基于WebGPU实现canvas高级滤镜-编程实验室

大家好，我是CC，在这里欢迎大家的到来～

背景

最近业务上需要个滤镜功能，高级点的且可以直接应用的那种，但是 Fabric.js 上只提供了基础滤镜（像黑白、复古等等）和自定义滤镜（调节单个参数，像亮度、对比度、饱和度等等）。原本设想通过组合各个参数设定好来滤镜使用，但是很快就被现实打败——找不到合适的参数数据，自己也不动设计。后经人指导可以基于 LUT 进行实现。

LUT（Lookup Table，查找表）是一种颜色映射技术，通过预定义的颜色转换规则，将输入颜色映射到输出颜色。

这是一张 LUT 图：

基于这张图实现的滤镜的逻辑大概是：

颜色映射：通过查找表将输入颜色映射到输出颜色
3D到2D转换：将3D颜色空间展开为2D纹理存储
三线性插值：在3D颜色空间中进行插值计算
GPU加速：利用WebGPU的并行计算能力高效处理每个像素

快速入门WebGPU

先看图理解

上边是浏览器的 WebGPU 对象，通过 Adapter（适配器）来匹配底层系统（电脑真实存在的物理设备）的 GPU，后续调用的也是 GPU 的原生 API。

下面介绍 WebGPU 常用 API 和原理。

调用

WebGPU 对象支持在 window 中调用，也可以在 worker 中调用。

Navigator.gpu WorkerNavigator.gpu

获取适配器

const adapter = await Navigator.gpu.requestAdapter() const adapter = await Navigator.gpu.requestAdapter({ powerPreference: 'low-power' // 默认值，也可选 high-performance(非必要使用) })

获取 GPU Device

const adapter = await Navigator.gpu.requestAdapter() const device = await adapter.requestDevice({ defaultQueue: '', label: '', requiredFeatures: [], requiredLimits: })

管线和着色器

管线（pipeline）是一个逻辑结构，可通过编程完成程序工作。

目前管线包括渲染管线和计算管线，渲染管线用于图形渲染，计算管线用于通用计算。

渲染管线包括两个阶段：顶点着色阶段和片元着色阶段。

使用生产机器人的流水线来比喻 WebGPU、pipeline 和 shader 之间的关系。

┌─────────────────────────────────────────────┐ │ WebGPU 工厂 │ │ ┌──────────────────────────────────────┐ │ │ │ Pipeline 生产线 │ │ │ │ ┌──────────────┐ ┌──────────────┐ │ │ │ │ │ 顶点着色器 │ │片段着色器 │ │ │ │ │ │(车体成型机器人) │ │(喷漆机器人) │ │ │ │ │ └──────────────┘ └──────────────┘ │ │ │ │ ↓ ↓ │ │ │ │ 车架成型 上色完成 │ │ │ └──────────────────────────────────────┘ │ └─────────────────────────────────────────────┘ 关键关系： 1. 工厂（WebGPU）提供生产环境 2. 生产线（Pipeline）定义生产流程 3. 机器人（Shader）执行具体任务 4. 三者缺一不可，协同工作

着色器使用

WebGPU 着色器语言是用称为 WebGPU 着色器语言（WGSL）的低级的类 Rust 语言编写的。

建立渲染管线

顶点着色阶段（@vertex代码块）接受包含位置和颜色的数据分块，根据给定的位置定位顶点，插入颜色，然后将数据传入到片元着色器阶段。

片元着色阶段（@fragment代码块）接受来自顶点着色器阶段的数据，并根据给定的颜色为顶点着色。

const shaders = ` struct VertexOut { @builtin(position) position : vec4f, @location(0) color : vec4f } @vertex fn vertex_main(@location(0) position: vec4f, @location(1) color: vec4f) -> VertexOut { var output : VertexOut; output.position = position; output.color = color; return output; } @fragment fn fragment_main(fragData: VertexOut) -> @location(0) vec4f { return fragData.color; } `; const shaderModule = device.createShaderModule({ code: shaders, }); const pipelineDescriptor = { vertex: { module: shaderModule, entryPoint: "vertex_main", buffers: vertexBuffers, }, fragment: { module: shaderModule, entryPoint: "fragment_main", targets: [ { format: navigator.gpu.getPreferredCanvasFormat(), }, ], }, primitive: { topology: "triangle-list", }, layout: "auto", }; const renderPipeline = device.createRenderPipeline(pipelineDescriptor);

创建缓冲区

const vertices = new Float32Array([ 0.0, 0.6, 0, 1, 1, 0, 0, 1, -0.5, -0.6, 0, 1, 0, 1, 0, 1, 0.5, -0.6, 0, 1, 0, 0, 1, 1, ]); const vertexBuffer = device.createBuffer({ size: vertices.byteLength, // make it big enough to store vertices in usage: GPUBufferUsage.VERTEX | GPUBufferUsage.COPY_DST, }); device.queue.writeBuffer(vertexBuffer, 0, vertices, 0, vertices.length);

配置 canvas 上下文

const canvas = document.querySelector("#gpuCanvas"); const context = canvas.getContext("webgpu"); context.configure({ device: device, format: navigator.gpu.getPreferredCanvasFormat(), // 纹理texture格式 alphaMode: "premultiplied", // 半透明纹理时使用的 alpha 模式 });

运行渲染管线

const commandEncoder = device.createCommandEncoder(); const textureView = context.getCurrentTexture().createView(); const renderPassDescriptor = { colorAttachments: [ { clearValue: { r: 0.0, g: 0.5, b: 1.0, a: 1.0 }, loadOp: "clear", storeOp: "store", view: textureView, }, ], }; const passEncoder = commandEncoder.beginRenderPass(renderPassDescriptor); const passEncoder = commandEncoder.beginRenderPass(renderPassDescriptor); passEncoder.setPipeline(pipeline); passEncoder.setBindGroup(0, bindGroup); passEncoder.draw(6); passEncoder.end(); device.queue.submit([commandEncoder.finish()]);

滤镜实现

基础类

export class WebGPUFilter { private canvas: HTMLCanvasElement; private device: GPUDevice | null = null; private context: GPUCanvasContext | null = null; private pipeline: GPURenderPipeline | null = null; private sampler: GPUSampler | null = null; constructor() { this.canvas = document.createElement('canvas'); } public async init() { if (!navigator.gpu) { console.error('WebGPU not supported'); throw new Error('WebGPU not supported'); } const adapter = await navigator.gpu.requestAdapter(); if (!adapter) { console.error('No WebGPU adapter found'); throw new Error('No WebGPU adapter found'); } this.device = await adapter.requestDevice(); this.context = this.canvas.getContext('webgpu'); if (!this.context) { throw new Error('WebGPU context not found'); } const presentationFormat = navigator.gpu.getPreferredCanvasFormat(); this.context.configure({ device: this.device, format: presentationFormat, alphaMode: 'premultiplied', }); // Create shader module const shaderModule = this.device.createShaderModule({ label: 'Filter Shader', code: ` struct VertexOutput { @builtin(position) Position : vec4f, @location(0) v_texCoord : vec2f, } @vertex fn vs_main(@builtin(vertex_index) vertexIndex : u32) -> VertexOutput { var pos = array<vec2f, 6>( vec2f(-1.0, -1.0), vec2f(1.0, -1.0), vec2f(-1.0, 1.0), vec2f(-1.0, 1.0), vec2f(1.0, -1.0), vec2f(1.0, 1.0) ); // UVs: Top-Left origin for WebGPU textures usually // But we need to match how the image is drawn. // Standard quad: // (-1,-1) -> (0, 1) in GL if 0,0 is bottom left. // In WebGPU, texture coords 0,0 is top-left. // If we map (-1,-1) [bottom-left on screen] to (0, 1) [bottom-left in texture uv], it matches. var tex = array<vec2f, 6>( vec2f(0.0, 1.0), vec2f(1.0, 1.0), vec2f(0.0, 0.0), vec2f(0.0, 0.0), vec2f(1.0, 1.0), vec2f(1.0, 0.0) ); var output : VertexOutput; output.Position = vec4f(pos[vertexIndex], 0.0, 1.0); output.v_texCoord = tex[vertexIndex]; return output; } struct Uniforms { intensity : f32, grid_size : f32, } @group(0) @binding(0) var u_image : texture_2d<f32>; @group(0) @binding(1) var u_image_sampler : sampler; @group(0) @binding(2) var u_lut : texture_2d<f32>; @group(0) @binding(3) var u_lut_sampler : sampler; @group(0) @binding(4) var<uniform> uniforms : Uniforms; @fragment fn fs_main(@location(0) v_texCoord : vec2f) -> @location(0) vec4f { let color = textureSample(u_image, u_image_sampler, v_texCoord); let blueColor = color.b * (uniforms.grid_size * uniforms.grid_size - 1.0); var quad1 : vec2f; quad1.y = floor(floor(blueColor) / uniforms.grid_size); quad1.x = floor(blueColor) - (quad1.y * uniforms.grid_size); var quad2 : vec2f; quad2.y = floor(ceil(blueColor) / uniforms.grid_size); quad2.x = ceil(blueColor) - (quad2.y * uniforms.grid_size); let N = uniforms.grid_size * uniforms.grid_size; let halfPixel = 0.5 / N; let scale = (N - 1.0) / N; let r = color.r * scale + halfPixel; let g = color.g * scale + halfPixel; var texPos1 : vec2f; texPos1.x = (quad1.x + r) / uniforms.grid_size; texPos1.y = (quad1.y + g) / uniforms.grid_size; var texPos2 : vec2f; texPos2.x = (quad2.x + r) / uniforms.grid_size; texPos2.y = (quad2.y + g) / uniforms.grid_size; let newColor1 = textureSample(u_lut, u_lut_sampler, texPos1); let newColor2 = textureSample(u_lut, u_lut_sampler, texPos2); let newColor = mix(newColor1, newColor2, fract(blueColor)); let finalColor = mix(color.rgb, newColor.rgb, uniforms.intensity); return vec4f(finalColor, color.a); } `, }); this.pipeline = this.device.createRenderPipeline({ label: 'Filter Pipeline', layout: 'auto', vertex: { module: shaderModule, entryPoint: 'vs_main', }, fragment: { module: shaderModule, entryPoint: 'fs_main', targets: [{ format: presentationFormat }], }, primitive: { topology: 'triangle-list', }, }); this.sampler = this.device.createSampler({ magFilter: 'linear', minFilter: 'linear', }); } private async createTextureFromImage( image: HTMLImageElement | HTMLCanvasElement, flipY = false ): Promise<GPUTexture> { if (!this.device) throw new Error('Device not initialized'); const texture = this.device.createTexture({ size: [image.width, image.height], format: 'rgba8unorm', usage: GPUTextureUsage.TEXTURE_BINDING | GPUTextureUsage.COPY_DST | GPUTextureUsage.RENDER_ATTACHMENT, }); const source = await createImageBitmap(image, { imageOrientation: flipY ? 'flipY' : 'none', premultiplyAlpha: 'none', }); this.device.queue.copyExternalImageToTexture({ source: source }, { texture: texture }, [ image.width, image.height, ]); return texture; } public async apply( sourceImage: HTMLImageElement, lutImage: HTMLImageElement, intensity: number ): Promise<HTMLCanvasElement> { if (!this.device || !this.context || !this.pipeline || !this.sampler) { // Attempt to init if not ready? Or just return canvas. // For simplicity, assume init() called. // If not, try init if (!this.device) await this.init(); if (!this.device) return this.canvas; } const device = this.device!; const context = this.context!; const pipeline = this.pipeline!; const sampler = this.sampler!; // Resize canvas if (this.canvas.width !== sourceImage.width || this.canvas.height !== sourceImage.height) { this.canvas.width = sourceImage.width; this.canvas.height = sourceImage.height; // Re-configure context after resize context.configure({ device: device, format: navigator.gpu.getPreferredCanvasFormat(), alphaMode: 'premultiplied', }); } // Determine grid size let gridSize = 8.0; if (lutImage.width <= 256) { gridSize = 4.0; } // Create Textures // WebGL implementation had sourceImage flipped Y (flipY=true) // and LUT not flipped (flipY=false). // In WebGPU, texture origin is top-left. Our UVs map bottom-left screen to (0,1) texture (bottom-left). // So we should NOT flip the source image, otherwise (0,0) becomes bottom-left in memory, // and UV (0,0) [top-left screen] would sample bottom-left of image. const imageTexture = await this.createTextureFromImage(sourceImage, false); const lutTexture = await this.createTextureFromImage(lutImage, false); // Create Uniform Buffer const uniformBufferSize = 8; // 2 floats * 4 bytes const uniformBuffer = device.createBuffer({ size: uniformBufferSize, usage: GPUBufferUsage.UNIFORM | GPUBufferUsage.COPY_DST, }); const uniformData = new Float32Array([intensity, gridSize]); device.queue.writeBuffer(uniformBuffer, 0, uniformData); // Bind Group const bindGroup = device.createBindGroup({ layout: pipeline.getBindGroupLayout(0), entries: [ { binding: 0, resource: imageTexture.createView() }, { binding: 1, resource: sampler }, { binding: 2, resource: lutTexture.createView() }, { binding: 3, resource: sampler }, { binding: 4, resource: { buffer: uniformBuffer } }, ], }); const commandEncoder = device.createCommandEncoder(); const textureView = context.getCurrentTexture().createView(); const renderPassDescriptor: GPURenderPassDescriptor = { colorAttachments: [ { view: textureView, clearValue: { r: 0.0, g: 0.0, b: 0.0, a: 0.0 }, loadOp: 'clear', storeOp: 'store', }, ], }; const passEncoder = commandEncoder.beginRenderPass(renderPassDescriptor); passEncoder.setPipeline(pipeline); passEncoder.setBindGroup(0, bindGroup); passEncoder.draw(6); passEncoder.end(); device.queue.submit([commandEncoder.finish()]); // Cleanup resources to avoid memory leaks? // In WebGPU, JS GC handles wrappers, but we might want to destroy textures manually if we create them every frame. // However, `apply` returns a canvas that has the content. // If we destroy `imageTexture` and `lutTexture` immediately, it might be fine because commands are submitted. // But let's let GC handle it for now unless performance is an issue. // Note: The canvas is now drawn. return this.canvas; } }

使用

// 初始化类 const filter = new WebGPUFilter(); await filter.init(); webgpuFilterRef.value = filter; // 应用滤镜 webgpuFilterRef.value .apply(img, filterImg, opacity) .then((result) => resolve(result))