Input stream might be silently changed without ::set_format() call.
Since nvdec has internal parser, nvdec element can figure out the format change
by itself.
Async CUDA operation with default stream (NULL CUstream) is not much
beneficial than blocking operation since all CUDA operations which belong
to the CUDA context will be synchronized with the default stream's operation.
Note that CUDA stream will share all resources of the corresponding CUDA context
but which can help parallel operation similar to the relation between thread and process
... and drop CUvideoctxlock usage. The CUvideoctxlock basically
has the identical role of cuda context push/pop but nvdec specific
way. Since we can share the CUDA context among encoders and decoders,
use CUDA context directly for accessing GPU API.
By adding system memory support for nvdec, both en/decoder
in the nvcodec plugin are able to be usable regardless of
OpenGL dependency. Besides, the direct use of system memory
might have less overhead than OpenGL memory depending on use cases.
(e.g., transcoding using S/W encoder)
Any plugin which returned FALSE from plugin_init will be blacklisted
so the plugin will be unusable even if an user install required runtime
dependency next time. So that's the reason why nvcodec returns TRUE always.
This commit is to remove possible misreading code.
This commit includes h265 main-10 profile support if the device can
decode it.
Note that since h264 10bits decoding is not supported by nvidia GPU for now,
the additional code path for h264 high-10 profile is a preparation for
the future Nvidia's enhancement.
Only the default device has been used by NVDEC so far.
This commit make it possible to use registered device id.
To simplify device id selection, GstNvDecCudaContext usage is removed.
By this commit, each codec has its own element factory so the
nvdec element factory is removed. Also, if there are more than one device,
additional nvdec element factory will be created per
device like nvh264device{device-id}dec, so that the element factory
can expose the exact capability of the device for the codec.
Callbacks of CUvideoparser is called on the streaming thread.
So the use of async queue has no benefit.
Make control flow straightforward instead of long while/switch loop.
... and put them into new nvcodec plugin.
* nvcodec plugin
Now each nvenc and nvdec element is moved to be a part of nvcodec plugin
for better interoperability.
Additionally, cuda runtime API header dependencies
(i.e., cuda_runtime_api.h and cuda_gl_interop.h) are removed.
Note that cuda runtime APIs have prefix "cuda". Since 1.16 release with
Windows support, only "cuda.h" and "cudaGL.h" dependent symbols have
been used except for some defined types. However, those types could be
replaced with other types which were defined by "cuda.h".
* dynamic library loading
CUDA library will be opened with g_module_open() instead of build-time linking.
On Windows, nvcuda.dll is installed to system path by CUDA Toolkit
installer, and on *nix, user should ensure that libcuda.so.1 can be
loadable (i.e., via LD_LIBRARY_PATH or default dlopen path)
Therefore, NVIDIA_VIDEO_CODEC_SDK_PATH env build time dependency for Windows
is removed.
