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.
