[MF]修复劫持相似链接影响，完善正则匹配
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@ -516,19 +516,19 @@
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// 启动检测循环
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startDetectionLoop();
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// 尝试从 CDN 加载模型
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try {
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const cdnModelUrl = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/models/hand-knn-model- 2.json';
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await loadKNNModelData(null, cdnModelUrl);
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updateStatus('模型加载成功！可以开始游戏了');
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isModelLoaded = true;
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startBtn.disabled = false;
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importModelBtn.disabled = true;
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} catch (cdnError) {
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console.warn('CDN 模型加载失败:', cdnError);
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updateStatus('CDN 模型加载失败，请手动导入模型');
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importModelBtn.disabled = false;
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}
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// // 尝试从 CDN 加载模型
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// try {
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// const cdnModelUrl = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/models/hand-knn-model-2.json';
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// await loadKNNModelData(null, cdnModelUrl);
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// updateStatus('模型加载成功！可以开始游戏了');
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// isModelLoaded = true;
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// startBtn.disabled = false;
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// importModelBtn.disabled = true;
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// } catch (cdnError) {
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// console.warn('CDN 模型加载失败:', cdnError);
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// updateStatus('CDN 模型加载失败，请手动导入模型');
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// importModelBtn.disabled = false;
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// }
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} catch (error) {
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console.error('初始化失败:', error);
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@ -573,20 +573,20 @@
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fileImporter.addEventListener('change', (event) => loadKNNModelData(event.target.files[0]));
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startStopBtn.addEventListener('click', togglePlaying);
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// 尝试从 CDN 加载模型
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try {
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const cdnJsonUrl = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/models/hand-knn-model.json';
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await loadKNNModelData(null, cdnJsonUrl);
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updateGlobalStatus('CDN 手势识别模型加载成功！');
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isModelLoaded = true;
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importModelBtn.disabled = true;
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startStopBtn.disabled = false;
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} catch (cdnError) {
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console.warn('CDN 模型加载失败:', cdnError);
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updateGlobalStatus('请手动导入模型文件');
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importModelBtn.disabled = false;
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startStopBtn.disabled = true;
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}
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// // 尝试从 CDN 加载模型
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// try {
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// const cdnJsonUrl = 'https://goood-space-assets.oss-cn-beijing.aliyuncs.com/public/models/hand-knn-model.json';
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// await loadKNNModelData(null, cdnJsonUrl);
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// updateGlobalStatus('CDN 手势识别模型加载成功！');
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// isModelLoaded = true;
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// importModelBtn.disabled = true;
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// startStopBtn.disabled = false;
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// } catch (cdnError) {
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// console.warn('CDN 模型加载失败:', cdnError);
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// updateGlobalStatus('请手动导入模型文件');
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// importModelBtn.disabled = false;
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// startStopBtn.disabled = true;
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// }
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} catch (error) {
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console.error('应用初始化失败:', error);
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8
game/钢琴/sounds/新建 文本文档.txt
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8
game/钢琴/sounds/新建 文本文档.txt
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@ -0,0 +1,8 @@
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<li><span class="note-id">ID 0:</span> 中央C (C2)</li>
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<li><span class="note-id">ID 1:</span> D2</li>
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<li><span class="note-id">ID 2:</span> E2</li>
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<li><span class="note-id">ID 3:</span> F2</li>
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<li><span class="note-id">ID 4:</span> G2</li>
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<li><span class="note-id">ID 5:</span> A2</li>
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<li><span class="note-id">ID 6:</span> B2</li>
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<li><span class="note-id">ID 7:</span> 高音C (C3)</li>
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@ -89,7 +89,8 @@
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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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// 'https://tfhub.dev/',
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'https://tfhub.dev/google/tfjs-model/movenet/singlepose/lightning/4/',
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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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@ -111,8 +112,8 @@
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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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// 匹配 model.json 或 group1-shardXof2.bin
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const fileNameMatch = url.match(/(model\.json|group1-shard\dof2\.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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@ -192,6 +193,7 @@
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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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@ -16,9 +16,8 @@
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// 定义需要被劫持的原始 URL 的域名模式
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// 我们观察到最终请求来自 storage.googleapis.com
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const INTERCEPT_DOMAINS = [
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'https://storage.googleapis.com/tfjs-models/', // tfjs 官方模型常用的 CDN
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'https://storage.googleapis.com/', // 更宽泛的匹配 Google Storage
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'https://tfhub.dev/', // 如果 MobileNet 也会通过 tfhub.dev 间接加载
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// 'https://tfhub.dev/', // 如果 MobileNet 也会通过 tfhub.dev 间接加载
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'https://tfhub.dev/google/imagenet/mobilenet_v2_100_224/classification/2/',
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];
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// 备份原始的 fetch 函数
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@ -38,7 +37,7 @@
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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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const fileNameMatch = url.match(/(model\.json|group1-shard\dof4\.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 = MOBILENET_MIRROR_BASE_URL + fileName; // 拼接新的镜像 URL
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@ -128,6 +127,8 @@
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})();
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</script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/mobilenet@latest"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/knn-classifier@latest"></script>
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@ -183,6 +183,7 @@
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</div>
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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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<!-- 如果你有其他模型的劫持代码，请确保它们都先于 TF.js 库 -->
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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 Speech Commands 模型文件
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@ -192,10 +193,8 @@
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// 定义需要被劫持的原始 URL 的域名模式
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// 明确指出是 tfjs-models 下的 speech-commands 模型
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const INTERCEPT_DOMAINS = [
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'https://storage.googleapis.com/tfjs-models/tfjs/speech-commands/',
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// 如果实际请求路径更短，也可以包含更宽泛的匹配
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// 'https://storage.googleapis.com/tfjs-models/',
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// 'https://storage.googleapis.com/',
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// 'https://storage.googleapis.com/tfjs-models/tfjs/speech-commands/',
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'https://storage.googleapis.com/tfjs-models/tfjs/speech-commands/v0.5/browser_fft/18w/',
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];
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// 备份原始的 fetch 函数
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@ -215,7 +214,7 @@
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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 metadata.json, model.json, group1-shardXofY (注意这里没有.bin后缀)
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const fileNameMatch = url.match(/(metadata\.json|model\.json|group1-shard\dof\d)/);
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const fileNameMatch = url.match(/(metadata\.json|model\.json|group1-shard\dof2)/);
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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 = SPEECH_COMMANDS_MIRROR_BASE_URL + fileName; // 拼接新的镜像 URL
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@ -299,6 +298,7 @@
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})();
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</script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest/dist/tf.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/speech-commands@latest/dist/speech-commands.min.js"></script>
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