Adding the support to build FFMPEG with HW accelerated decode(nvdec) and
encode on aarch64 architecture.
Signed-off-by: Timo Rothenpieler <timo@rothenpieler.org>
The webm_chunk muxer requires the WebM muxer, yet it does not directly
require anything from libavformat/matroska.c (it does not even include
the corresponding header). So remove the dependency from the Makefile
and add a _select to configure.
Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@gmail.com>
vf_dnn_processing.c recently changed to use swscale to trasfer data
between AVFrame and dnn model.
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Linjie Fu <linjie.fu@intel.com>
Using a compiler with a different host triplet is considered
cross-compiling, even when it is for the same architecture as the
build system. With such a cross-compiler, it is still valid to
optimize builds with --cpu=host. Make the condition that aborts in
this case into a warning instead, since a cross-compiler for an
incompatible architecture will fail with -mtune=native anyway.
Signed-off-by: David Michael <fedora.dm0@gmail.com>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
They use non-public functions, which is unacceptable for a public API
example. Rename the example back to avio_list_dir.
This effectively reverts c84d208c27 and
767d780ec0.
Supports connecting to a RabbitMQ broker via AMQP version 0-9-1.
Signed-off-by: Andriy Gelman <andriy.gelman@gmail.com>
Signed-off-by: Marton Balint <cus@passwd.hu>
The check_x86asm() checks would force enable these variables on success,
bypassing any --disable-* command line option.
This is important in the case of AVX512, where the relevant define is used
to choose between different values for memory alignment and strides in
some allocations.
Signed-off-by: James Almer <jamrial@gmail.com>
This commit adds a chromatic aberration filter for Vulkan that attempts to
emulate a lens chromatic aberration effect.
For a YUV frame it will instead shift the chroma channels, providing a
simple approximation.
This commit adds a Vulkan filtering infrastructure for libavfilter.
It attempts to abstract as much as possible of the Vulkan API from filters.
The way the hwcontext and the framework are designed permits for parallel,
non-CPU-blocking filtering throughout, with the exception of up/downloading
and mapping.
This commit adds the necessary code to initialize and use a Vulkan device
within the hwcontext libavutil framework.
Currently direct mapping to VAAPI and DRM frames is functional, and
transfers to CUDA and native frames are supported.
Lets hope the future Vulkan video decode extension fits well within this
framework.
SetConsoleTextAttribute used to be unavailable for Windows Store apps,
but is available to them now. But GetStdHandle still is unavailable,
thus make sure to check for both functions before using code that
requires both.
Signed-off-by: Martin Storsjö <martin@martin.st>
libx265.c references a member x265_picture.quantOffsets (for ROI
support) which was added in X265_BUILD 70. Increase the minimum libx265
version to fix compilation.
Signed-off-by: Andriy Gelman <andriy.gelman@gmail.com>
Reviewed-by: Derek Buitenhuis <derek.buitenhuis@gmail.com>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
"VAProcFilterParameterBufferHDRToneMapping" was defined in libva 2.4.1, which will lead to
build failure for the filter tonemap_vaapi for libva 2.3.0 with current check. This patch
is to fix this build error.
Signed-off-by: Xinpeng Sun <xinpeng.sun@intel.com>
When testing on a memory limited system, these tests consume a
significant amount of memory and can often fail if testing by running
multiple processes in parallel.
Signed-off-by: Martin Storsjö <martin@martin.st>
It performs HDR(High Dynamic Range) to SDR(Standard Dynamic Range) conversion
with tone-mapping. It only supports HDR10 as input temporarily.
An example command to use this filter with vaapi codecs:
FFMPEG -hwaccel vaapi -vaapi_device /dev/dri/renderD128 -hwaccel_output_format vaapi \
-i INPUT -vf 'tonemap_vaapi=format=p010' -c:v hevc_vaapi -profile 2 OUTPUT
Signed-off-by: Xinpeng Sun <xinpeng.sun@intel.com>
Signed-off-by: Zachary Zhou <zachary.zhou@intel.com>
Signed-off-by: Ruiling Song <ruiling.song@intel.com>
These functions aren't available when building for the restricted
UWP/WinRT/WinStore API subsets.
Normally when building in this mode, one is probably only building
the libraries, but being able to build ffmpeg.exe still is useful
(and a ffmpeg.exe targeting these API subsets still can be run
e.g. in wine, for testing).
Signed-off-by: Martin Storsjö <martin@martin.st>
fix when pkg-config fail and openssl > 1.1.0 --enable-openssl fail,
the root cause is check_lib can't found the SSL_library_init().
Reviewed-by: James Almer <jamrial@gmail.com>
Signed-off-by: macweng <macweng@tencent.com>
This BSF takes Temporal Units split across different AVPackets and merges them
by looking for Temporal Delimiter OBUs.
Signed-off-by: James Almer <jamrial@gmail.com>
This filter accepts all the dnn networks which do image processing.
Currently, frame with formats rgb24 and bgr24 are supported. Other
formats such as gray and YUV will be supported next. The dnn network
can accept data in float32 or uint8 format. And the dnn network can
change frame size.
The following is a python script to halve the value of the first
channel of the pixel. It demos how to setup and execute dnn model
with python+tensorflow. It also generates .pb file which will be
used by ffmpeg.
import tensorflow as tf
import numpy as np
import imageio
in_img = imageio.imread('in.bmp')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]
filter_data = np.array([0.5, 0, 0, 0, 1., 0, 0, 0, 1.]).reshape(1,1,3,3).astype(np.float32)
filter = tf.Variable(filter_data)
x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
y = tf.nn.conv2d(x, filter, strides=[1, 1, 1, 1], padding='VALID', name='dnn_out')
sess=tf.Session()
sess.run(tf.global_variables_initializer())
output = sess.run(y, feed_dict={x: in_data})
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'halve_first_channel.pb', as_text=False)
output = output * 255.0
output = output.astype(np.uint8)
imageio.imsave("out.bmp", np.squeeze(output))
To do the same thing with ffmpeg:
- generate halve_first_channel.pb with the above script
- generate halve_first_channel.model with tools/python/convert.py
- try with following commands
./ffmpeg -i input.jpg -vf dnn_processing=model=halve_first_channel.model:input=dnn_in:output=dnn_out:fmt=rgb24:dnn_backend=native -y out.native.png
./ffmpeg -i input.jpg -vf dnn_processing=model=halve_first_channel.pb:input=dnn_in:output=dnn_out:fmt=rgb24:dnn_backend=tensorflow -y out.tf.png
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
