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import {
Vector2
} from 'three';
/**
* Convolution shader
* ported from o3d sample to WebGL / GLSL
*/
const ConvolutionShader = {
name: 'ConvolutionShader',
defines: {
'KERNEL_SIZE_FLOAT': '25.0',
'KERNEL_SIZE_INT': '25'
},
uniforms: {
'tDiffuse': { value: null },
'uImageIncrement': { value: new Vector2( 0.001953125, 0.0 ) },
'cKernel': { value: [] }
},
vertexShader: /* glsl */`
uniform vec2 uImageIncrement;
varying vec2 vUv;
void main() {
vUv = uv - ( ( KERNEL_SIZE_FLOAT - 1.0 ) / 2.0 ) * uImageIncrement;
gl_Position = projectionMatrix * modelViewMatrix * vec4( position, 1.0 );
}`,
fragmentShader: /* glsl */`
uniform float cKernel[ KERNEL_SIZE_INT ];
uniform sampler2D tDiffuse;
uniform vec2 uImageIncrement;
varying vec2 vUv;
void main() {
vec2 imageCoord = vUv;
vec4 sum = vec4( 0.0, 0.0, 0.0, 0.0 );
for( int i = 0; i < KERNEL_SIZE_INT; i ++ ) {
sum += texture2D( tDiffuse, imageCoord ) * cKernel[ i ];
imageCoord += uImageIncrement;
}
gl_FragColor = sum;
}`,
buildKernel: function ( sigma ) {
// We lop off the sqrt(2 * pi) * sigma term, since we're going to normalize anyway.
const kMaxKernelSize = 25;
let kernelSize = 2 * Math.ceil( sigma * 3.0 ) + 1;
if ( kernelSize > kMaxKernelSize ) kernelSize = kMaxKernelSize;
const halfWidth = ( kernelSize - 1 ) * 0.5;
const values = new Array( kernelSize );
let sum = 0.0;
for ( let i = 0; i < kernelSize; ++ i ) {
values[ i ] = gauss( i - halfWidth, sigma );
sum += values[ i ];
}
// normalize the kernel
for ( let i = 0; i < kernelSize; ++ i ) values[ i ] /= sum;
return values;
}
};
function gauss( x, sigma ) {
return Math.exp( - ( x * x ) / ( 2.0 * sigma * sigma ) );
}
export { ConvolutionShader };