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@ -8490,6 +8490,115 @@ Negate input video. |
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It accepts an integer in input; if non-zero it negates the |
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alpha component (if available). The default value in input is 0. |
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@section nnedi |
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Deinterlace video using neural network edge directed interpolation. |
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This filter accepts the following options: |
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@table @option |
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@item weights |
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Mandatory option, without binary file filter can not work. |
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Currently file can be found here: |
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https://github.com/dubhater/vapoursynth-nnedi3/blob/master/src/nnedi3_weights.bin |
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@item deint |
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Set which frames to deinterlace, by default it is @code{all}. |
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Can be @code{all} or @code{interlaced}. |
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@item field |
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Set mode of operation. |
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Can be one of the following: |
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@table @samp |
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@item af |
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Use frame flags, both fields. |
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@item a |
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Use frame flags, single field. |
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@item t |
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Use top field only. |
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@item b |
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Use bottom field only. |
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@item ft |
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Use both fields, top first. |
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@item fb |
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Use both fields, bottom first. |
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@end table |
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@item planes |
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Set which planes to process, by default filter process all frames. |
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@item nsize |
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Set size of local neighborhood around each pixel, used by the predictor neural |
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network. |
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Can be one of the following: |
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@table @samp |
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@item s8x6 |
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@item s16x6 |
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@item s32x6 |
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@item s48x6 |
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@item s8x4 |
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@item s16x4 |
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@item s32x4 |
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@end table |
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@item nns |
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Set the number of neurons in predicctor neural network. |
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Can be one of the following: |
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@table @samp |
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@item n16 |
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@item n32 |
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@item n64 |
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@item n128 |
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@item n256 |
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@end table |
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@item qual |
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Controls the number of different neural network predictions that are blended |
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together to compute the final output value. Can be @code{fast}, default or |
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@code{slow}. |
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@item etype |
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Set which set of weights to use in the predictor. |
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Can be one of the following: |
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@table @samp |
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@item a |
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weights trained to minimize absolute error |
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@item s |
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weights trained to minimize squared error |
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@end table |
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@item pscrn |
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Controls whether or not the prescreener neural network is used to decide |
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which pixels should be processed by the predictor neural network and which |
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can be handled by simple cubic interpolation. |
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The prescreener is trained to know whether cubic interpolation will be |
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sufficient for a pixel or whether it should be predicted by the predictor nn. |
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The computational complexity of the prescreener nn is much less than that of |
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the predictor nn. Since most pixels can be handled by cubic interpolation, |
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using the prescreener generally results in much faster processing. |
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The prescreener is pretty accurate, so the difference between using it and not |
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using it is almost always unnoticeable. |
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Can be one of the following: |
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@table @samp |
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@item none |
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@item original |
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@item new |
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@end table |
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Default is @code{new}. |
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@item fapprox |
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Set various debugging flags. |
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@end table |
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@section noformat |
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Force libavfilter not to use any of the specified pixel formats for the |
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