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v0.1.1
NNStreamer 0.1.1 Release - Full "Plug & Play" capability of subplugins (tensor_filter, tensor_filter::custom, tensor_decoder) - Fully configurable subplugin locations - Capability to build subplungins wihtout the dependencies on nnstreamer sources - Revert Tensorflow input-memcpy-less-ness for multi-tensor support. (Will support memcpy-less-ness later) - Support "String" type of tensors - API sets updated (still not "stable") - Code location refactored. - Yocto/Openembedded Layer Registered (not tested): "meta-neural-network" - No more additional shared libraries. - Better error handling and messages for a few plugins - Android support (N / arm64)
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v0.1.0
Release of NNStreamer 0.1.0 Changes - Build system migration cmake --> meson - Support Tensorflow without input/output tensor memcpy - other/tensor stream format updated - From 0.1.0, a single property, "dimension", describes the whole dimension instead of "dim1", "dim2", ... - Objective 1: in the future, we may support tensors with more than 4 dimensions without updating the protocol. - Objective 2: it was just too ugly. - Example applications migrated to other git repo to make this repo ready for upstreaming in the fugure and to ensure buildability for third party developers. - Support run-time attaching subplugins (filter and decoder) - Support "ini" and envvar configurations for subplugin locations - Dynamic external recurrences - Subplugin API sets (draft. do not expect backward compatibility) - Bug fixes (memory leaks, incorrect logs, type checks, ...)
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v0.0.3
Release of version 0.0.3 0.0.2 -> 0.0.3: - Support external recurrencies with tensor_repo (more test cases are to be released later) - Support multi-operators with a single instance of tensor_transform (with a few limitations on the supported orders of operators) - Support split - Support bounding-box decoding (tensor_decoder) - Support subplugins for tensor_decoder - Internal APIs for dynamic configurations and subplugins. tensor_filter and tensor_decoder will be updated to use such configurations in the later releases. - Tensorflow support is in-progress, it's postponed to later releases. (Still, tensorflow-lite is the only framework officially supported) - Pipeviz support. (tensor_converter/filter/decoder) - Tested with MTCNN (each "part" is separated as an instance of tensor_filter). - Meson build introduced. - Released via build.tizen.org (Tizen Devel. x64/x86/arm32/arm64) and launchpad.net (Ubuntu/PPA. x64/x86/arm32/arm64) - Static build for Android (Not tested. No example. An example Android application is to be released later) - Timestamp handling / Synchronization support - AWS App Testing Enabled (testing nnstreamer application with virtual camera devices in AWS) - arm64 support added
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v0.0.1
NNStreamer release of version 0.0.1 Support single-tensored tensorflow-lite models with video streams. Provide limited types of tensor-supporting filters. No synchronization policy modifiers supplied, yet. There are a lot of Not-Yet-Implemented cases in the released filters. Example applications and unit tests are supplied.