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doc/filters: fix alphabetic order of some video filters

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doc/filters.texi
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...@@ -6905,6 +6905,66 @@ colorbalance=rs=.3 ...@@ -6905,6 +6905,66 @@ colorbalance=rs=.3
@end example @end example
@end itemize @end itemize
@section colorchannelmixer
Adjust video input frames by re-mixing color channels.
This filter modifies a color channel by adding the values associated to
the other channels of the same pixels. For example if the value to
modify is red, the output value will be:
@example
@var{red}=@var{red}*@var{rr} + @var{blue}*@var{rb} + @var{green}*@var{rg} + @var{alpha}*@var{ra}
@end example
The filter accepts the following options:
@table @option
@item rr
@item rg
@item rb
@item ra
Adjust contribution of input red, green, blue and alpha channels for output red channel.
Default is @code{1} for @var{rr}, and @code{0} for @var{rg}, @var{rb} and @var{ra}.
@item gr
@item gg
@item gb
@item ga
Adjust contribution of input red, green, blue and alpha channels for output green channel.
Default is @code{1} for @var{gg}, and @code{0} for @var{gr}, @var{gb} and @var{ga}.
@item br
@item bg
@item bb
@item ba
Adjust contribution of input red, green, blue and alpha channels for output blue channel.
Default is @code{1} for @var{bb}, and @code{0} for @var{br}, @var{bg} and @var{ba}.
@item ar
@item ag
@item ab
@item aa
Adjust contribution of input red, green, blue and alpha channels for output alpha channel.
Default is @code{1} for @var{aa}, and @code{0} for @var{ar}, @var{ag} and @var{ab}.
Allowed ranges for options are @code{[-2.0, 2.0]}.
@end table
@subsection Examples
@itemize
@item
Convert source to grayscale:
@example
colorchannelmixer=.3:.4:.3:0:.3:.4:.3:0:.3:.4:.3
@end example
@item
Simulate sepia tones:
@example
colorchannelmixer=.393:.769:.189:0:.349:.686:.168:0:.272:.534:.131
@end example
@end itemize
@section colorkey @section colorkey
RGB colorspace color keying. RGB colorspace color keying.
...@@ -7031,66 +7091,6 @@ colorlevels=romin=0.5:gomin=0.5:bomin=0.5 ...@@ -7031,66 +7091,6 @@ colorlevels=romin=0.5:gomin=0.5:bomin=0.5
@end example @end example
@end itemize @end itemize
@section colorchannelmixer
Adjust video input frames by re-mixing color channels.
This filter modifies a color channel by adding the values associated to
the other channels of the same pixels. For example if the value to
modify is red, the output value will be:
@example
@var{red}=@var{red}*@var{rr} + @var{blue}*@var{rb} + @var{green}*@var{rg} + @var{alpha}*@var{ra}
@end example
The filter accepts the following options:
@table @option
@item rr
@item rg
@item rb
@item ra
Adjust contribution of input red, green, blue and alpha channels for output red channel.
Default is @code{1} for @var{rr}, and @code{0} for @var{rg}, @var{rb} and @var{ra}.
@item gr
@item gg
@item gb
@item ga
Adjust contribution of input red, green, blue and alpha channels for output green channel.
Default is @code{1} for @var{gg}, and @code{0} for @var{gr}, @var{gb} and @var{ga}.
@item br
@item bg
@item bb
@item ba
Adjust contribution of input red, green, blue and alpha channels for output blue channel.
Default is @code{1} for @var{bb}, and @code{0} for @var{br}, @var{bg} and @var{ba}.
@item ar
@item ag
@item ab
@item aa
Adjust contribution of input red, green, blue and alpha channels for output alpha channel.
Default is @code{1} for @var{aa}, and @code{0} for @var{ar}, @var{ag} and @var{ab}.
Allowed ranges for options are @code{[-2.0, 2.0]}.
@end table
@subsection Examples
@itemize
@item
Convert source to grayscale:
@example
colorchannelmixer=.3:.4:.3:0:.3:.4:.3:0:.3:.4:.3
@end example
@item
Simulate sepia tones:
@example
colorchannelmixer=.393:.769:.189:0:.349:.686:.168:0:.272:.534:.131
@end example
@end itemize
@section colormatrix @section colormatrix
Convert color matrix. Convert color matrix.
...@@ -7612,6 +7612,40 @@ ffmpeg -f lavfi -i nullsrc=s=100x100,coreimage=filter=CIQRCodeGenerator@@inputMe ...@@ -7612,6 +7612,40 @@ ffmpeg -f lavfi -i nullsrc=s=100x100,coreimage=filter=CIQRCodeGenerator@@inputMe
@end example @end example
@end itemize @end itemize
@section cover_rect
Cover a rectangular object
It accepts the following options:
@table @option
@item cover
Filepath of the optional cover image, needs to be in yuv420.
@item mode
Set covering mode.
It accepts the following values:
@table @samp
@item cover
cover it by the supplied image
@item blur
cover it by interpolating the surrounding pixels
@end table
Default value is @var{blur}.
@end table
@subsection Examples
@itemize
@item
Cover a rectangular object by the supplied image of a given video using @command{ffmpeg}:
@example
ffmpeg -i file.ts -vf find_rect=newref.pgm,cover_rect=cover.jpg:mode=cover new.mkv
@end example
@end itemize
@section crop @section crop
Crop the input video to given dimensions. Crop the input video to given dimensions.
...@@ -9452,6 +9486,50 @@ edgedetect=mode=colormix:high=0 ...@@ -9452,6 +9486,50 @@ edgedetect=mode=colormix:high=0
@end example @end example
@end itemize @end itemize
@section elbg
Apply a posterize effect using the ELBG (Enhanced LBG) algorithm.
For each input image, the filter will compute the optimal mapping from
the input to the output given the codebook length, that is the number
of distinct output colors.
This filter accepts the following options.
@table @option
@item codebook_length, l
Set codebook length. The value must be a positive integer, and
represents the number of distinct output colors. Default value is 256.
@item nb_steps, n
Set the maximum number of iterations to apply for computing the optimal
mapping. The higher the value the better the result and the higher the
computation time. Default value is 1.
@item seed, s
Set a random seed, must be an integer included between 0 and
UINT32_MAX. If not specified, or if explicitly set to -1, the filter
will try to use a good random seed on a best effort basis.
@item pal8
Set pal8 output pixel format. This option does not work with codebook
length greater than 256.
@end table
@section entropy
Measure graylevel entropy in histogram of color channels of video frames.
It accepts the following parameters:
@table @option
@item mode
Can be either @var{normal} or @var{diff}. Default is @var{normal}.
@var{diff} mode measures entropy of histogram delta values, absolute differences
between neighbour histogram values.
@end table
@section eq @section eq
Set brightness, contrast, saturation and approximate gamma adjustment. Set brightness, contrast, saturation and approximate gamma adjustment.
...@@ -9627,50 +9705,6 @@ ffmpeg -i video.avi -filter_complex 'extractplanes=y+u+v[y][u][v]' -map '[y]' y. ...@@ -9627,50 +9705,6 @@ ffmpeg -i video.avi -filter_complex 'extractplanes=y+u+v[y][u][v]' -map '[y]' y.
@end example @end example
@end itemize @end itemize
@section elbg
Apply a posterize effect using the ELBG (Enhanced LBG) algorithm.
For each input image, the filter will compute the optimal mapping from
the input to the output given the codebook length, that is the number
of distinct output colors.
This filter accepts the following options.
@table @option
@item codebook_length, l
Set codebook length. The value must be a positive integer, and
represents the number of distinct output colors. Default value is 256.
@item nb_steps, n
Set the maximum number of iterations to apply for computing the optimal
mapping. The higher the value the better the result and the higher the
computation time. Default value is 1.
@item seed, s
Set a random seed, must be an integer included between 0 and
UINT32_MAX. If not specified, or if explicitly set to -1, the filter
will try to use a good random seed on a best effort basis.
@item pal8
Set pal8 output pixel format. This option does not work with codebook
length greater than 256.
@end table
@section entropy
Measure graylevel entropy in histogram of color channels of video frames.
It accepts the following parameters:
@table @option
@item mode
Can be either @var{normal} or @var{diff}. Default is @var{normal}.
@var{diff} mode measures entropy of histogram delta values, absolute differences
between neighbour histogram values.
@end table
@section fade @section fade
Apply a fade-in/out effect to the input video. Apply a fade-in/out effect to the input video.
...@@ -9762,6 +9796,40 @@ fade=t=in:st=5.5:d=0.5 ...@@ -9762,6 +9796,40 @@ fade=t=in:st=5.5:d=0.5
@end itemize @end itemize
@section fftdnoiz
Denoise frames using 3D FFT (frequency domain filtering).
The filter accepts the following options:
@table @option
@item sigma
Set the noise sigma constant. This sets denoising strength.
Default value is 1. Allowed range is from 0 to 30.
Using very high sigma with low overlap may give blocking artifacts.
@item amount
Set amount of denoising. By default all detected noise is reduced.
Default value is 1. Allowed range is from 0 to 1.
@item block
Set size of block, Default is 4, can be 3, 4, 5 or 6.
Actual size of block in pixels is 2 to power of @var{block}, so by default
block size in pixels is 2^4 which is 16.
@item overlap
Set block overlap. Default is 0.5. Allowed range is from 0.2 to 0.8.
@item prev
Set number of previous frames to use for denoising. By default is set to 0.
@item next
Set number of next frames to to use for denoising. By default is set to 0.
@item planes
Set planes which will be filtered, by default are all available filtered
except alpha.
@end table
@section fftfilt @section fftfilt
Apply arbitrary expressions to samples in frequency domain Apply arbitrary expressions to samples in frequency domain
...@@ -9842,43 +9910,9 @@ fftfilt=dc_Y=0:weight_Y='1+squish(1-(Y+X)/100)' ...@@ -9842,43 +9910,9 @@ fftfilt=dc_Y=0:weight_Y='1+squish(1-(Y+X)/100)'
Blur: Blur:
@example @example
fftfilt=dc_Y=0:weight_Y='exp(-4 * ((Y+X)/(W+H)))' fftfilt=dc_Y=0:weight_Y='exp(-4 * ((Y+X)/(W+H)))'
@end example @end example
@end itemize
@section fftdnoiz
Denoise frames using 3D FFT (frequency domain filtering).
The filter accepts the following options:
@table @option
@item sigma
Set the noise sigma constant. This sets denoising strength.
Default value is 1. Allowed range is from 0 to 30.
Using very high sigma with low overlap may give blocking artifacts.
@item amount
Set amount of denoising. By default all detected noise is reduced.
Default value is 1. Allowed range is from 0 to 1.
@item block
Set size of block, Default is 4, can be 3, 4, 5 or 6.
Actual size of block in pixels is 2 to power of @var{block}, so by default
block size in pixels is 2^4 which is 16.
@item overlap
Set block overlap. Default is 0.5. Allowed range is from 0.2 to 0.8.
@item prev
Set number of previous frames to use for denoising. By default is set to 0.
@item next
Set number of next frames to to use for denoising. By default is set to 0.
@item planes @end itemize
Set planes which will be filtered, by default are all available filtered
except alpha.
@end table
@section field @section field
...@@ -10378,40 +10412,6 @@ ffmpeg -i file.ts -vf find_rect=newref.pgm,cover_rect=cover.jpg:mode=cover new.m ...@@ -10378,40 +10412,6 @@ ffmpeg -i file.ts -vf find_rect=newref.pgm,cover_rect=cover.jpg:mode=cover new.m
@end example @end example
@end itemize @end itemize
@section cover_rect
Cover a rectangular object
It accepts the following options:
@table @option
@item cover
Filepath of the optional cover image, needs to be in yuv420.
@item mode
Set covering mode.
It accepts the following values:
@table @samp
@item cover
cover it by the supplied image
@item blur
cover it by interpolating the surrounding pixels
@end table
Default value is @var{blur}.
@end table
@subsection Examples
@itemize
@item
Cover a rectangular object by the supplied image of a given video using @command{ffmpeg}:
@example
ffmpeg -i file.ts -vf find_rect=newref.pgm,cover_rect=cover.jpg:mode=cover new.mkv
@end example
@end itemize
@section floodfill @section floodfill
Flood area with values of same pixel components with another values. Flood area with values of same pixel components with another values.
...@@ -16449,6 +16449,114 @@ in [-30,0] will filter edges. Default value is @option{luma_threshold}. ...@@ -16449,6 +16449,114 @@ in [-30,0] will filter edges. Default value is @option{luma_threshold}.
If a chroma option is not explicitly set, the corresponding luma value If a chroma option is not explicitly set, the corresponding luma value
is set. is set.
@section sobel
Apply sobel operator to input video stream.
The filter accepts the following option:
@table @option
@item planes
Set which planes will be processed, unprocessed planes will be copied.
By default value 0xf, all planes will be processed.
@item scale
Set value which will be multiplied with filtered result.
@item delta
Set value which will be added to filtered result.
@end table
@anchor{spp}
@section spp
Apply a simple postprocessing filter that compresses and decompresses the image
at several (or - in the case of @option{quality} level @code{6} - all) shifts
and average the results.
The filter accepts the following options:
@table @option
@item quality
Set quality. This option defines the number of levels for averaging. It accepts
an integer in the range 0-6. If set to @code{0}, the filter will have no
effect. A value of @code{6} means the higher quality. For each increment of
that value the speed drops by a factor of approximately 2. Default value is
@code{3}.
@item qp
Force a constant quantization parameter. If not set, the filter will use the QP
from the video stream (if available).
@item mode
Set thresholding mode. Available modes are:
@table @samp
@item hard
Set hard thresholding (default).
@item soft
Set soft thresholding (better de-ringing effect, but likely blurrier).
@end table
@item use_bframe_qp
Enable the use of the QP from the B-Frames if set to @code{1}. Using this
option may cause flicker since the B-Frames have often larger QP. Default is
@code{0} (not enabled).
@end table
@section sr
Scale the input by applying one of the super-resolution methods based on
convolutional neural networks. Supported models:
@itemize
@item
Super-Resolution Convolutional Neural Network model (SRCNN).
See @url{https://arxiv.org/abs/1501.00092}.
@item
Efficient Sub-Pixel Convolutional Neural Network model (ESPCN).
See @url{https://arxiv.org/abs/1609.05158}.
@end itemize
Training scripts as well as scripts for model file (.pb) saving can be found at
@url{https://github.com/XueweiMeng/sr/tree/sr_dnn_native}. Original repository
is at @url{https://github.com/HighVoltageRocknRoll/sr.git}.
Native model files (.model) can be generated from TensorFlow model
files (.pb) by using tools/python/convert.py
The filter accepts the following options:
@table @option
@item dnn_backend
Specify which DNN backend to use for model loading and execution. This option accepts
the following values:
@table @samp
@item native
Native implementation of DNN loading and execution.
@item tensorflow
TensorFlow backend. To enable this backend you
need to install the TensorFlow for C library (see
@url{https://www.tensorflow.org/install/install_c}) and configure FFmpeg with
@code{--enable-libtensorflow}
@end table
Default value is @samp{native}.
@item model
Set path to model file specifying network architecture and its parameters.
Note that different backends use different file formats. TensorFlow backend
can load files for both formats, while native backend can load files for only
its format.
@item scale_factor
Set scale factor for SRCNN model. Allowed values are @code{2}, @code{3} and @code{4}.
Default value is @code{2}. Scale factor is necessary for SRCNN model, because it accepts
input upscaled using bicubic upscaling with proper scale factor.
@end table
@section ssim @section ssim
Obtain the SSIM (Structural SImilarity Metric) between two input videos. Obtain the SSIM (Structural SImilarity Metric) between two input videos.
...@@ -16751,114 +16859,6 @@ asendcmd='5.0 astreamselect map 1',astreamselect=inputs=2:map=0 ...@@ -16751,114 +16859,6 @@ asendcmd='5.0 astreamselect map 1',astreamselect=inputs=2:map=0
@end example @end example
@end itemize @end itemize
@section sobel
Apply sobel operator to input video stream.
The filter accepts the following option:
@table @option
@item planes
Set which planes will be processed, unprocessed planes will be copied.
By default value 0xf, all planes will be processed.
@item scale
Set value which will be multiplied with filtered result.
@item delta
Set value which will be added to filtered result.
@end table
@anchor{spp}
@section spp
Apply a simple postprocessing filter that compresses and decompresses the image
at several (or - in the case of @option{quality} level @code{6} - all) shifts
and average the results.
The filter accepts the following options:
@table @option
@item quality
Set quality. This option defines the number of levels for averaging. It accepts
an integer in the range 0-6. If set to @code{0}, the filter will have no
effect. A value of @code{6} means the higher quality. For each increment of
that value the speed drops by a factor of approximately 2. Default value is
@code{3}.
@item qp
Force a constant quantization parameter. If not set, the filter will use the QP
from the video stream (if available).
@item mode
Set thresholding mode. Available modes are:
@table @samp
@item hard
Set hard thresholding (default).
@item soft
Set soft thresholding (better de-ringing effect, but likely blurrier).
@end table
@item use_bframe_qp
Enable the use of the QP from the B-Frames if set to @code{1}. Using this
option may cause flicker since the B-Frames have often larger QP. Default is
@code{0} (not enabled).
@end table
@section sr
Scale the input by applying one of the super-resolution methods based on
convolutional neural networks. Supported models:
@itemize
@item
Super-Resolution Convolutional Neural Network model (SRCNN).
See @url{https://arxiv.org/abs/1501.00092}.
@item
Efficient Sub-Pixel Convolutional Neural Network model (ESPCN).
See @url{https://arxiv.org/abs/1609.05158}.
@end itemize
Training scripts as well as scripts for model file (.pb) saving can be found at
@url{https://github.com/XueweiMeng/sr/tree/sr_dnn_native}. Original repository
is at @url{https://github.com/HighVoltageRocknRoll/sr.git}.
Native model files (.model) can be generated from TensorFlow model
files (.pb) by using tools/python/convert.py
The filter accepts the following options:
@table @option
@item dnn_backend
Specify which DNN backend to use for model loading and execution. This option accepts
the following values:
@table @samp
@item native
Native implementation of DNN loading and execution.
@item tensorflow
TensorFlow backend. To enable this backend you
need to install the TensorFlow for C library (see
@url{https://www.tensorflow.org/install/install_c}) and configure FFmpeg with
@code{--enable-libtensorflow}
@end table
Default value is @samp{native}.
@item model
Set path to model file specifying network architecture and its parameters.
Note that different backends use different file formats. TensorFlow backend
can load files for both formats, while native backend can load files for only
its format.
@item scale_factor
Set scale factor for SRCNN model. Allowed values are @code{2}, @code{3} and @code{4}.
Default value is @code{2}. Scale factor is necessary for SRCNN model, because it accepts
input upscaled using bicubic upscaling with proper scale factor.
@end table
@anchor{subtitles} @anchor{subtitles}
@section subtitles @section subtitles
......
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