small polish
convasep offset now working, matches convsep very closely
This commit is contained in:
John Cupitt
parent
2e8f14c6a5
commit
8a9ee7e4ce
11
TODO
11
TODO
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@ -1,11 +1,18 @@
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- convasep does not handle offset correctly
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- tests for convasep ... just check it matches convsep +/- some small amount
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- try this blur.mat
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6 1 3896
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20 22 24 27 30 32
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ie. missing offset, though scale is there ... is not recognised
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- test new clip stuff?
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- worley could output float distance by default?
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- add more webp tests to py suite
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@ -175,9 +175,9 @@ vips_conv_init( VipsConv *conv )
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*
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* Optional arguments:
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*
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* * @precision: calculation accuracy
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* * @layers: number of layers for approximation
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* * @cluster: cluster lines closer than this distance
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* * @precision: #VipsPrecision, calculation accuracy
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* * @layers: %gint, number of layers for approximation
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* * @cluster: %gint, cluster lines closer than this distance
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*
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* Convolution.
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*
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@ -190,8 +190,10 @@ vips_conv_init( VipsConv *conv )
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*
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* where scale and offset are part of @mask.
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*
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* If @precision is #VIPS_PRECISION_INTEGER then the convolution is performed
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* with integer arithmetic and the output image
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* If @precision is #VIPS_PRECISION_INTEGER, then
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* elements of @mask are converted to
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* integers before convolution, using rint(),
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* and the output image
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* always has the same #VipsBandFormat as the input image.
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*
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* For #VIPS_FORMAT_UCHAR images, vips_conv() uses a fast vector path based on
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@ -204,7 +206,9 @@ vips_conv_init( VipsConv *conv )
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* is always #VIPS_FORMAT_FLOAT unless @in is #VIPS_FORMAT_DOUBLE, in which case
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* @out is also #VIPS_FORMAT_DOUBLE.
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*
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* If @precision is #VIPS_PRECISION_APPROXIMATE then the output image
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* If @precision is #VIPS_PRECISION_APPROXIMATE then, like
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* #VIPS_PRECISION_INTEGER, @mask is converted to int before convolution, and
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* the output image
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* always has the same #VipsBandFormat as the input image.
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*
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* Larger values for @layers give more accurate
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@ -216,6 +220,8 @@ vips_conv_init( VipsConv *conv )
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* Smaller values of @cluster will give more accurate results, but be slower
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* and use more memory. 10% of the mask radius is a good rule of thumb.
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*
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* See also: vips_convsep().
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*
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* Returns: 0 on success, -1 on error
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*/
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int
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@ -53,11 +53,6 @@
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TODO
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- are we handling mask offset correctly?
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nope! we have area and rounding, but neither properly incorporates
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offset
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- how about making a cumulative image and then subtracting points in
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that, rather than keeping a set of running totals
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@ -68,14 +63,10 @@
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*/
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/* Show sample pixels as they are transformed.
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#define DEBUG_PIXELS
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*/
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/*
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*/
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#define DEBUG
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#define VIPS_DEBUG
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*/
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#ifdef HAVE_CONFIG_H
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#include <config.h>
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@ -306,7 +297,7 @@ vips_convasep_decompose( VipsConvasep *convasep )
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for( z = 0; z < convasep->width; z++ )
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sum += coeff[z];
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convasep->area = rint( sum * convasep->area / scale );
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convasep->area = VIPS_RINT( sum * convasep->area / scale );
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convasep->rounding = (convasep->area + 1) / 2;
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convasep->offset = offset;
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@ -463,8 +454,11 @@ G_STMT_START { \
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isum[z] += p[x]; \
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sum += convasep->factor[z] * isum[z]; \
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} \
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sum = (sum + convasep->rounding) / convasep->area + \
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convasep->offset; \
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\
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/* Don't add offset ... we only want to do that once, do it on \
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* the vertical pass. \
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*/ \
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sum = (sum + convasep->rounding) / convasep->area; \
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CLIP( sum ); \
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*q = sum; \
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q += ostride; \
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@ -477,8 +471,7 @@ G_STMT_START { \
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sum += convasep->factor[z] * isum[z]; \
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} \
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p += istride; \
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sum = (sum + convasep->rounding) / convasep->area + \
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convasep->offset; \
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sum = (sum + convasep->rounding) / convasep->area; \
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CLIP( sum ); \
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*q = sum; \
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q += ostride; \
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@ -504,7 +497,11 @@ G_STMT_START { \
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dsum[z] += p[x]; \
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sum += convasep->factor[z] * dsum[z]; \
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} \
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sum = sum / convasep->area + convasep->offset; \
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\
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/* Don't add offset ... we only want to do that once, do it on \
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* the vertical pass. \
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*/ \
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sum = sum / convasep->area; \
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*q = sum; \
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q += ostride; \
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\
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@ -516,7 +513,7 @@ G_STMT_START { \
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sum += convasep->factor[z] * dsum[z]; \
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} \
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p += istride; \
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sum = sum / convasep->area + convasep->offset; \
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sum = sum / convasep->area; \
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*q = sum; \
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q += ostride; \
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} \
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@ -830,6 +827,7 @@ vips_convasep_pass( VipsConvasep *convasep,
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static int
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vips_convasep_build( VipsObject *object )
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{
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VipsObjectClass *class = VIPS_OBJECT_GET_CLASS( object );
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VipsConvolution *convolution = (VipsConvolution *) object;
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VipsConvasep *convasep = (VipsConvasep *) object;
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VipsImage **t = (VipsImage **) vips_object_local_array( object, 4 );
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@ -839,6 +837,9 @@ vips_convasep_build( VipsObject *object )
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if( VIPS_OBJECT_CLASS( vips_convasep_parent_class )->build( object ) )
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return( -1 );
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if( vips_check_separable( class->nickname, convolution->M ) )
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return( -1 );
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/* An int version of our mask.
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*/
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if( vips__image_intize( convolution->M, &t[3] ) )
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@ -915,12 +916,11 @@ vips_convasep_init( VipsConvasep *convasep )
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* Approximate separable convolution. This is a low-level operation, see
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* vips_convsep() for something more convenient.
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*
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* The mask must be 1xn or nx1 elements.
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* The output image
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* always has the same #VipsBandFormat as the input image.
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*
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* The image is convolved twice: once with @mask and then again with @mask
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* rotated by 90 degrees.
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* @mask must be 1xn or nx1 elements.
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* Elements of @mask are converted to
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* integers before convolution.
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*
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* Larger values for @layers give more accurate
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* results, but are slower. As @layers approaches the mask radius, the
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@ -928,7 +928,10 @@ vips_convasep_init( VipsConvasep *convasep )
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* match. For many large masks, such as Gaussian, @layers need be only 10% of
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* this value and accuracy will still be good.
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*
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* See also: vips_conv().
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* The output image
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* always has the same #VipsBandFormat as the input image.
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*
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* See also: vips_convsep().
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*
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* Returns: 0 on success, -1 on error
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*/
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@ -83,8 +83,14 @@ vips_convsep_build( VipsObject *object )
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in = t[0];
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}
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else {
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if( vips_rot( convolution->M, &t[0], VIPS_ANGLE_D90, NULL ) ||
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vips_conv( convolution->in, &t[1], convolution->M,
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if( vips_rot( convolution->M, &t[0], VIPS_ANGLE_D90, NULL ) )
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return( -1 );
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/* We must only add the offset once.
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*/
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vips_image_set_double( t[0], "offset", 0 );
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if( vips_conv( convolution->in, &t[1], convolution->M,
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"precision", convsep->precision,
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"layers", convsep->layers,
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"cluster", convsep->cluster,
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