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v4:Two-stage cascade (WNet)

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youfu
2026-06-16 17:47:20 +08:00
parent daf3d68247
commit 11fea3d054
13 changed files with 154 additions and 55 deletions
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web/index.html
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@@ -56,7 +56,8 @@
<div class="vers">
<button class="ver-btn" data-v="v1" data-i18n="btn_v1"></button>
<button class="ver-btn" data-v="v2" data-i18n="btn_v2"></button>
<button class="ver-btn" data-v="v3" data-i18n="btn_v3" disabled></button>
<button class="ver-btn" data-v="v3" data-i18n="btn_v3"></button>
<button class="ver-btn" data-v="v4" data-i18n="btn_v4"></button>
</div>
<div class="notice" id="verNotice"></div>
<div class="metricbar">
@@ -97,18 +98,19 @@ const T = {
title: "Predicting Wireless Coverage with Deep Learning",
subtitle: "A U-Net predicts a base station's signal coverage across a city — running live in your browser. Switch between model versions to see how it improved.",
ver_h: "Model version",
btn_v1: "v1 · baseline", btn_v2: "v2 · distance fix", btn_v3: "v3 · soon",
m_error: "RMSE on unseen cities",
btn_v1: "v1 · baseline", btn_v2: "v2 · distance fix", btn_v3: "v3 · checkerboard fix", btn_v4: "v4 · WNet refine",
m_error: "RMSE on held-out cities",
notice_v1: "Baseline (2-channel input: buildings + transmitter). Known issue: coverage cuts off in a square around the transmitter — the far field stays blank because the network can't propagate the source that far.",
notice_v2: "Adds a distance-to-transmitter input channel (3-channel). Fixed: the square cutoff — coverage now spans the whole map, with far-field rays and distant building shadows. Known issue: faint checkerboard texture in smooth areas, from transposed-convolution upsampling.",
notice_v3: "In progress. Replaces transposed-convolution upsampling with resize-convolution to remove the checkerboard texture. Not yet available.",
notice_v3: "Replaces transposed-convolution upsampling with resize-convolution. Fixed: the checkerboard texture — smooth regions are clean. Known issue: along a long unobstructed corridor the far-field beam fades before reaching the edge — a residual receptive-field limit.",
notice_v4: "Two cascaded U-Nets — a coarse predictor feeds a refiner. Because the refiner's input already contains a global coverage estimate, every pixel gets long-range context (a larger effective receptive field). Fixed: the fading corridor — coverage stays bright to the edge. Lowest error of all four versions.",
demo_h: "Try it yourself",
select_label: "City layout:", click_hint: "Click the map to place a transmitter.",
input_title: "City map — click to place transmitter", output_title: "Predicted coverage",
legend_weak: "weak", legend_strong: "strong",
how_h: "How it works",
how_p: "The model takes the building layout and the transmitter location as image channels and outputs a coverage heatmap, learned from the public RadioMapSeer dataset (5.9 GHz urban propagation). It was given no propagation equations — it learned signal falloff and building shadowing from data. The model runs entirely in your browser via ONNX Runtime Web; nothing is sent to a server.",
footer: "Dataset: RadioMapSeer (Yapar et al., 2022), CC BY 4.0. Independent portfolio project. Error reported on held-out test cities.",
footer: "Dataset: RadioMapSeer (Yapar et al., 2022), CC BY 4.0. Independent portfolio project. Errors are on held-out cities the model never trained on.",
st_loading: "Loading model…", st_ready: "Pick a layout and click to place a transmitter.",
st_running: "Running inference…",
st_done: (ms) => "Predicted in " + ms + " ms. Click again to move the transmitter.",
@@ -116,37 +118,39 @@ const T = {
},
zh: {
title: "基于深度学习的无线信号覆盖预测",
subtitle: "一个 U-Net 在你的浏览器中实时预测基站的信号覆盖。切换不同模型版本，看看它是如何一步步改进的。",
subtitle: "一个 U-Net 在你的浏览器中实时预测基站的信号覆盖。切换不同模型版本,看看它是如何一步步改进的。",
ver_h: "模型版本",
btn_v1: "v1 · 基线", btn_v2: "v2 · 距离修复", btn_v3: "v3 · 即将推出",
m_error: "未见城市上的 RMSE",
notice_v1: "基线模型（2 通道输入：建筑 + 发射机）。已知问题：覆盖在发射机周围呈方形截断——远场为空白，因为网络无法将信号源的影响传播到远处。",
notice_v2: "新增「到发射机的距离」输入通道（3 通道）。已修复：方形截断——覆盖现已贯穿整张地图，远场射线与远处建筑阴影都能呈现。已知问题：平滑区域出现轻微棋盘格纹理，来自转置卷积上采样。",
notice_v3: "开发中。用 resize 卷积替换转置卷积上采样，以消除棋盘格纹理。暂未上线。",
btn_v1: "v1 · 基线", btn_v2: "v2 · 距离修复", btn_v3: "v3 · 棋盘格修复", btn_v4: "v4 · WNet 精修",
m_error: "留出城市上的 RMSE",
notice_v1: "基线模型(2 通道输入:建筑 + 发射机)。已知问题:覆盖在发射机周围呈方形截断——远场为空白,因为网络无法将信号源的影响传播到远处。",
notice_v2: "新增「到发射机的距离」输入通道(3 通道)。已修复:方形截断——覆盖现已贯穿整张地图,远场射线与远处建筑阴影都能呈现。已知问题:平滑区域出现轻微棋盘格纹理,来自转置卷积上采样。",
notice_v3: "用 resize 卷积(双线性上采样 + 卷积)替换转置卷积。已修复:棋盘格纹理消失,平滑区域变得干净。已知问题:在无遮挡的长走廊中,远场光束在到达边缘前逐渐变暗——残留的感受野限制。",
notice_v4: "两个级联 U-Net——粗预测网络的输出送入精修网络。由于精修网络的输入已包含一张全局覆盖估计,每个像素都获得了长程上下文(更大的有效感受野)。已修复:长走廊衰减,覆盖一直明亮延伸到边缘。四个版本中误差最低。",
demo_h: "在线体验",
select_label: "城市布局：", click_hint: "点击地图以放置发射机。",
select_label: "城市布局:", click_hint: "点击地图以放置发射机。",
input_title: "城市地图——点击放置发射机", output_title: "预测覆盖",
legend_weak: "弱", legend_strong: "强",
how_h: "实现原理",
how_p: "模型以建筑布局和发射机位置作为图像通道输入，输出覆盖热力图，训练自公开的 RadioMapSeer 数据集（5.9 GHz 城市传播）。它没有被告知任何传播公式，完全从数据中学会了信号衰减与建筑遮蔽。模型通过 ONNX Runtime Web 完全在你的浏览器中运行，不会向服务器发送任何数据。",
footer: "数据集：RadioMapSeer（Yapar 等，2022），CC BY 4.0 许可。独立作品集项目。误差基于留出的测试城市。",
how_p: "模型以建筑布局和发射机位置作为图像通道输入,输出覆盖热力图,训练自公开的 RadioMapSeer 数据集(5.9 GHz 城市传播)。它没有被告知任何传播公式,完全从数据中学会了信号衰减与建筑遮蔽。模型通过 ONNX Runtime Web 完全在你的浏览器中运行,不向服务器发送任何数据。",
footer: "数据集:RadioMapSeer(Yapar 等,2022),CC BY 4.0 许可。独立作品集项目。误差基于模型从未训练过的留出城市。",
st_loading: "正在加载模型…", st_ready: "选择布局并点击放置发射机。",
st_running: "正在推理…",
st_done: (ms) => "推理完成，用时 " + ms + " 毫秒。再次点击可移动发射机。",
st_error: (m) => "错误：" + m
st_done: (ms) => "推理完成,用时 " + ms + " 毫秒。再次点击可移动发射机。",
st_error: (m) => "错误:" + m
}
};
const VERSIONS = {
v1: { model: "radio_unet_v1.onnx", channels: 2, available: true },
v2: { model: "radio_unet_v2.onnx", channels: 3, available: true },
v3: { model: "radio_unet_v3.onnx", channels: 3, available: false },
v3: { model: "radio_unet_v3.onnx", channels: 3, available: true },
v4: { model: "radio_unet_v4.onnx", channels: 3, available: true },
};
const METRICS = { v1: "0.052", v2: "0.034", v3: "—" };
const METRICS = { v1: "0.052", v2: "0.034", v3: "0.030", v4: "0.021" };
const SIZE = 256;
let currentLang = (navigator.language || "en").toLowerCase().startsWith("zh") ? "zh" : "en";
let activeVersion = "v2";
let activeVersion = "v4";
const sessions = {};
let buildings = null, txRC = null;
@@ -221,7 +225,7 @@ function buildInput(){
input.set(buildings, 0); // channel 0: buildings
const [r,c] = txRC;
input[SIZE*SIZE + r*SIZE + c] = 1.0; // channel 1: transmitter
if (ch === 3){ // channel 2: distance to Tx (v2/v3)
if (ch === 3){ // channel 2: distance to Tx (v2/v3/v4)
const off = 2*SIZE*SIZE, norm = Math.SQRT2 * SIZE;
for(let yy=0; yy<SIZE; yy++)
for(let xx=0; xx<SIZE; xx++)