197 lines
5.2 KiB
Plaintext
197 lines
5.2 KiB
Plaintext
// Copyright (c) 2017-2018 Xiamen Yaji Software Co., Ltd.
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// 高斯模糊
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//
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// 参考资料（必读）
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// * http://www.ruanyifeng.com/blog/2012/11/gaussian_blur.html
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// * https://zh.wikipedia.org/wiki/%E9%AB%98%E6%96%AF%E6%A8%A1%E7%B3%8A
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CCEffect %{
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techniques:
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- passes:
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- vert: vs
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frag: fs
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blendState:
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targets:
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- blend: true
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rasterizerState:
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cullMode: none
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properties:
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texture: { value: white }
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alphaThreshold: { value: 0.5 }
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# # 标准方差值
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# stDev: {
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# value: 0.84089642,
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# inspector: {
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# tooltip: "标准方差值"
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# }
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# }
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# 纹理尺寸
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textureSize: {
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value: [100.0, 100.0],
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inspector: {
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tooltip: "纹理尺寸px（宽 x 高）"
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}
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}
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}%
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CCProgram vs %{
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precision highp float;
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#include <cc-global>
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#include <cc-local>
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in vec3 a_position;
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in vec4 a_color;
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out vec4 v_color;
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#if USE_TEXTURE
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in vec2 a_uv0;
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out vec2 v_uv0;
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#endif
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void main () {
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vec4 pos = vec4(a_position, 1);
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#if CC_USE_MODEL
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pos = cc_matViewProj * cc_matWorld * pos;
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#else
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pos = cc_matViewProj * pos;
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#endif
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#if USE_TEXTURE
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v_uv0 = a_uv0;
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#endif
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v_color = a_color;
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gl_Position = pos;
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}
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}%
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CCProgram fs %{
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precision highp float;
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#include <alpha-test>
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in vec4 v_color;
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#if USE_TEXTURE
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in vec2 v_uv0;
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uniform sampler2D texture;
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#endif
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#if ENABLE_GAUSSIAN_BLUR
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// 定义无理数
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#define e 2.718281828459045
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// 定义标准方差值（方差值越大，越模糊，但是需要计算的高斯矩阵范围会变大，从而带来巨大的计算量）
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// #define stDev 0.84089642
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#define stDev 1.5
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// #define stDev 5.0
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// #define stDev 10.0
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// 定义π
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#define pi 3.141592653589793
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// 接收外部变量
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uniform GaussianBlur {
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// 纹理尺寸（宽 x 高）（px）
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vec2 textureSize;
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// // 标准方差值
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// float stDev;
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}
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/**
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* 获取权重(对应二维高斯函数公式，见 https://zh.wikipedia.org/wiki/%E9%AB%98%E6%96%AF%E6%A8%A1%E7%B3%8A )
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*/
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float getWeight(float x, float y) {
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return (1.0 / (2.0 * pi * pow(stDev, 2.0))) * pow(1.0 / e, (pow(x, 2.0) + pow(y, 2.0)) / (2.0 * pow(stDev, 2.0)));
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}
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#endif
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void main () {
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vec4 o = vec4(1, 1, 1, 1);
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#if USE_TEXTURE
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o *= texture(texture, v_uv0);
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#if CC_USE_ALPHA_ATLAS_TEXTURE
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o.a *= texture2D(texture, v_uv0 + vec2(0, 0.5)).r;
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#endif
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#endif
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o *= v_color;
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ALPHA_TEST(o);
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gl_FragColor = o;
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#if ENABLE_GAUSSIAN_BLUR
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// 根据高斯分布（也叫正态分布），在3个标准差范围内的分布比例占到99%的权重，因此我们只需要计算矩阵范围 [6 * stDev + 1, 6 * stDev +1] 上的权重
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const float size = floor(stDev * 6.0 + 1.0);
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const float halfSize = floor(size / 2.0);
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// 步骤一：计算所有权重的和
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// // v1：遍历所有点，每个点都计算权重
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// float totalWeight = 0.0;
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// for(float x = -halfSize; x<= halfSize; x++) {
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// for (float y = -halfSize; y<= halfSize; y++) {
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// totalWeight += getWeight(x, y);
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// }
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// }
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// v2：因为高斯分布是对称的，所以只计算原点、X轴正方向 * 2 、Y轴正方向 * 2 、第一象限的权重 * 4即可求出所有权重之和，相比起v1版本，减少很多循环计算
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// 原点
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float totalWeight = getWeight(0.0, 0.0);
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// X轴正方向上的权重 * 2.0 就是整个X轴上的权重
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for(float x = 1.0; x <= halfSize; x++) {
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totalWeight += getWeight(x, 0.0) * 2.0;
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}
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// Y轴正方向上的权重 * 2.0 就是整个Y轴上的权重
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for(float y = 1.0; y <= halfSize; y++) {
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totalWeight += getWeight(0.0, y) * 2.0;
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}
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// 第一象限的权重 * 4.0 就是4个象限的权重
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for(float x = 1.0; x <= halfSize; x++) {
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for (float y = 1.0; y<= halfSize; y++) {
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totalWeight += getWeight(x, y) * 4.0;
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}
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}
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// TODO:
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//
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// 因为权重矩阵是一次性计算即可不断应用，因此可以将权重矩阵的计算放到CPU计算，并传入到Shader直接渲染，因此有以下优化方案
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//
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// v3：原始权重矩阵在CPU计算并传入到Shader
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// v4：加权平均后的权重矩阵在CPU计算并传入Shader
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// 步骤二：采样周边像素并应用加权平均值，得出最终像素值
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vec4 finalColor = vec4(0.0, 0.0, 0.0, 0.0);
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// float divider = 0.01;
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float onePxWidth = 1.0 / textureSize.x;
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float onePxHeight = 1.0 / textureSize.y;
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for(float x = -halfSize; x<= halfSize; x++) {
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for (float y = -halfSize; y<= halfSize; y++) {
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// 求出对应坐标的真正权重（对应权重矩阵）
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float weight = getWeight(x, y) / totalWeight;
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// 求出对应坐标像素颜色值的加权值
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// finalColor += texture(texture, v_uv0 + vec2(divider * x, divider * y)) * weight;
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finalColor += texture(texture, v_uv0 + vec2(onePxWidth * x, onePxHeight * y)) * weight;
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}
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}
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gl_FragColor = finalColor;
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#endif
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}
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}%
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