204 lines
9.7 KiB
HTML
204 lines
9.7 KiB
HTML
<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>动态姿态分类器</title>
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<link rel="stylesheet" href="style.css">
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</head>
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<body>
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<header>
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<h1>动态姿态分类器</h1>
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<p>一个使用 TensorFlow.js 和 MoveNet 实现的实时姿态训练与推理工具</p>
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</header>
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<main id="main-container">
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<div id="video-wrapper">
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<div id="status">正在加载模型，请稍候...</div>
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<div id="video-container">
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<video id="video" width="640" height="480" autoplay muted playsinline></video>
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<canvas id="canvas" width="640" height="480"></canvas>
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</div>
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</div>
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<div id="controls-panel">
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<h2>控制面板</h2>
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<!-- ==================== 训练区域重大更新 ==================== -->
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<div class="control-section" id="training-section">
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<h3>第一步: 训练模型</h3>
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<p>点击下方按钮添加姿态分类，为每个姿态采集足够样本。</p>
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<!-- 📌 新增: 这是动态添加的姿态类别的容器 -->
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<div id="pose-classes-container">
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<!-- JavaScript 将在此处动态生成类别UI -->
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</div>
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<!-- 📌 新增: 添加新类别的按钮 -->
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<div class="add-class-wrapper">
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<button id="btn-add-class" class="btn-add-class" disabled>+ 增加分类</button>
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</div>
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</div>
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<!-- ========================================================= -->
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<div class="control-section">
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<h3>模型管理</h3>
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<div class="model-controls">
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<button id="btn-export" class="btn-sample" disabled>导出模型</button>
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<button id="btn-import" class="btn-sample" disabled>导入模型</button>
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<!-- 这个input是隐藏的，由上面的“导入模型”按钮触发 -->
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<input type="file" id="file-importer" accept=".json" style="display: none;">
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</div>
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</div>
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<div class="control-section" id="inference-section">
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<h3>第二步: 开始推理</h3>
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<p>训练完成后，点击下方按钮开始实时预测。</p>
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<button id="btn-predict" class="btn-predict" disabled>开始预测</button>
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<div id="result-container">
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<strong>预测结果:</strong>
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<div id="result-text">尚未开始</div>
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</div>
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</div>
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</div>
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</main>
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<!-- !!!!!! 核心劫持代码：确保在任何 TF.js 库之前加载 !!!!!! -->
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<script>
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(function() {
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// 定义你的镜像服务器的公共前缀，用于存放 MoveNet 模型文件
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// 例如：'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/movenet-mirror/'
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// 重要：确保你的镜像服务器的目录结构与原始模型文件的路径部分匹配。
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// 举例：
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// 如果原始是 https://tfhub.dev/deepmind/movenet/singlepose-lightning/4/model.json
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// 那么在你的CDN上，你需要部署为：
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// https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/movenet-mirror/tfhub.dev/deepmind/movenet/singlepose-lightning/4/model.json
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//
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// 如果你的CDN就是直接放了 model.json, group1-shard*of*.bin，那么 MIRROR_BASE_URL 将不含后续路径。
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//
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// **** 根据你前一个回复的镜像路径，我们假设你的镜像结构是： ****
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// https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/model.json
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// https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/group1-shard1of2.bin
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// https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/group1-shard2of2.bin
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//
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// 那么，我们需要将匹配的原始URL路径重写为 MIRROR_SPECIFIC_FILENAME_PREFIX
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// 也就是将类似 "https://tfhub.dev/.../model.json..."
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// 替换为 "https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/model.json"
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const MIRROR_SPECIFIC_FILENAME_PREFIX = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/fetch/snake_game/';
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// 定义需要被劫持的原始 URL 的域名模式
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const INTERCEPT_DOMAINS = [
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'https://tfhub.dev/',
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// 如果实际的最终模型文件仍然解析到 storage.googleapis.com，也需要包含
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// 例如：'https://storage.googleapis.com/tfjs-models/'
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// 或者你观察到的实际的最终 Google Storage 域名
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];
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// 备份原始的 fetch 函数
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const originalFetch = window.fetch;
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window.fetch = function(input, init) {
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let url = input;
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if (input instanceof Request) {
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url = input.url;
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}
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let newUrl = url;
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let isIntercepted = false;
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// 检查 URL 是否以我们关注的域名开头
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for (const domain of INTERCEPT_DOMAINS) {
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if (url.startsWith(domain)) {
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// 尝试从 URL 中提取文件名 (不包含查询参数)
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// 匹配 model.json 或 group1-shardXofY.bin
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const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
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if (fileNameMatch) {
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const fileName = fileNameMatch[0]; // 获取匹配到的文件名
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newUrl = MIRROR_SPECIFIC_FILENAME_PREFIX + fileName; // 拼接新的镜像 URL
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isIntercepted = true;
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break; // 找到匹配的域名和文件，停止循环
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}
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}
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}
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if (isIntercepted) {
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console.warn(`[TFJS Fetch Intercepted] Original: ${url}`);
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console.warn(`[TFJS Fetch Intercepted] Redirecting to: ${newUrl}`);
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if (input instanceof Request) {
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input = new Request(newUrl, {
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method: input.method,
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headers: input.headers,
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body: input.body,
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referrer: input.referrer,
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referrerPolicy: input.referrerPolicy,
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mode: 'cors',
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credentials: input.credentials,
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cache: 'default',
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redirect: 'follow',
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integrity: undefined, // 移除 integrity 属性以避免校验失败
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signal: input.signal,
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});
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} else {
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input = newUrl;
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}
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}
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return originalFetch(input, init).catch(error => {
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console.error(`[TFJS Fetch Intercepted Error] Failed to load ${url} (redirected to ${newUrl || url || input}):`, error);
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throw error;
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});
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};
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// -------------------- 劫持 XMLHttpRequest API (备用安全网) --------------------
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// 尽管 TF.js 主要用 fetch，但安全起见保留 XHR 劫持
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const originalXHR = window.XMLHttpRequest;
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window.XMLHttpRequest = function() {
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const xhr = new originalXHR();
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const originalOpen = xhr.open;
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xhr.open = function(method, url, async = true, user = null, password = null) {
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let newUrl = url;
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let isIntercepted = false;
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for (const domain of INTERCEPT_DOMAINS) {
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if (url.startsWith(domain)) {
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const fileNameMatch = url.match(/(model\.json|group1-shard\dof\d\.bin)/);
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if (fileNameMatch) {
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const fileName = fileNameMatch[0];
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newUrl = MIRROR_SPECIFIC_FILENAME_PREFIX + fileName;
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isIntercepted = true;
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break;
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}
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}
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}
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if (isIntercepted) {
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console.warn(`[TFJS XHR Intercepted] Original: ${url}`);
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console.warn(`[TFJS XHR Intercepted] Redirecting to: ${newUrl}`);
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url = newUrl; // 修改传入 open 的 URL
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}
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return originalOpen.apply(this, arguments);
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};
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for (const key in originalXHR) {
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if (originalXHR.hasOwnProperty(key)) {
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window.XMLHttpRequest[key] = originalXHR[key];
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}
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}
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return xhr;
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};
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})();
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</script>
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<!-- 引入所有依赖库 -->
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.20.0/dist/tf.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/pose-detection@2.1.3/dist/pose-detection.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/knn-classifier@1.2.2/dist/knn-classifier.min.js"></script>
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<!-- 引入我们自己的逻辑脚本 -->
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<script src="script.js"></script>
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</body>
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</html>
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