it's stranage to use option "level" in runtime change path but used
"quality" in option, add "quality" in runtime change path, it's more
intuitive and keep the "level" for compatibility.
Reviewe-by: Michael Niedermayer <michael@niedermayer.cc>
Signed-off-by: Jun Zhao <barryjzhao@tencent.com>
libavformat/img2.h: New field export_path_metadata to
VideoDemuxData to only allow the use of the extra metadata
upon explicit user request, for security reasons.
libavformat/img2dec.c: Modify image2 demuxer to make available
two special metadata entries called lavf.image2dec.source_path
and lavf.image2dec.source_basename, which represents, respectively,
the complete path to the source image for the current frame and
the basename i.e. the file name related to the current frame.
These can then be used by filters like drawtext and others. The
metadata fields will only be available when explicitly enabled
with image2 option -export_path_metadata 1.
doc/demuxers.texi: Documented the new metadata fields available
for image2 and how to use them.
doc/filters.texi: Added an example on how to use the new metadata
fields with drawtext filter, in order to plot the input file path
to each output frame.
Usage example:
ffmpeg -f image2 -export_path_metadata 1 -pattern_type glob
-framerate 18 -i '/path/to/input/files/*.jpg'
-filter_complex drawtext="fontsize=40:fontcolor=white:
fontfile=FreeSans.ttf:borderw=2:bordercolor=black:
text='%{metadata\:lavf.image2dec.source_basename\:NA}':x=5:y=50"
output.avi
Fixes#2874.
Signed-off-by: Alexandre Heitor Schmidt <alexandre.schmidt@gmail.com>
Signed-off-by: Marton Balint <cus@passwd.hu>
The following is a python script to halve the value of the gray
image. 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
from skimage import color
from skimage import io
in_img = io.imread('input.jpg')
in_img = color.rgb2gray(in_img)
io.imsave('ori_gray.jpg', np.squeeze(in_img))
in_data = np.expand_dims(in_img, axis=0)
in_data = np.expand_dims(in_data, axis=3)
filter_data = np.array([0.5]).reshape(1,1,1,1).astype(np.float32)
filter = tf.Variable(filter_data)
x = tf.placeholder(tf.float32, shape=[1, None, None, 1], 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())
graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'halve_gray_float.pb', as_text=False)
print("halve_gray_float.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate halve_gray_float.model\n")
output = sess.run(y, feed_dict={x: in_data})
output = output * 255.0
output = output.astype(np.uint8)
io.imsave("out.jpg", np.squeeze(output))
To do the same thing with ffmpeg:
- generate halve_gray_float.pb with the above script
- generate halve_gray_float.model with tools/python/convert.py
- try with following commands
./ffmpeg -i input.jpg -vf format=grayf32,dnn_processing=model=halve_gray_float.model:input=dnn_in:output=dnn_out:dnn_backend=native out.native.png
./ffmpeg -i input.jpg -vf format=grayf32,dnn_processing=model=halve_gray_float.pb:input=dnn_in:output=dnn_out:dnn_backend=tensorflow out.tf.png
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
do not request AVFrame's format in vf_ddn_processing with 'fmt',
but to add another filter for the format.
command examples:
./ffmpeg -i input.jpg -vf format=bgr24,dnn_processing=model=halve_first_channel.model:input=dnn_in:output=dnn_out:dnn_backend=native -y out.native.png
./ffmpeg -i input.jpg -vf format=rgb24,dnn_processing=model=halve_first_channel.model:input=dnn_in:output=dnn_out:dnn_backend=native -y out.native.png
Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
In order to access the original opaque parameter of a buffer in the buffer
pool. (The buffer pool implementation overrides the normal opaque parameter but
also saves it so it is accessible).
v2: add assertion check before dereferencing the BufferPoolEntry.
Signed-off-by: Marton Balint <cus@passwd.hu>
ts_target_bitrate is in kbps, not bps. This commit clarifies the unit
and modifies the example to match the description.
Signed-off-by: James Zern <jzern@google.com>
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>
add linger parameter to libsrt, it's setting the number of seconds
that the socket waits for unsent data when closing.
Reviewed-by: Andriy Gelman <andriy.gelman@gmail.com>
Signed-off-by: Jun Zhao <barryjzhao@tencent.com>
Adjustment of evaluated values shifted to ff_adjust_scale_dimensions
Shifted code for force_original_aspect_ratio and force_divisble_by from
vf_scale so it is now available for scale_cuda, scale_npp and
scale_vaapi as well.
This sets the range of the first automatically assigned PMT PID or elementary
stream PID parameters to [0x20, 0x1ffa]. You can still assign manually a PID
for a stream using AVStream->id in the wider [0x10, 0x1ffe] range as specified
by ISO13818-1. But since DVB and ATSC both reserves some PIDs, let's not allow
them to be automatically assigned.
Also make sure that assigned PID numbers are valid and fix the error message
for the previous PID collision checks.
Signed-off-by: Marton Balint <cus@passwd.hu>
Disable by default to output all the layers, to match libaomdec wrapper.
Add option to select the operating point for the spatial layers.
Update the documentation with the new options.
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>
This introduces two new AVOption options for the FTP protocol,
one named ftp-user to supply the username to be used for auth,
one named ftp-password to supply the password to be used for auth.
These are useful for when an API user does not wish to deal with
URL manipulation and percent encoding.
Setting them while also having credentials in the URL will use the
credentials from the URL. The rationale for this is that credentials
embedded in the URL are probably more specific to what the user is
trying to do than anything set by some API user.
Signed-off-by: Nicolas Frattaroli <ffmpeg@fratti.ch>
Signed-off-by: Marton Balint <cus@passwd.hu>
Allows user to set maximum number of buffered packets when
probing a codec. It was a hard-coded parameter before this commit.
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
Implemented as a variant of the hash muxer, reusing most functions,
and making use of the previously introduced array of hashes.
Signed-off-by: Moritz Barsnick <barsnick@gmx.net>
Reviewed-by: James Almer <jamrial@gmail.com>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
When ffmpeg was streaming, multiple clients were only supported by using a
multicast destination address. An alternative was to stream to a server which
re-distributes the content. This commit adds ZeroMQ as a protocol, which allows
multiple clients to connect to a single ffmpeg instance.
Signed-off-by: Marton Balint <cus@passwd.hu>
This is an alias for JEDEC P22.
The name associated with the value is also changed
from jedec-p22 to ebu3213 to match ITU-T H.273.
Signed-off-by: Raphaël Zumer <rzumer@tebako.net>
Signed-off-by: James Almer <jamrial@gmail.com>
Added linux support for amf encoder through vulkan.
To use h.264(AMD VCE) encoder on linux amdgru-pro version 19.20+ and
amf-amdgpu-pro package(amdgru-pro contains, but does not install
automatically) are required.
This driver can be installed using amdgpu-pro-install script in
official amd driver archive.
Initialization of amf encoder occurs in this order:
1) trying to initialize through dx11(only windows)
2) trying to initialize through dx9(only windows)
3) trying to initialize through vulkan
Only Vulkan initialization available on linux.
Add the support of dehaze filter in existing derain filter source
code. As the processing procedure in FFmpeg is the same for current
derain and dehaze, we reuse the derain filter source code. The
model training and generation scripts are in repo
https://github.com/XueweiMeng/derain_filter.git
Reviewed-by: Steven Liu <lq@onvideo.cn>
Signed-off-by: Xuewei Meng <xwmeng96@gmail.com>
The packet counting based approach caused excessive sdt/pat/pmt for VBR, so
let's use a timestamp based approach instead similar to how we emit PCRs.
SDT/PAT/PMT period should be consistent for both VBR and CBR from now on.
Also change the type of sdt_period and pat_period to AV_OPT_TYPE_DURATION so no
floating point math is necessary.
Fixes ticket #3714.
Signed-off-by: Marton Balint <cus@passwd.hu>
Add the usage of tensorflow model in derain filter. Training scripts
as well as scripts for tf/native model generation are provided in the
repository at https://github.com/XueweiMeng/derain_filter.git.
Reviewed-by: Steven Liu <lq@onvideo.cn>
Signed-off-by: Xuewei Meng <xwmeng96@gmail.com>
These functions can be used to print a variable number of strings consecutively
to the IO context. Unlike av_bprintf, no temporary buffer is necessary.
Signed-off-by: Marton Balint <cus@passwd.hu>
This patch adds a new option to the scale filter which ensures that the
output resolution is divisible by the given integer when used together
with `force_original_aspect_ratio`. This works similar to using `-n` in
the `w` and `h` options.
This option respects the value set for `force_original_aspect_ratio`,
increasing or decreasing the resolution accordingly.
The use case for this is to set a fixed target resolution using `w` and
`h`, to use the `force_original_aspect_ratio` option to make sure that
the video always fits in the defined bounding box regardless of aspect
ratio, but to also make sure that the calculated output resolution is
divisible by n so in can be encoded with certain encoders/options if
that is required.
Signed-off-by: Lars Kiesow <lkiesow@uos.de>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
The awnser which most people will seek is put first
Reviewed-by: Thilo Borgmann <thilo.borgmann@mail.de>
Signed-off-by: Michael Niedermayer <michael@niedermayer.cc>
