YV12 format is supported by Nvidia NVENC without manual conversion.
So nvenc is exposing YV12 format at sinkpad template but there is some
missing point around uploading the memory to GPU.
Currently h264parser produces a field or a frame for
alignment=au for interlaced streams, but the flag
MFX_BITSTREAM_COMPLETE_FRAME needs a complete frame
or complementary field pair of data, this results in
broken images being output.
Some patches have been sent out to fix h264parser,
but they are pending on some unfinished work. In
order to make gstreamer-msdk decoding work properly
for interlaced streams before h264parser is fixed,
this flag will be removed temporarily and will be
added back once h264parser if fixed.
Related to:
https://gitlab.freedesktop.org/gstreamer/gst-plugins-bad/merge_requests/399https://gitlab.freedesktop.org/gstreamer/gst-plugins-bad/merge_requests/228
Instead of using the information we stored ourselves for the video frame
itself. Which was also the wrong one: it was the mode from the property,
not the autodetected one.
This fixes vanc extraction with mode=auto
The gst_cuda_result macro function is more helpful for debugging
than previous cuda_OK because gst_cuda_result prints the function
and line number. If the CUDA API return was not CUDA_SUCCESS,
gst_cuda_result will print WARNING level debug message with
error name, error text strings.
... 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.
... and add support CUDA context sharing similar to glcontext sharing.
Multiple CUDA context per GPU is not the best practice. The context
sharing method is very similar to that of glcontext. The difference
is that there can be multiple context object on a pipeline since
the CUDA context is created per GPU id. For example, a pipeline
has nvh264dec (uses GPU #0) and nvh264device0dec (uses GPU #1),
then two CUDA context will propagated to all pipeline.
New object and helper functions can remove duplicated code
from nvenc/nvdec. Also this is prework for CUDA device context sharing
among nvdec(s)/nvenc(s).
We don't support negotiation with downstream but simply set caps based
on the buffers we receive. This prevents renegotiation to other formats,
and negotiation to NTSC in mode=auto in the beginning until the first
buffer is received.
As side-effect of this, also remove various other caps handling code
that was working around the behaviour of the default
BaseSrc::negotiate().
During GstVideoInfo conversion from GstCaps, interlace-mode is
inferred to progressive so unspecified interlace-mode should not cause any
negotiation issue. Simly set GST_PAD_FLAG_ACCEPT_INTERSECT flag
on sinkpad to fix issue.
Encoded bitstream might not have valid framerate. If upstream
provided non-variable-framerate (i.e., fps_n > 0 and fps_d > 0)
use upstream framerate instead of parsed one.
Encoding thread is terminated without any notification so
upstream streaming thread is locked because there is nothing
to pop from GAsyncQueue. If downstream returns error,
we need put SHUTDOWN_COOKIE to GAsyncQueue for chain function
can wakeup.
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)
False warning from MSVC, or it does not understand that
g_assert_not_reached() does not return.
...\gst-plugins-bad-1.0-1.17.0.1\sys\decklink\gstdecklink.cpp(1647) : warning C4715: 'gst_decklink_configure_duplex_mode': not all control paths return a value
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.
Since we build nvcodec plugin without external CUDA dependency,
CUDA and en/decoder library loading failure can be natural behavior.
Emit error only when the module was opend but required symbols are missing.
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.
GstVideoDecoder::drain/flush can be called at very initial state
with stream-start and flush-stop event, respectively.
Draning with NULL CUvideoparser seems to unsafe and that eventually
failed to handle it.
It is possible that the output region size (e.g. 192x144) is different
from the coded picture size (e.g. 192x256). We may adjust the alignment
parameters so that the padding is respected in GstVideoInfo and use
GstVideoInfo to calculate mfx frame width and height
This fixes the error below when decoding a stream which has different
output region size and coded picture size
0:00:00.057726900 28634 0x55df6c3220a0 ERROR msdkdec
gstmsdkdec.c:1065:gst_msdkdec_handle_frame:<msdkh265dec0>
DecodeFrameAsync failed (failed to allocate memory)
Sample pipeline:
gst-launch-1.0 filesrc location=output.h265 ! h265parse ! msdkh265dec !
glimagesink
... and add our stub cuda header.
Newly introduced stub cuda.h file is defining minimal types in order to
build nvcodec plugin without system installed CUDA toolkit dependency.
This will make cross-compile possible.
* By this commit, if there are more than one device,
nvenc element factory will be created per
device like nvh264device{device-id}enc and nvh265device{device-id}enc
in addition to nvh264enc and nvh265enc, so that the element factory
can expose the exact capability of the device for the codec.
* Each element factory will have fixed cuda-device-id
which is determined during plugin initialization
depending on the capability of corresponding device.
(e.g., when only the second device can encode h265 among two GPU,
then nvh265enc will choose "1" (zero-based numbering)
as it's target cuda-device-id. As we have element factory
per GPU device, "cuda-device-id" property is changed to read-only.
* nvh265enc gains ability to encoding
4:4:4 8bits, 4:2:0 10 bits formats and up to 8K resolution
depending on device capability.
Additionally, I420 GLMemory input is supported by nvenc.
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.
