boofcv.alg.transform.ii.impl.ImplIntegralImageOps Maven / Gradle / Ivy
/*
* Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.alg.transform.ii.impl;
import boofcv.alg.transform.ii.IntegralKernel;
import boofcv.struct.ImageRectangle;
import boofcv.struct.image.*;
/**
*
* Compute the integral image for different types of input images.
*
*
*
* DO NOT MODIFY: Generated by {@link GenerateImplIntegralImageOps}.
*
*
* @author Peter Abeles
*/
public class ImplIntegralImageOps {
public static void transform(final GrayF32 input , final GrayF32 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
float total = 0;
for( ; indexSrc < end; indexSrc++ ) {
transformed.data[indexDst++] = total += input.data[indexSrc];
}
for( int y = 1; y < input.height; y++ ) {
indexSrc = input.startIndex + input.stride*y;
indexDst = transformed.startIndex + transformed.stride*y;
int indexPrev = indexDst - transformed.stride;
end = indexSrc + input.width;
total = 0;
for( ; indexSrc < end; indexSrc++ ) {
total += input.data[indexSrc];
transformed.data[indexDst++] = transformed.data[indexPrev++] + total;
}
}
}
public static void transform(final GrayF64 input , final GrayF64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
double total = 0;
for( ; indexSrc < end; indexSrc++ ) {
transformed.data[indexDst++] = total += input.data[indexSrc];
}
for( int y = 1; y < input.height; y++ ) {
indexSrc = input.startIndex + input.stride*y;
indexDst = transformed.startIndex + transformed.stride*y;
int indexPrev = indexDst - transformed.stride;
end = indexSrc + input.width;
total = 0;
for( ; indexSrc < end; indexSrc++ ) {
total += input.data[indexSrc];
transformed.data[indexDst++] = transformed.data[indexPrev++] + total;
}
}
}
public static void transform(final GrayU8 input , final GrayS32 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
int total = 0;
for( ; indexSrc < end; indexSrc++ ) {
transformed.data[indexDst++] = total += input.data[indexSrc]& 0xFF;
}
for( int y = 1; y < input.height; y++ ) {
indexSrc = input.startIndex + input.stride*y;
indexDst = transformed.startIndex + transformed.stride*y;
int indexPrev = indexDst - transformed.stride;
end = indexSrc + input.width;
total = 0;
for( ; indexSrc < end; indexSrc++ ) {
total += input.data[indexSrc]& 0xFF;
transformed.data[indexDst++] = transformed.data[indexPrev++] + total;
}
}
}
public static void transform(final GrayS32 input , final GrayS32 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
int total = 0;
for( ; indexSrc < end; indexSrc++ ) {
transformed.data[indexDst++] = total += input.data[indexSrc];
}
for( int y = 1; y < input.height; y++ ) {
indexSrc = input.startIndex + input.stride*y;
indexDst = transformed.startIndex + transformed.stride*y;
int indexPrev = indexDst - transformed.stride;
end = indexSrc + input.width;
total = 0;
for( ; indexSrc < end; indexSrc++ ) {
total += input.data[indexSrc];
transformed.data[indexDst++] = transformed.data[indexPrev++] + total;
}
}
}
public static void transform(final GrayS64 input , final GrayS64 transformed )
{
int indexSrc = input.startIndex;
int indexDst = transformed.startIndex;
int end = indexSrc + input.width;
long total = 0;
for( ; indexSrc < end; indexSrc++ ) {
transformed.data[indexDst++] = total += input.data[indexSrc];
}
for( int y = 1; y < input.height; y++ ) {
indexSrc = input.startIndex + input.stride*y;
indexDst = transformed.startIndex + transformed.stride*y;
int indexPrev = indexDst - transformed.stride;
end = indexSrc + input.width;
total = 0;
for( ; indexSrc < end; indexSrc++ ) {
total += input.data[indexSrc];
transformed.data[indexDst++] = transformed.data[indexPrev++] + total;
}
}
}
public static void convolve( GrayF32 integral ,
IntegralKernel kernel,
GrayF32 output )
{
for( int y = 0; y < integral.height; y++ ) {
for( int x = 0; x < integral.width; x++ ) {
float total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static void convolveBorder(GrayF32 integral ,
IntegralKernel kernel,
GrayF32 output , int borderX , int borderY )
{
for( int x = 0; x < integral.width; x++ ) {
for( int y = 0; y < borderY; y++ ) {
float total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int y = integral.height-borderY; y < integral.height; y++ ) {
float total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
int endY = integral.height-borderY;
for( int y = borderY; y < endY; y++ ) {
for( int x = 0; x < borderX; x++ ) {
float total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int x = integral.width-borderX; x < integral.width; x++ ) {
float total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static float convolveSparse(GrayF32 integral , IntegralKernel kernel , int x , int y )
{
float ret = 0;
int N = kernel.getNumBlocks();
for( int i = 0; i < N; i++ ) {
ImageRectangle r = kernel.blocks[i];
ret += block_zero(integral,x+r.x0,y+r.y0,x+r.x1,y+r.y1)*kernel.scales[i];
}
return ret;
}
public static float block_unsafe(GrayF32 integral , int x0 , int y0 , int x1 , int y1 )
{
float br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
float tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
float bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
float tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static float block_zero(GrayF32 integral , int x0 , int y0 , int x1 , int y1 )
{
x0 = Math.min(x0,integral.width-1);
y0 = Math.min(y0,integral.height-1);
x1 = Math.min(x1,integral.width-1);
y1 = Math.min(y1,integral.height-1);
float br=0,tr=0,bl=0,tl=0;
if( x1 >= 0 && y1 >= 0)
br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
if( y0 >= 0 && x1 >= 0)
tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
if( x0 >= 0 && y1 >= 0)
bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
if( x0 >= 0 && y0 >= 0)
tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static void convolve( GrayS32 integral ,
IntegralKernel kernel,
GrayS32 output )
{
for( int y = 0; y < integral.height; y++ ) {
for( int x = 0; x < integral.width; x++ ) {
int total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static void convolveBorder(GrayS32 integral ,
IntegralKernel kernel,
GrayS32 output , int borderX , int borderY )
{
for( int x = 0; x < integral.width; x++ ) {
for( int y = 0; y < borderY; y++ ) {
int total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int y = integral.height-borderY; y < integral.height; y++ ) {
int total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
int endY = integral.height-borderY;
for( int y = borderY; y < endY; y++ ) {
for( int x = 0; x < borderX; x++ ) {
int total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int x = integral.width-borderX; x < integral.width; x++ ) {
int total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static int convolveSparse(GrayS32 integral , IntegralKernel kernel , int x , int y )
{
int ret = 0;
int N = kernel.getNumBlocks();
for( int i = 0; i < N; i++ ) {
ImageRectangle r = kernel.blocks[i];
ret += block_zero(integral,x+r.x0,y+r.y0,x+r.x1,y+r.y1)*kernel.scales[i];
}
return ret;
}
public static int block_unsafe(GrayS32 integral , int x0 , int y0 , int x1 , int y1 )
{
int br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
int tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
int bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
int tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static int block_zero(GrayS32 integral , int x0 , int y0 , int x1 , int y1 )
{
x0 = Math.min(x0,integral.width-1);
y0 = Math.min(y0,integral.height-1);
x1 = Math.min(x1,integral.width-1);
y1 = Math.min(y1,integral.height-1);
int br=0,tr=0,bl=0,tl=0;
if( x1 >= 0 && y1 >= 0)
br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
if( y0 >= 0 && x1 >= 0)
tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
if( x0 >= 0 && y1 >= 0)
bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
if( x0 >= 0 && y0 >= 0)
tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static void convolve( GrayF64 integral ,
IntegralKernel kernel,
GrayF64 output )
{
for( int y = 0; y < integral.height; y++ ) {
for( int x = 0; x < integral.width; x++ ) {
double total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static void convolveBorder(GrayF64 integral ,
IntegralKernel kernel,
GrayF64 output , int borderX , int borderY )
{
for( int x = 0; x < integral.width; x++ ) {
for( int y = 0; y < borderY; y++ ) {
double total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int y = integral.height-borderY; y < integral.height; y++ ) {
double total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
int endY = integral.height-borderY;
for( int y = borderY; y < endY; y++ ) {
for( int x = 0; x < borderX; x++ ) {
double total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int x = integral.width-borderX; x < integral.width; x++ ) {
double total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static double convolveSparse(GrayF64 integral , IntegralKernel kernel , int x , int y )
{
double ret = 0;
int N = kernel.getNumBlocks();
for( int i = 0; i < N; i++ ) {
ImageRectangle r = kernel.blocks[i];
ret += block_zero(integral,x+r.x0,y+r.y0,x+r.x1,y+r.y1)*kernel.scales[i];
}
return ret;
}
public static double block_unsafe(GrayF64 integral , int x0 , int y0 , int x1 , int y1 )
{
double br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
double tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
double bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
double tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static double block_zero(GrayF64 integral , int x0 , int y0 , int x1 , int y1 )
{
x0 = Math.min(x0,integral.width-1);
y0 = Math.min(y0,integral.height-1);
x1 = Math.min(x1,integral.width-1);
y1 = Math.min(y1,integral.height-1);
double br=0,tr=0,bl=0,tl=0;
if( x1 >= 0 && y1 >= 0)
br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
if( y0 >= 0 && x1 >= 0)
tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
if( x0 >= 0 && y1 >= 0)
bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
if( x0 >= 0 && y0 >= 0)
tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static void convolve( GrayS64 integral ,
IntegralKernel kernel,
GrayS64 output )
{
for( int y = 0; y < integral.height; y++ ) {
for( int x = 0; x < integral.width; x++ ) {
long total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static void convolveBorder(GrayS64 integral ,
IntegralKernel kernel,
GrayS64 output , int borderX , int borderY )
{
for( int x = 0; x < integral.width; x++ ) {
for( int y = 0; y < borderY; y++ ) {
long total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int y = integral.height-borderY; y < integral.height; y++ ) {
long total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
int endY = integral.height-borderY;
for( int y = borderY; y < endY; y++ ) {
for( int x = 0; x < borderX; x++ ) {
long total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
for( int x = integral.width-borderX; x < integral.width; x++ ) {
long total = 0;
for( int i = 0; i < kernel.blocks.length; i++ ) {
ImageRectangle b = kernel.blocks[i];
total += block_zero(integral,x+b.x0,y+b.y0,x+b.x1,y+b.y1)*kernel.scales[i];
}
output.set(x,y,total);
}
}
}
public static long convolveSparse(GrayS64 integral , IntegralKernel kernel , int x , int y )
{
long ret = 0;
int N = kernel.getNumBlocks();
for( int i = 0; i < N; i++ ) {
ImageRectangle r = kernel.blocks[i];
ret += block_zero(integral,x+r.x0,y+r.y0,x+r.x1,y+r.y1)*kernel.scales[i];
}
return ret;
}
public static long block_unsafe(GrayS64 integral , int x0 , int y0 , int x1 , int y1 )
{
long br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
long tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
long bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
long tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
public static long block_zero(GrayS64 integral , int x0 , int y0 , int x1 , int y1 )
{
x0 = Math.min(x0,integral.width-1);
y0 = Math.min(y0,integral.height-1);
x1 = Math.min(x1,integral.width-1);
y1 = Math.min(y1,integral.height-1);
long br=0,tr=0,bl=0,tl=0;
if( x1 >= 0 && y1 >= 0)
br = integral.data[ integral.startIndex + y1*integral.stride + x1 ];
if( y0 >= 0 && x1 >= 0)
tr = integral.data[ integral.startIndex + y0*integral.stride + x1 ];
if( x0 >= 0 && y1 >= 0)
bl = integral.data[ integral.startIndex + y1*integral.stride + x0 ];
if( x0 >= 0 && y0 >= 0)
tl = integral.data[ integral.startIndex + y0*integral.stride + x0 ];
return br-tr-bl+tl;
}
}