Nnedi3ocl/nnedi3ocl

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== [[Script variables|Syntax and Parameters]] ==
 
== [[Script variables|Syntax and Parameters]] ==
 
:{{Template:FuncDef|nnedi3ocl (''clip'', ''int'' "field", ''bool'' "dh", ''bool'' "Y", ''bool'' "U", ''bool'' "V", ''int'' "nsize", ''int'' "nns", ''int'' "qual", ''int'' "etype", ''int'' "dw")}}
 
:{{Template:FuncDef|nnedi3ocl (''clip'', ''int'' "field", ''bool'' "dh", ''bool'' "Y", ''bool'' "U", ''bool'' "V", ''int'' "nsize", ''int'' "nns", ''int'' "qual", ''int'' "etype", ''int'' "dw")}}
 +
<br>
 +
::{{Par2| |clip| }}
 +
::<blockquote style="width: 27%;">Input clip must be [[planar]].</blockquote>
 
<br>
 
<br>
 
::{{Par2|field|int|-1}}
 
::{{Par2|field|int|-1}}
:::Controls the mode of operation (double vs same rate) and which field is kept.
+
::<blockquote style="width: 27%;">Controls the mode of operation (double vs same rate) and which field is kept. Possible settings:</blockquote>
:::Possible settings:<br>
+
  
 
::::*-2 = double rate (alternates each frame), uses avisynth's internal parity value to start
 
::::*-2 = double rate (alternates each frame), uses avisynth's internal parity value to start
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::::*3 = double rate (alternates each frame), starts with top
 
::::*3 = double rate (alternates each frame), starts with top
  
:::If {{Template:FuncDef|field}} is set to -1, then nnedi3ocl calls child->GetParity(0) during initialization.
+
::<blockquote style="width: 54.5%;">If {{Template:FuncDef|field}} is set to -1, then nnedi3ocl calls child->GetParity(0) during initialization. If it returns true, then {{Template:FuncDef|field}} is set to 1. If it returns false, then {{Template:FuncDef|field}} is set to 0. If {{Template:FuncDef|field}} is set to -2, then the same thing happens, but instead of setting {{Template:FuncDef|field}} to 1 or 0 it is set to 3 or 2.</blockquote>
:::If it returns true, then {{Template:FuncDef|field}} is set to 1. If it returns false, then {{Template:FuncDef|field}} is set to 0.
+
 
:::If {{Template:FuncDef|field}} is set to -2, then the same thing happens, but instead of setting {{Template:FuncDef|field}} to 1 or 0 it is set to 3 or 2.
+
::<blockquote style="width: 55%;">&bull; Default for {{Template:FuncDef|field}} is the value of {{Template:FuncDef|dw}}.</blockquote>
<br>
+
:::&bull; Default for {{Template:FuncDef|field}} is the value of {{Template:FuncDef|dw}}.
+
 
<br>
 
<br>
 
::{{Par2|dh|bool|false}}
 
::{{Par2|dh|bool|false}}
:::Doubles the height of the input. Each line of the input is copied to every other line
+
::<blockquote style="width: 55%;">Doubles the height of the input. Each line of the input is copied to every other line of the output and the missing lines are interpolated. If {{Template:FuncDef|field}}=0, the input is copied to the odd lines of the output. If {{Template:FuncDef|field}}=1, the input is copied to the even lines of the output.</blockquote>
:::of the output and the missing lines are interpolated. If {{Template:FuncDef|field}}=0, the input is copied
+
 
:::to the odd lines of the output. If {{Template:FuncDef|field}}=1, the input is copied to the even lines of
+
::<blockquote style="width: 21%;"> &bull; {{Template:FuncDef|field}} must be set to either -1, 0, or 1 when using {{Template:FuncDef|dh}}=true. &bull; Default for {{Template:FuncDef|dh}} is false when {{Template:FuncDef|dw}}=-1 and true otherwise.</blockquote>
:::the output. {{Template:FuncDef|field}} must be set to either -1, 0, or 1 when using {{Template:FuncDef|dh}}=true.
+
<br>
+
:::&bull; Default for {{Template:FuncDef|dh}} is false when {{Template:FuncDef|dw}}=-1 and true otherwise.
+
 
<br>
 
<br>
 
::{{Par2|Y|bool|true}}
 
::{{Par2|Y|bool|true}}
 
::{{Par2|U|bool|true}}
 
::{{Par2|U|bool|true}}
 
::{{Par2|V|bool|true}}
 
::{{Par2|V|bool|true}}
:::These control whether or not the specified plane is processed. Set to true to
+
::<blockquote style="width: 55%;">These control whether or not the specified plane is processed. Set to true to process or false to ignore. Ignored planes are not copied, zero'd, or even considered. So what the ignored planes happen to contain on output is unpredictable.</blockquote>
:::process or false to ignore. Ignored planes are not copied, zero'd, or even
+
:::considered. So what the ignored planes happen to contain on output is unpredictable.
+
 
<br>
 
<br>
 
::{{Par2|nsize|int|0}}
 
::{{Par2|nsize|int|0}}
:::Sets the size of the local neighborhood around each pixel that is used by the predictor neural network.
+
::<blockquote style="width: 55%;">Sets the size of the local neighborhood around each pixel that is used by the predictor neural network.</blockquote>
  
 
::::*0 -  8x6
 
::::*0 -  8x6
  
:::Only {{Template:FuncDef|nsize}} 0 is implemented, other values are simply ignored.  
+
::<blockquote style="width: 55%;">Only {{Template:FuncDef|nsize}} 0 is implemented, other values are simply ignored.</blockquote>
 
<br>
 
<br>
 
::{{Par2|nns|int|1}}
 
::{{Par2|nns|int|1}}
:::Sets the number of neurons in the predictor neural network. Possible settings are
+
::<blockquote style="width: 55%;">Sets the number of neurons in the predictor neural network. Possible settings are 0, 1, 2, 3, and 4. 0 is fastest. 4 is slowest, but should give the best quality. This is a quality vs speed option; however, differences are usually small. The difference in speed will become larger as '{{Template:FuncDef|qual}}' is increased.</blockquote>
:::0, 1, 2, 3, and 4. 0 is fastest. 4 is slowest, but should give the best quality. This
+
:::is a quality vs speed option; however, differences are usually small. The difference
+
:::in speed will become larger as '{{Template:FuncDef|qual}}' is increased.
+
  
 
::::*0 - 16
 
::::*0 - 16
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<br>
 
<br>
 
::{{Par2|qual|int|1}}
 
::{{Par2|qual|int|1}}
:::Controls the number of different neural network predictions that are blended together
+
::<blockquote style="width: 55%;">Controls the number of different neural network predictions that are blended together to compute the final output value. Each neural network was trained on a different set of training data. Blending the results of these different networks improves generalization to unseen data. Possible values are 1 or 2. Essentially this is a quality vs speed option. Larger values will result in more processing time, but should give better results. However, the difference is usually pretty small. I would recommend using {{Template:FuncDef|qual}}>1 for things like single image enlargement.</blockquote>
:::to compute the final output value. Each neural network was trained on a different set
+
:::of training data. Blending the results of these different networks improves generalization
+
:::to unseen data. Possible values are 1 or 2. Essentially this is a quality vs speed
+
:::option. Larger values will result in more processing time, but should give better results.
+
:::However, the difference is usually pretty small. I would recommend using {{Template:FuncDef|qual}}>1 for
+
:::things like single image enlargement.
+
 
<br>
 
<br>
 
::{{Par2|etype|int|0}}
 
::{{Par2|etype|int|0}}
:::Controls which set of weights to use in the predictor nn. Possible settings:
+
::<blockquote style="width: 20%;">Controls which set of weights to use in the predictor nn. Possible settings:</blockquote>
  
 
::::*0 - weights trained to minimize absolute error
 
::::*0 - weights trained to minimize absolute error
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<br>
 
<br>
 
::{{Par2|dw|int|-1}}
 
::{{Par2|dw|int|-1}}
:::Controls scaling in horizontal direction:  
+
::<blockquote style="width: 55%;">Controls scaling in horizontal direction:</blockquote>
  
 
::::*-1 - no scaling.
 
::::*-1 - no scaling.

Revision as of 04:30, 30 August 2014

Back to nnedi3ocl




Description

nnedi3ocl is an intra-field only deinterlacer. It takes in a frame, throws away one field, and then interpolates the missing pixels using
only information from the kept field. It has same rate and double rate modes, and works with Y8, YV12, YV16, and YV24 input.


Syntax and Parameters

nnedi3ocl (clip, int "field", bool "dh", bool "Y", bool "U", bool "V", int "nsize", int "nns", int "qual", int "etype", int "dw")


clip   =
Input clip must be planar.


int  field = -1
Controls the mode of operation (double vs same rate) and which field is kept. Possible settings:
  • -2 = double rate (alternates each frame), uses avisynth's internal parity value to start
  • -1 = same rate, uses avisynth's internal parity value
  • 0 = same rate, keep bottom field
  • 1 = same rate, keep top field
  • 2 = double rate (alternates each frame), starts with bottom
  • 3 = double rate (alternates each frame), starts with top
If field is set to -1, then nnedi3ocl calls child->GetParity(0) during initialization. If it returns true, then field is set to 1. If it returns false, then field is set to 0. If field is set to -2, then the same thing happens, but instead of setting field to 1 or 0 it is set to 3 or 2.
• Default for field is the value of dw.


bool  dh = false
Doubles the height of the input. Each line of the input is copied to every other line of the output and the missing lines are interpolated. If field=0, the input is copied to the odd lines of the output. If field=1, the input is copied to the even lines of the output.
field must be set to either -1, 0, or 1 when using dh=true. • Default for dh is false when dw=-1 and true otherwise.


bool  Y = true
bool  U = true
bool  V = true
These control whether or not the specified plane is processed. Set to true to process or false to ignore. Ignored planes are not copied, zero'd, or even considered. So what the ignored planes happen to contain on output is unpredictable.


int  nsize = 0
Sets the size of the local neighborhood around each pixel that is used by the predictor neural network.
  • 0 - 8x6
Only nsize 0 is implemented, other values are simply ignored.


int  nns = 1
Sets the number of neurons in the predictor neural network. Possible settings are 0, 1, 2, 3, and 4. 0 is fastest. 4 is slowest, but should give the best quality. This is a quality vs speed option; however, differences are usually small. The difference in speed will become larger as 'qual' is increased.
  • 0 - 16
  • 1 - 32
  • 2 - 64
  • 3 - 128
  • 4 - 256


int  qual = 1
Controls the number of different neural network predictions that are blended together to compute the final output value. Each neural network was trained on a different set of training data. Blending the results of these different networks improves generalization to unseen data. Possible values are 1 or 2. Essentially this is a quality vs speed option. Larger values will result in more processing time, but should give better results. However, the difference is usually pretty small. I would recommend using qual>1 for things like single image enlargement.


int  etype = 0
Controls which set of weights to use in the predictor nn. Possible settings:
  • 0 - weights trained to minimize absolute error
  • 1 - weights trained to minimize squared error


int  dw = -1
Controls scaling in horizontal direction:
  • -1 - no scaling.
  • 0 - scales like field 0 with dh=true, but horizontally.
  • 1 - scales like field 1 with dh=true, but horizontally.


Examples

nnedi3ocl with default settings:

AviSource("Blah.avi")
nnedi3ocl(field=-1, dh=false, Y=true, U=true, V=true, nsize=6, nns=1, qual=1, etype=0, dw=-1)




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