recognizer score in VideoWorker
• Fixed bug with 12v face recognition methods on 32-bit systems

Face SDK v3.17.1

What's new

• Added new parameters for recognizers: num_threads, inter_op_num_threads and execution_mode
• Added ability to pass encoded images to Capturer through Python API
• Added examples of using Processing Blocks in Python

Bug Fixes and Improvements

• Updated "score" formula for recognizers
• Fixed a bug in BLF detector
• Fixed a bug on С# occurred when using Recognizer < 12.x with CUDA acceleration
• Fixed a bug which led to a "segfault" when recreating the FacerecService
• Fixed a bug with a license on Flutter
• Fixed a bug in Python API which led to memory leak
• Fixed visualization bugs in processing_block_demo
• Fixed a bug in Python Samples occurred due to missing library path on Windows