Tags: niley7464/nnstreamer
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Release of 2.0 Long-Term-Stable This is NNStreamer 2.0 Long-Term-Stable release. 2.0's main features after 1.8 release include: - Edge-AI capability (among-device AI) with pub/sub and query. In 2.0, this capability is an initial release without performance optimizations or feature extensions. We will eventually implement the promised optimizations and extensions with later (2.1+) versions. - Tensor stream types updated: flexible tensors and sparse tensors are now supported. Single-tensor (other/tensor) is being obsoleted. Please use other/tensors instead. - New H/W accelerators and AI frameworks supported - Tensor-converter/decoder with subplugins and custom functions - New elements: Tensor-IF, Join, Tensor-crop, Tensor-rate Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>
Release of NNStreamer 1.7.2 devel
This is a developmental release of NNStreamaer 1.7.2.
1.7.1 -> 1.7.2 (includes a huge amount of changes)
- NNStreamer for Edge-AI project started.
- Main festures of 1.8.0 release and its immediate successors will be "Edge-AI", which allows distributed on-device AI inferences.
- The new stream type, "Flex-Tensor", is introduced. Dimensions and types of tensor stream may vary per frame without cap-renegotiations.
- Many nnstreamer's tensor-* elements support Flex-Tensor.
- You may use tensor-converter to convert between flex-tensor and (static) tensor.
- MQTT-SINK and MQTT-SRC elements are added for edge-AI systems with MQTT pub/sub streams.
- MQTT streams support "ANY" capabilities.
- Assuming that clocks of nodes are synchronized by NTP or other mechanisms, pipeline users may send timestamp related info via MQTT streams for multi-source synchronization.
- Tensor-crop, a new nnstreamer-gstreamer element.
- Basic feature only (cropping a tensor stream with information of another tensor stream)
- Major features
- GSTPipeline to PBTXT parser. You can use PBTXT-pipeline visualization tools with the parsed results.
- FlexBuffers support.
- TVM support
- Tensor-IF with custom (user code plugged at run-time) conditions
- Tensorflow-lite delegation designation is generalized.
- Tensorflow2-lite XNNPACK delegation
- NNTrainer-inference can be attached as a filter along with both API sets.
- CAPI: updated documentation, added new enums for recent nnstreamer features, ...
- API interface and implementation is separated to another git repository for better architecture.
- Tensor-converter and Tensor-decoder support custom ops.
- Minor features
- Filter subplugin priority with ini file configuration.
- Decoder/Bounding-Box improved: output tensor mapping, clamp bounding box locations, labeling issues, more options.
- Decoder/Pose-Estimation improved: proper labeling.
- Testcases added for gRPC, Android, Tensor-rate, ...
- Refactoring (reduce complexity, remove duplicity, build options, ...)
- Android build & release upgraded.
- Converter usability upgrade: property to list subplugins, subplugin naming/install rules.
- Pytorch: exception handling, Android build
- gRPC: per-IDL packaging, interface updates, common-code revise, async mode, ...
- Support Tensorflow 2.4 API (TF has broken backward compatibility again)
- Tensor-transform: may operate on chosen tensor or channel only.
- Fixes
- Android resource leak.
- CAPI timing, header issues, seg-faults, memory leaks, ...
- MacOS build errors.
- TensorRT dependency bugs
- Edge-TPU compatibility issues.
- Unit test fixes (memory leaks, resource leaks, skip disabled features, ...)
- Fixed reported issues (security, memory leaks, query-caps, ...)
- Extra
- Support for Python 2.x is dropped.
- Automated doc-page generation with Hotdoc.
- Android build now includes GST-Shark for performance profiling.
Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>
Release of NNStreamer 1.7.1 devel
This is a developmental (unstable) release of NNStreamer 1.7.1.
1.7.0 -> 1.7.1
- Major features
- Tensor-IF, a new element. It allows to create conditional branches based on tensor values.
- Join, a new element. It merges output sinks from src pads of different elements with the same GST-Cap.
- Tensor-rate, a new element. It allows throttling by generating QoS messages.
- TensorRT support
- TF1-lite and TF2-lite coexistance
- TFx-lite NNAPI, GPU Delegation
- Minor features
- hw-accel options for tensor-filters are refactored
- python3-embed enabled if python3 >= 3.8
- Subplugin initialization optimization.
- Docker scripts for Ubuntu developers.
- Fixes
- flatbuf dependency related with tensorflow-lite.
- tensor-decoder configures framerate.
- Dynamic dimension related API issues fixed.
- MacOS, Yocto compatibility issues fixed. (A few Yocto known issues are still remaining.)
- License mismatches resolved.
- A few Test cases fixed.
- Packaging issues fixed and style cleaned-up.
- Extra
- A lot of interesting sample applications are added.
Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>
Release of NNStreamer 1.6.0 LTS This is NNStreamer 1.6.0 release along with - Tizen 6.0 M2 release - Android/Phone product release We will release 1.6.0 after all the internal testing/verification is completed. Hotfixes after this may create NNStreamaer 1.6.y. If new features are being merged after 1.6.0, we will branch out 1.6.y branch and start 1.7.x development from the main branch. Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>
Release of 1.4.0
Major changes since 1.2.0 release:
1.3.1 -> 1.4.0
- Stable release with API changes
- *Tensor-filter subplugin API has been updated.*
- Stability fixes & added unit test cases
- C-API updates
1.3.0 -> 1.3.1
- 1.3.1 is a devel version for 1.4.0 release.
- Support C++ class custom filters. (C++ class as a NN model)
- A tensor-filter instance may have multiple model files easily.
- Updated env-var handling logic for non-Tizen devices.
- Unit test: higher visibility & behavior correctness fixes.
- Auto-generated test cases for tensor-filter sub-plugins (extensions).
- Android/Java support with more convinient methods.
- Support gcc9
- Support openVino as a tensor-filter, allowing to accelerate with Intel NCS/Myriad.
- Support NCSDK as a tensor-filter.
- Support ARMNN as a tensor-filter. (support TF-Lite and Caffe models)
- Reduce asserts and add error handling routines.
- Support Androdi/SNAP as a tensor-filter.
- Support hardware accelerators & 8-bit quantization for NNFW-Runtime & stabilize NNFW-Runtime support with test cases.
- Support Edge-TPU and its runtime as a tensor-filter.
- Filter subplugins refactored to have a single source file (.cc)
- Support model reload
- A lot of fixes for bugs found by Coverity, SVACE, and other static analysis tools
1.2.0 -> 1.3.0:
- 1.3.0 is a devel version for 1.4.0 release.
- From 1.2.0, 1.even.x is a release and 1.odd.x is a devel version.
- When 1.3.x is "done", it will release 1.4.0 and move on to 1.5.0
Signed-off-by: MyungJoo Ham <myungjoo.ham@samsung.com>
[TestCoverage/Fix] Generate test coverage results in gcc-9 env. This commit generates test coverage results in gcc-9 env. But, it requires the latest version of lcov, and some perl modules. So, this should be done only in CI servers that can hold cached rpm files. Signed-off-by: Dongju Chae <dongju.chae@samsung.com>
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