redo im_log_*mask() as classes
This commit is contained in:
John Cupitt
parent
aa107b1bf7
commit
7ef4573f18
@ -1,5 +1,5 @@
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19/10/13 started 7.37.0
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- redone im_rotate_*mask45(), im_gauss_*mask*() as classes
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- redone im_rotate_*mask45(), im_gauss_*mask*(), im_log_*mask*() as classes
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18/10/13 started 7.36.3
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- fix compiler warnings in ubuntu 13.10
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@ -3,7 +3,8 @@ noinst_LTLIBRARIES = libcreate.la
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libcreate_la_SOURCES = \
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create.c \
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pcreate.h \
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gauss.c \
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gaussmat.c \
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logmat.c \
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buildlut.c \
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invertlut.c \
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tonelut.c \
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@ -111,7 +111,8 @@ void
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vips_create_operation_init( void )
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{
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extern GType vips_black_get_type( void );
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extern GType vips_gauss_get_type( void );
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extern GType vips_gaussmat_get_type( void );
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extern GType vips_logmat_get_type( void );
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extern GType vips_gaussnoise_get_type( void );
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#ifdef HAVE_PANGOFT2
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extern GType vips_text_get_type( void );
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@ -127,7 +128,8 @@ vips_create_operation_init( void )
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extern GType vips_identity_get_type( void );
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vips_black_get_type();
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vips_gauss_get_type();
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vips_gaussmat_get_type();
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vips_logmat_get_type();
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vips_gaussnoise_get_type();
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#ifdef HAVE_PANGOFT2
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vips_text_get_type();
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@ -13,7 +13,7 @@
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* - set scale in _sep variant, why not
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* 21/10/10
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* - gtkdoc
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* 20/10/10
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* 20/10/13
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* - redone as a class
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*/
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@ -62,7 +62,7 @@
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#include "pcreate.h"
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typedef struct _VipsGauss {
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typedef struct _VipsGaussmat {
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VipsCreate parent_instance;
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double sigma;
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@ -71,40 +71,38 @@ typedef struct _VipsGauss {
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gboolean separable;
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gboolean integer;
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} VipsGauss;
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} VipsGaussmat;
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typedef struct _VipsGaussClass {
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typedef struct _VipsGaussmatClass {
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VipsCreateClass parent_class;
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} VipsGaussClass;
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} VipsGaussmatClass;
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G_DEFINE_TYPE( VipsGauss, vips_gauss, VIPS_TYPE_CREATE );
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G_DEFINE_TYPE( VipsGaussmat, vips_gaussmat, VIPS_TYPE_CREATE );
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static int
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vips_gauss_build( VipsObject *object )
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vips_gaussmat_build( VipsObject *object )
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{
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VipsObjectClass *class = VIPS_OBJECT_GET_CLASS( object );
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VipsCreate *create = VIPS_CREATE( object );
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VipsGauss *gauss = (VipsGauss *) object;
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VipsGaussmat *gaussmat = (VipsGaussmat *) object;
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double sig2 = 2. * gaussmat->sigma * gaussmat->sigma;
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int max_x = 8 * gaussmat->sigma > 5000 ? 5000 : 8 * gaussmat->sigma ;
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int x, y;
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int max_x;
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int width, height;
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double sig2; /* sig2 = 2. * sigma * sigma */
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double sum;
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if( VIPS_OBJECT_CLASS( vips_gauss_parent_class )->build( object ) )
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if( VIPS_OBJECT_CLASS( vips_gaussmat_parent_class )->build( object ) )
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return( -1 );
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/* Find the size of the mask. Limit the mask size to 10k x 10k for
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* sanity.
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*/
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sig2 = 2. * gauss->sigma * gauss->sigma;
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max_x = 8 * gauss->sigma > 5000 ? 5000 : 8 * gauss->sigma ;
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for( x = 0; x < max_x; x++ ) {
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double v = exp( - ((double)(x * x)) / sig2 );
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if( v < gauss->min_ampl )
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if( v < gaussmat->min_ampl )
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break;
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}
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if( x == max_x ) {
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@ -112,7 +110,7 @@ vips_gauss_build( VipsObject *object )
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return( -1 );
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}
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width = x * 2 + 1;
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height = gauss->separable ? 1 : width;
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height = gaussmat->separable ? 1 : width;
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vips_image_init_fields( create->out,
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width, height, 1,
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@ -131,7 +129,7 @@ vips_gauss_build( VipsObject *object )
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double distance = xo * xo + yo * yo;
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double v = exp( -distance / sig2 );
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if( gauss->integer )
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if( gaussmat->integer )
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v = VIPS_RINT( 20 * v );
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*VIPS_MATRIX( create->out, x, y ) = v;
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@ -146,7 +144,7 @@ vips_gauss_build( VipsObject *object )
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}
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static void
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vips_gauss_class_init( VipsGaussClass *class )
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vips_gaussmat_class_init( VipsGaussmatClass *class )
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{
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GObjectClass *gobject_class = G_OBJECT_CLASS( class );
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VipsObjectClass *vobject_class = VIPS_OBJECT_CLASS( class );
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@ -154,49 +152,49 @@ vips_gauss_class_init( VipsGaussClass *class )
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gobject_class->set_property = vips_object_set_property;
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gobject_class->get_property = vips_object_get_property;
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vobject_class->nickname = "gauss";
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vobject_class->nickname = "gaussmat";
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vobject_class->description = _( "make a gaussian image" );
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vobject_class->build = vips_gauss_build;
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vobject_class->build = vips_gaussmat_build;
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VIPS_ARG_DOUBLE( class, "sigma", 2,
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_( "Radius" ),
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_( "Radius of Gaussian" ),
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VIPS_ARGUMENT_REQUIRED_INPUT,
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G_STRUCT_OFFSET( VipsGauss, sigma ),
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G_STRUCT_OFFSET( VipsGaussmat, sigma ),
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0.000001, 10000.0, 1.0 );
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VIPS_ARG_DOUBLE( class, "min_ampl", 3,
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_( "Width" ),
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_( "Minimum amplitude of Gaussian" ),
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VIPS_ARGUMENT_REQUIRED_INPUT,
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G_STRUCT_OFFSET( VipsGauss, min_ampl ),
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G_STRUCT_OFFSET( VipsGaussmat, min_ampl ),
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0.000001, 10000.0, 0.1 );
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VIPS_ARG_BOOL( class, "separable", 4,
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_( "Separable" ),
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_( "Generate separable Gaussian" ),
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VIPS_ARGUMENT_OPTIONAL_INPUT,
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G_STRUCT_OFFSET( VipsGauss, separable ),
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G_STRUCT_OFFSET( VipsGaussmat, separable ),
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FALSE );
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VIPS_ARG_BOOL( class, "integer", 5,
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_( "Integer" ),
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_( "Generate integer Gaussian" ),
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VIPS_ARGUMENT_OPTIONAL_INPUT,
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G_STRUCT_OFFSET( VipsGauss, integer ),
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G_STRUCT_OFFSET( VipsGaussmat, integer ),
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FALSE );
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}
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static void
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vips_gauss_init( VipsGauss *gauss )
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vips_gaussmat_init( VipsGaussmat *gaussmat )
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{
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gauss->sigma = 1;
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gauss->min_ampl = 0.1;
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gaussmat->sigma = 1;
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gaussmat->min_ampl = 0.1;
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}
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/**
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* vips_gauss:
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* vips_gaussmat:
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* @sigma: standard deviation of mask
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* @min_ampl: minimum amplitude
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* @...: %NULL-terminated list of optional named arguments
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@ -231,13 +229,13 @@ vips_gauss_init( VipsGauss *gauss )
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* Returns: 0 on success, -1 on error
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*/
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int
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vips_gauss( VipsImage **out, double sigma, double min_ampl, ... )
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vips_gaussmat( VipsImage **out, double sigma, double min_ampl, ... )
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{
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va_list ap;
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int result;
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va_start( ap, min_ampl );
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result = vips_call_split( "gauss", ap, out, sigma, min_ampl );
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result = vips_call_split( "gaussmat", ap, out, sigma, min_ampl );
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va_end( ap );
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return( result );
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273
libvips/create/logmat.c
Normal file
273
libvips/create/logmat.c
Normal file
@ -0,0 +1,273 @@
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/* laplacian of logmatian
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*
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* Written on: 30/11/1989
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* Updated on: 6/12/1991
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* 7/8/96 JC
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* - ansified, mem leaks plugged
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* 20/11/98 JC
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* - mask too large check added
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* 26/3/02 JC
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* - ahem, was broken since '96, thanks matt
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* 16/7/03 JC
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* - makes mask out to zero, not out to minimum, thanks again matt
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* 22/10/10
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* - gtkdoc
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* 20/10/13
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* - redone as a class from logmat.c
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*/
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/*
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This file is part of VIPS.
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VIPS is free software; you can redistribute it and/or modify
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it under the terms of the GNU Lesser General Public License as published by
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the Free Software Foundation; either version 2 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
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02110-1301 USA
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*/
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/*
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These files are distributed with VIPS - http://www.vips.ecs.soton.ac.uk
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*/
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/*
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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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#endif /*HAVE_CONFIG_H*/
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#include <vips/intl.h>
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#include <stdio.h>
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#include <string.h>
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#include <stdlib.h>
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#include <math.h>
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#include <vips/vips.h>
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#include "pcreate.h"
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typedef struct _VipsLogmat {
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VipsCreate parent_instance;
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double sigma;
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double min_ampl;
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gboolean separable;
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gboolean integer;
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} VipsLogmat;
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typedef struct _VipsLogmatClass {
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VipsCreateClass parent_class;
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} VipsLogmatClass;
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G_DEFINE_TYPE( VipsLogmat, vips_logmat, VIPS_TYPE_CREATE );
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static int
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vips_logmat_build( VipsObject *object )
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{
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VipsObjectClass *class = VIPS_OBJECT_GET_CLASS( object );
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VipsCreate *create = VIPS_CREATE( object );
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VipsLogmat *logmat = (VipsLogmat *) object;
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double sig2 = logmat->sigma * logmat->sigma;
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double last;
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int x, y;
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int width, height;
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double sum;
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if( VIPS_OBJECT_CLASS( vips_logmat_parent_class )->build( object ) )
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return( -1 );
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/* Find the size of the mask. We want to eval the mask out to the
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* flat zero part, ie. beyond the minimum and to the point where it
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* comes back up towards zero.
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*/
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last = 0.0;
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for( x = 0; x < 5000; x++ ) {
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const double distance = x * x;
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double val;
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/* Handbook of Pattern Recognition and image processing
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* by Young and Fu AP 1986 pp 220-221
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* temp = (1.0 / (2.0 * IM_PI * sig4)) *
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(2.0 - (distance / sig2)) *
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exp( (-1.0) * distance / (2.0 * sig2) )
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.. use 0.5 to normalise
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*/
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val = 0.5 *
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(2.0 - (distance / sig2)) *
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exp( -distance / (2.0 * sig2) );
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/* Stop when change in value (ie. difference from the last
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* point) is positive (ie. we are going up) and absolute value
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* is less than the min.
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*/
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if( val - last >= 0 &&
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fabs( val ) < logmat->min_ampl )
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break;
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last = val;
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}
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if( x == 5000 ) {
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vips_error( class->nickname, "%s", _( "mask too large" ) );
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return( -1 );
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}
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width = x * 2 + 1;
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height = logmat->separable ? 1 : width;
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vips_image_init_fields( create->out,
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width, height, 1,
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VIPS_FORMAT_DOUBLE, VIPS_CODING_NONE, VIPS_INTERPRETATION_B_W,
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1.0, 1.0 );
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vips_demand_hint( create->out,
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VIPS_DEMAND_STYLE_ANY, NULL );
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if( vips_image_write_prepare( create->out ) )
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return( -1 );
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sum = 0.0;
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for( y = 0; y < height; y++ ) {
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for( x = 0; x < width; x++ ) {
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int xo = x - width / 2;
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int yo = y - height / 2;
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double distance = xo * xo + yo * yo;
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double v = 0.5 *
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(2.0 - (distance / sig2)) *
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exp( -distance / (2.0 * sig2) );
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if( logmat->integer )
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v = VIPS_RINT( 20 * v );
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*VIPS_MATRIX( create->out, x, y ) = v;
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sum += v;
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}
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}
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vips_image_set_double( create->out, "scale", sum );
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vips_image_set_double( create->out, "offset", 0.0 );
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return( 0 );
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}
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static void
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vips_logmat_class_init( VipsLogmatClass *class )
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{
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GObjectClass *gobject_class = G_OBJECT_CLASS( class );
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VipsObjectClass *vobject_class = VIPS_OBJECT_CLASS( class );
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gobject_class->set_property = vips_object_set_property;
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gobject_class->get_property = vips_object_get_property;
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vobject_class->nickname = "logmat";
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vobject_class->description = _( "make a laplacian of gaussian image" );
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vobject_class->build = vips_logmat_build;
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VIPS_ARG_DOUBLE( class, "sigma", 2,
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_( "Radius" ),
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_( "Radius of Logmatian" ),
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VIPS_ARGUMENT_REQUIRED_INPUT,
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G_STRUCT_OFFSET( VipsLogmat, sigma ),
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0.000001, 10000.0, 1.0 );
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VIPS_ARG_DOUBLE( class, "min_ampl", 3,
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_( "Width" ),
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_( "Minimum amplitude of Logmatian" ),
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VIPS_ARGUMENT_REQUIRED_INPUT,
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G_STRUCT_OFFSET( VipsLogmat, min_ampl ),
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0.000001, 10000.0, 0.1 );
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VIPS_ARG_BOOL( class, "separable", 4,
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_( "Separable" ),
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_( "Generate separable Logmatian" ),
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VIPS_ARGUMENT_OPTIONAL_INPUT,
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G_STRUCT_OFFSET( VipsLogmat, separable ),
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FALSE );
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VIPS_ARG_BOOL( class, "integer", 5,
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_( "Integer" ),
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_( "Generate integer Logmatian" ),
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VIPS_ARGUMENT_OPTIONAL_INPUT,
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G_STRUCT_OFFSET( VipsLogmat, integer ),
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FALSE );
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}
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static void
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vips_logmat_init( VipsLogmat *logmat )
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{
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logmat->sigma = 1;
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logmat->min_ampl = 0.1;
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}
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/**
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* vips_logmat:
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* @sigma: standard deviation of mask
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* @min_ampl: minimum amplitude
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* @...: %NULL-terminated list of optional named arguments
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*
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* Optional arguments:
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*
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* @separable: generate a separable logmatian
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* @integer: generate an integer logmatian
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*
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* Creates a circularly symmetric Laplacian of Gaussian mask
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* of radius
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* @sigma. The size of the mask is determined by the variable @min_ampl;
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* if for instance the value .1 is entered this means that the produced mask
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* is clipped at values within 10 persent of zero, and where the change
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* between mask elements is less than 10%.
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*
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* The program uses the following equation: (from Handbook of Pattern
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* Recognition and image processing by Young and Fu, AP 1986 pages 220-221):
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*
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* H(r) = (1 / (2 * M_PI * s4)) *
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* (2 - (r2 / s2)) *
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* exp(-r2 / (2 * s2))
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*
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* where s2 = @sigma * @sigma, s4 = s2 * s2, r2 = r * r.
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*
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* The generated mask has odd size and its maximum value is normalised to
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* 1.0, unless @integer is set.
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*
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* If @separable is set, only the centre horizontal is generated. This is
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* useful for separable convolutions.
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*
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* If @integer is set, an integer logmatian is generated. This is useful for
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* integer convolutions.
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*
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* "scale" is set to the sum of all the mask elements.
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*
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* See also: vips_gauss(), vips_conv().
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*
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* Returns: 0 on success, -1 on error
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*/
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int
|
||||
vips_logmat( VipsImage **out, double sigma, double min_ampl, ... )
|
||||
{
|
||||
va_list ap;
|
||||
int result;
|
||||
|
||||
va_start( ap, min_ampl );
|
||||
result = vips_call_split( "logmat", ap, out, sigma, min_ampl );
|
||||
va_end( ap );
|
||||
|
||||
return( result );
|
||||
}
|
||||
@ -45,7 +45,6 @@ libdeprecated_la_SOURCES = \
|
||||
im_mask2vips.c \
|
||||
im_vips2mask.c \
|
||||
rotmask.c \
|
||||
im_logmasks.c \
|
||||
rw_mask.c \
|
||||
im_matcat.c \
|
||||
im_matinv.c \
|
||||
|
||||
@ -1,238 +0,0 @@
|
||||
/* laplacian of gaussian
|
||||
*
|
||||
* Written on: 30/11/1989
|
||||
* Updated on: 6/12/1991
|
||||
* 7/8/96 JC
|
||||
* - ansified, mem leaks plugged
|
||||
* 20/11/98 JC
|
||||
* - mask too large check added
|
||||
* 26/3/02 JC
|
||||
* - ahem, was broken since '96, thanks matt
|
||||
* 16/7/03 JC
|
||||
* - makes mask out to zero, not out to minimum, thanks again matt
|
||||
* 22/10/10
|
||||
* - gtkdoc
|
||||
*/
|
||||
|
||||
/*
|
||||
|
||||
This file is part of VIPS.
|
||||
|
||||
VIPS is free software; you can redistribute it and/or modify
|
||||
it under the terms of the GNU Lesser General Public License as published by
|
||||
the Free Software Foundation; either version 2 of the License, or
|
||||
(at your option) any later version.
|
||||
|
||||
This program is distributed in the hope that it will be useful,
|
||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
||||
GNU Lesser General Public License for more details.
|
||||
|
||||
You should have received a copy of the GNU Lesser General Public License
|
||||
along with this program; if not, write to the Free Software
|
||||
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
|
||||
02110-1301 USA
|
||||
|
||||
*/
|
||||
|
||||
/*
|
||||
|
||||
These files are distributed with VIPS - http://www.vips.ecs.soton.ac.uk
|
||||
|
||||
*/
|
||||
|
||||
/*
|
||||
#define PIM_RINT 1
|
||||
*/
|
||||
|
||||
#ifdef HAVE_CONFIG_H
|
||||
#include <config.h>
|
||||
#endif /*HAVE_CONFIG_H*/
|
||||
#include <vips/intl.h>
|
||||
|
||||
#include <stdio.h>
|
||||
#include <math.h>
|
||||
|
||||
#include <vips/vips.h>
|
||||
#include <vips/util.h>
|
||||
|
||||
#define IM_MAXMASK 256
|
||||
|
||||
/**
|
||||
* im_log_dmask:
|
||||
* @filename: the returned mask has this set as the filename
|
||||
* @sigma: standard deviation of mask
|
||||
* @min_ampl: minimum amplitude
|
||||
*
|
||||
* im_log_dmask() creates a circularly symmetric Laplacian of Gaussian mask
|
||||
* of radius
|
||||
* @sigma. The size of the mask is determined by the variable @min_ampl;
|
||||
* if for instance the value .1 is entered this means that the produced mask
|
||||
* is clipped at values within 10 persent of zero, and where the change
|
||||
* between mask elements is less than 10%.
|
||||
*
|
||||
* The program uses the following equation: (from Handbook of Pattern
|
||||
* Recognition and image processing by Young and Fu, AP 1986 pages 220-221):
|
||||
*
|
||||
* H(r) = (1 / (2 * M_PI * s4)) *
|
||||
* (2 - (r2 / s2)) *
|
||||
* exp(-r2 / (2 * s2))
|
||||
*
|
||||
* where s2 = sigma * sigma, s4 = s2 * s2, r2 = r * r.
|
||||
*
|
||||
* The generated mask has odd size and its maximum value is normalised to 1.0.
|
||||
*
|
||||
* See also: im_log_imask(), im_gauss_dmask(), im_conv().
|
||||
*
|
||||
* Returns: the calculated mask on success, or NULL on error.
|
||||
*/
|
||||
DOUBLEMASK *
|
||||
im_log_dmask( const char *filename, double sigma, double min_ampl )
|
||||
{
|
||||
const double sig2 = sigma * sigma;
|
||||
|
||||
double last;
|
||||
int x, y, k;
|
||||
|
||||
double *pt1, *pt2, *pt3, *pt4;
|
||||
int xm, ym;
|
||||
int xm2, ym2; /* xm2 = xm/2 */
|
||||
int offset;
|
||||
double *cf, *cfs, *mc;
|
||||
DOUBLEMASK *m;
|
||||
double sum;
|
||||
|
||||
/* Find the size of the mask depending on the entered data. We want to
|
||||
* eval the mask out to the flat zero part, ie. beyond the minimum and
|
||||
* to the point where it comes back up towards zero.
|
||||
*/
|
||||
last = 0.0;
|
||||
for( x = 0; x < IM_MAXMASK; x++ ) {
|
||||
const double distance = x * x;
|
||||
double val;
|
||||
|
||||
/* Handbook of Pattern Recognition and image processing
|
||||
* by Young and Fu AP 1986 pp 220-221
|
||||
* temp = (1.0 / (2.0 * IM_PI * sig4)) *
|
||||
(2.0 - (distance / sig2)) *
|
||||
exp( (-1.0) * distance / (2.0 * sig2) )
|
||||
|
||||
.. use 0.5 to normalise
|
||||
*/
|
||||
val = 0.5 *
|
||||
(2.0 - (distance / sig2)) *
|
||||
exp( -distance / (2.0 * sig2) );
|
||||
|
||||
/* Stop when change in value (ie. difference from the last
|
||||
* point) is positive (ie. we are going up) and absolute value
|
||||
* is less than the min.
|
||||
*/
|
||||
if( val - last >= 0 &&
|
||||
fabs( val ) < min_ampl )
|
||||
break;
|
||||
|
||||
last = val;
|
||||
}
|
||||
if( x == IM_MAXMASK ) {
|
||||
im_error( "im_log_dmask", "%s", _( "mask too large" ) );
|
||||
return( NULL );
|
||||
}
|
||||
|
||||
xm2 = x;
|
||||
ym2 = x;
|
||||
xm = xm2 * 2 + 1;
|
||||
ym = ym2 * 2 + 1;
|
||||
|
||||
if( !(cfs = IM_ARRAY( NULL, (xm2 + 1) * (ym2 + 1), double )) )
|
||||
return( NULL );
|
||||
|
||||
/* Make 1/4 of the mask.
|
||||
*/
|
||||
for( k = 0, y = 0; y <= ym2; y++ )
|
||||
for( x = 0; x <= xm2; x++, k++ ) {
|
||||
const double distance = x * x + y * y;
|
||||
|
||||
cfs[k] = 0.5 *
|
||||
(2.0 - (distance / sig2)) *
|
||||
exp( -distance / (2.0 * sig2) );
|
||||
}
|
||||
|
||||
#ifdef PIM_RINT
|
||||
for( k = 0, y = 0; y <= ym2; y++ ) {
|
||||
for( x = 0; x <= xm2; x++, k++ )
|
||||
fprintf( stderr, "%3.2f ", cfs[k] );
|
||||
fprintf( stderr, "\n" );
|
||||
}
|
||||
#endif
|
||||
|
||||
if( !(m = im_create_dmask( filename, xm, ym )) ) {
|
||||
im_free( cfs );
|
||||
return( NULL );
|
||||
}
|
||||
|
||||
/* Copy the 1/4 cfs into the m
|
||||
*/
|
||||
cf = cfs;
|
||||
offset = xm2 * (xm + 1);
|
||||
mc = m->coeff + offset;
|
||||
for( y = 0; y <= ym2; y++ ) {
|
||||
for( x = 0; x <= xm2; x++ ) {
|
||||
pt1 = mc + (y * xm) + x;
|
||||
pt2 = mc - (y * xm) + x;
|
||||
pt3 = mc + (y * xm) - x;
|
||||
pt4 = mc - (y * xm) - x;
|
||||
|
||||
*pt1 = cf[x];
|
||||
*pt2 = cf[x];
|
||||
*pt3 = cf[x];
|
||||
*pt4 = cf[x];
|
||||
}
|
||||
|
||||
cf += (xm2 + 1);
|
||||
}
|
||||
im_free( cfs );
|
||||
|
||||
sum = 0.0;
|
||||
for( k = 0, y = 0; y < m->ysize; y++ )
|
||||
for( x = 0; x < m->xsize; x++, k++ )
|
||||
sum += m->coeff[k];
|
||||
m->scale = sum;
|
||||
m->offset = 0.0;
|
||||
|
||||
#ifdef PIM_RINT
|
||||
im_print_dmask( m );
|
||||
#endif
|
||||
|
||||
return( m );
|
||||
}
|
||||
|
||||
/**
|
||||
* im_log_imask:
|
||||
* @filename: the returned mask has this set as the filename
|
||||
* @sigma: standard deviation of mask
|
||||
* @min_ampl: minimum amplitude
|
||||
*
|
||||
* im_log_imask() works exactly as im_log_dmask(), but the returned mask
|
||||
* is scaled so that it's maximum value it set to 100.
|
||||
*
|
||||
* See also: im_log_dmask(), im_gauss_imask(), im_conv().
|
||||
*
|
||||
* Returns: the calculated mask on success, or NULL on error.
|
||||
*/
|
||||
INTMASK *
|
||||
im_log_imask( const char *filename, double sigma, double min_ampl )
|
||||
{
|
||||
DOUBLEMASK *dm;
|
||||
INTMASK *im;
|
||||
|
||||
if( !(dm = im_log_dmask( filename, sigma, min_ampl )) )
|
||||
return( NULL );
|
||||
|
||||
if( !(im = im_scale_dmask( dm, dm->filename )) ) {
|
||||
im_free_dmask( dm );
|
||||
return( NULL );
|
||||
}
|
||||
im_free_dmask( dm );
|
||||
|
||||
return( im ) ;
|
||||
}
|
||||
@ -1900,7 +1900,7 @@ im_gauss_dmask( const char *filename, double sigma, double min_ampl )
|
||||
VipsImage *t;
|
||||
DOUBLEMASK *msk;
|
||||
|
||||
if( vips_gauss( &t, sigma, min_ampl,
|
||||
if( vips_gaussmat( &t, sigma, min_ampl,
|
||||
NULL ) )
|
||||
return( NULL );
|
||||
if( !(msk = im_vips2mask( t, filename )) ) {
|
||||
@ -1918,7 +1918,7 @@ im_gauss_dmask_sep( const char *filename, double sigma, double min_ampl )
|
||||
VipsImage *t;
|
||||
DOUBLEMASK *msk;
|
||||
|
||||
if( vips_gauss( &t, sigma, min_ampl,
|
||||
if( vips_gaussmat( &t, sigma, min_ampl,
|
||||
"seperable", TRUE,
|
||||
NULL ) )
|
||||
return( NULL );
|
||||
@ -1937,7 +1937,7 @@ im_gauss_imask( const char *filename, double sigma, double min_ampl )
|
||||
VipsImage *t;
|
||||
INTMASK *msk;
|
||||
|
||||
if( vips_gauss( &t, sigma, min_ampl,
|
||||
if( vips_gaussmat( &t, sigma, min_ampl,
|
||||
"integer", TRUE,
|
||||
NULL ) )
|
||||
return( NULL );
|
||||
@ -1956,7 +1956,7 @@ im_gauss_imask_sep( const char *filename, double sigma, double min_ampl )
|
||||
VipsImage *t;
|
||||
INTMASK *msk;
|
||||
|
||||
if( vips_gauss( &t, sigma, min_ampl,
|
||||
if( vips_gaussmat( &t, sigma, min_ampl,
|
||||
"integer", TRUE,
|
||||
"seperable", TRUE,
|
||||
NULL ) )
|
||||
@ -1970,6 +1970,43 @@ im_gauss_imask_sep( const char *filename, double sigma, double min_ampl )
|
||||
return( msk );
|
||||
}
|
||||
|
||||
INTMASK *
|
||||
im_log_imask( const char *filename, double sigma, double min_ampl )
|
||||
{
|
||||
VipsImage *t;
|
||||
INTMASK *msk;
|
||||
|
||||
if( vips_logmat( &t, sigma, min_ampl,
|
||||
"integer", TRUE,
|
||||
NULL ) )
|
||||
return( NULL );
|
||||
if( !(msk = im_vips2imask( t, filename )) ) {
|
||||
g_object_unref( t );
|
||||
return( NULL );
|
||||
}
|
||||
g_object_unref( t );
|
||||
|
||||
return( msk );
|
||||
}
|
||||
|
||||
DOUBLEMASK *
|
||||
im_log_dmask( const char *filename, double sigma, double min_ampl )
|
||||
{
|
||||
VipsImage *t;
|
||||
DOUBLEMASK *msk;
|
||||
|
||||
if( vips_logmat( &t, sigma, min_ampl,
|
||||
NULL ) )
|
||||
return( NULL );
|
||||
if( !(msk = im_vips2mask( t, filename )) ) {
|
||||
g_object_unref( t );
|
||||
return( NULL );
|
||||
}
|
||||
g_object_unref( t );
|
||||
|
||||
return( msk );
|
||||
}
|
||||
|
||||
int
|
||||
im_recomb( IMAGE *in, IMAGE *out, DOUBLEMASK *recomb )
|
||||
{
|
||||
|
||||
@ -47,7 +47,9 @@ int vips_xyz( VipsImage **out, int width, int height, ... )
|
||||
__attribute__((sentinel));
|
||||
int vips_grey( VipsImage **out, int width, int height, ... )
|
||||
__attribute__((sentinel));
|
||||
int vips_gauss( VipsImage **out, double sigma, double min_ampl, ... )
|
||||
int vips_gaussmat( VipsImage **out, double sigma, double min_ampl, ... )
|
||||
__attribute__((sentinel));
|
||||
int vips_logmat( VipsImage **out, double sigma, double min_ampl, ... )
|
||||
__attribute__((sentinel));
|
||||
|
||||
int vips_text( VipsImage **out, const char *text, ... )
|
||||
|
||||
Loading…
Reference in New Issue
Block a user