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