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ibelem commited on Sep 19, 2025

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README.md +8 -0
assets/index-D77ZMihC.css +1 -0
assets/index-Dcc8IGX5.js +0 -0
assets/ort-wasm-simd-threaded.jsep-B0T3yYHD.wasm +3 -0
index.html +78 -0
src/index.html +78 -0
src/main.js +383 -0
src/package-lock.json +2012 -0
src/package.json +18 -0
src/style.css +104 -0
src/vite.config.js +7 -0

README.md ADDED Viewed

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+---
+title: WebNN Video Object Detection
+emoji: 💻
+colorFrom: blue
+colorTo: pink
+sdk: static
+pinned: false
+---

assets/index-D77ZMihC.css ADDED Viewed

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+ *{box-sizing:border-box;padding:0;margin:0;font-family:sans-serif}html,body{height:100%}body{padding:16px 32px}body,#container{display:flex;flex-direction:column;justify-content:center;align-items:center}#controls{display:flex;padding:1rem;gap:1rem}#controls>div{text-align:center}h1,h4{text-align:center}h4{margin-top:.5rem}#container{position:relative;width:540px;height:405px;max-width:100%;max-height:100%;border:2px dashed #d1d5db;border-radius:.75rem;overflow:hidden;margin-top:1rem;background-size:100% 100%;background-position:center;background-repeat:no-repeat}#overlay,canvas{position:absolute;width:100%;height:100%}#status{min-height:16px;margin:8px 0}.bounding-box{position:absolute;box-sizing:border-box;border:solid 2px}.bounding-box-label{color:#fff;position:absolute;font-size:12px;margin:-16px 0 0 -2px;padding:1px}#size-container,#scale-container{display:none}a{color:#275efe;text-decoration:none}a:hover{text-decoration:underline}#versions{margin-top:.5rem;font-size:.8rem;color:#0000004d}

assets/index-Dcc8IGX5.js ADDED Viewed

The diff for this file is too large to render. See raw diff

assets/ort-wasm-simd-threaded.jsep-B0T3yYHD.wasm ADDED Viewed

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c46655e8a94afc45338d4cb2b840475f88e5012d524509916e505079c00bfa39
+size 21596019

index.html ADDED Viewed

	@@ -0,0 +1,78 @@

+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Transformers.js | Real-time object detection</title>
+    <script type="module" crossorigin src="/assets/index-Dcc8IGX5.js"></script>
+    <link rel="stylesheet" crossorigin href="/assets/index-D77ZMihC.css">
+  </head>
+  <body>
+    <h1>
+      Real-time object detection w/ YOLO12n
+    </h1>
+    <h4>
+      Runs locally in your browser, powered by
+      <a href="http://github.com/huggingface/transformers.js" target="_blank"
+        >🤗 Transformers.js</a
+      > x <label id="device"></label>
+    </h4>
+    <div id="container">
+      <video id="video" autoplay muted playsinline></video>
+      <canvas id="canvas" width="360" height="240"></canvas>
+      <div id="overlay"></div>
+    </div>
+    <div id="controls">
+      <div id="size-container">
+        <label>Image size</label>
+        (<label id="size-value">640</label>)
+        <br />
+        <input
+          id="size"
+          type="range"
+          min="640"
+          max="640"
+          step="32"
+          value="640"
+          disabled
+        />
+      </div>
+      <div>
+        <label>Threshold</label>
+        (<label id="threshold-value">0.25</label>)
+        <br />
+        <input
+          id="threshold"
+          type="range"
+          min="0.01"
+          max="1"
+          step="0.01"
+          value="0.25"
+          disabled
+        />
+      </div>
+      <div id="scale-container">
+        <label>Scale</label>
+        (<label id="scale-value">1</label>)
+        <br />
+        <input
+          id="scale"
+          type="range"
+          min="1"
+          max="1"
+          step="0.01"
+          value="1"
+          disabled
+        />
+      </div>
+    </div>
+    <label id="status"></label>
+    <div>
+      <a href="?device=webnn-gpu">WebNN GPU</a> · <a href="?device=webnn-npu">WebNN NPU</a>
+    </div>
+    <div id="versions">
+      @huggingface/transformers: 3.7.3 · onnxruntime-web: 1.22.0-dev.20250409-89f8206ba4
+    </div>
+  </body>
+</html>

src/index.html ADDED Viewed

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+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Transformers.js | Real-time object detection</title>
+    <link rel="stylesheet" href="/style.css" />
+  </head>
+  <body>
+    <h1>
+      Real-time object detection w/ YOLO12n
+    </h1>
+    <h4>
+      Runs locally in your browser, powered by
+      <a href="http://github.com/huggingface/transformers.js" target="_blank"
+        >🤗 Transformers.js</a
+      > x <label id="device"></label>
+    </h4>
+    <div id="container">
+      <video id="video" autoplay muted playsinline></video>
+      <canvas id="canvas" width="360" height="240"></canvas>
+      <div id="overlay"></div>
+    </div>
+    <div id="controls">
+      <div id="size-container">
+        <label>Image size</label>
+        (<label id="size-value">640</label>)
+        <br />
+        <input
+          id="size"
+          type="range"
+          min="640"
+          max="640"
+          step="32"
+          value="640"
+          disabled
+        />
+      </div>
+      <div>
+        <label>Threshold</label>
+        (<label id="threshold-value">0.25</label>)
+        <br />
+        <input
+          id="threshold"
+          type="range"
+          min="0.01"
+          max="1"
+          step="0.01"
+          value="0.25"
+          disabled
+        />
+      </div>
+      <div id="scale-container">
+        <label>Scale</label>
+        (<label id="scale-value">1</label>)
+        <br />
+        <input
+          id="scale"
+          type="range"
+          min="1"
+          max="1"
+          step="0.01"
+          value="1"
+          disabled
+        />
+      </div>
+    </div>
+    <label id="status"></label>
+    <div>
+      <a href="?device=webnn-gpu">WebNN GPU</a> · <a href="?device=webnn-npu">WebNN NPU</a>
+    </div>
+    <div id="versions">
+      @huggingface/transformers: 3.7.3 · onnxruntime-web: 1.22.0-dev.20250409-89f8206ba4
+    </div>
+    <script type="module" src="/main.js"></script>
+  </body>
+</html>

src/main.js ADDED Viewed

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+import { AutoModel, AutoProcessor, RawImage } from "@huggingface/transformers";
+// Reference the elements that we will need
+const deviceLabel = document.getElementById("device");
+const status = document.getElementById("status");
+const container = document.getElementById("container");
+const overlay = document.getElementById("overlay");
+const canvas = document.getElementById("canvas");
+const video = document.getElementById("video");
+const thresholdSlider = document.getElementById("threshold");
+const thresholdLabel = document.getElementById("threshold-value");
+const sizeSlider = document.getElementById("size");
+const sizeLabel = document.getElementById("size-value");
+const scaleSlider = document.getElementById("scale");
+const scaleLabel = document.getElementById("scale-value");
+function setStreamSize(width, height) {
+  video.width = canvas.width = Math.round(width);
+  video.height = canvas.height = Math.round(height);
+  // Make sure overlay matches canvas exactly
+  overlay.style.width = `${canvas.width}px`;
+  overlay.style.height = `${canvas.height}px`;
+}
+status.textContent = "Loading model...";
+function getDeviceConfig(deviceParam, dtypeParam) {
+  const defaultDevice = 'webnn-gpu';
+  const defaultDtype = 'fp16';
+  const webnnDevices = ['webnn-gpu', 'webnn-cpu', 'webnn-npu'];
+  const supportedDtypes = ['fp16', 'fp32', 'int8'];
+  const device = (deviceParam || defaultDevice).toLowerCase();
+  const dtype = (dtypeParam && supportedDtypes.includes(dtypeParam.toLowerCase()))
+    ? dtypeParam.toLowerCase()
+    : (webnnDevices.includes(device) ? defaultDtype : 'fp32');
+  const sessionOptions = { logSeverityLevel: 0 };
+  return { device, dtype, sessionOptions };
+}
+const urlParams = new URLSearchParams(window.location.search);
+let { device, dtype, sessionOptions } = getDeviceConfig(urlParams.get('device'), urlParams.get('dtype'));
+let deviceValue = 'WebNN GPU';
+switch (device) {
+  case 'webgpu':
+    deviceValue = 'WebGPU';
+    break;
+  case 'webnn-gpu':
+    deviceValue = 'WebNN GPU';
+    break;
+  case 'webnn-cpu':
+    deviceValue = 'WebNN CPU';
+    break;
+  case 'webnn-npu':
+    deviceValue = 'WebNN NPU';
+    break;
+  default:
+    deviceValue = 'WebNN GPU';
+}
+deviceLabel.textContent = deviceValue;
+if (!['webgpu', 'webnn-gpu', 'webnn-cpu', 'webnn-npu'].includes(device)) {
+  status.textContent = `Unsupported device ${device}. Falling back to WebNN GPU.`;
+  device = 'webnn-gpu';
+}
+// Load model and processor
+const model_id = "webnn/yolo12n";
+let model, processor;
+try {
+  status.textContent = "Loading model...";
+  model = await AutoModel.from_pretrained(model_id, {
+    device: device,
+    dtype: dtype,
+    session_options: sessionOptions
+  });
+  processor = await AutoProcessor.from_pretrained(model_id);
+  // Configure processor to match model's expected input size (640x640)
+  processor.feature_extractor.size = { width: 640, height: 640 };
+  status.textContent = "Model loaded successfully!";
+} catch (err) {
+  console.error(err);
+  let errorMessage = `Error: ${err.message}`;
+  status.textContent = errorMessage;
+  status.style.color = "red";
+  // Stop execution
+  throw err;
+}
+// Set up controls
+let scale = 1;
+scaleSlider.addEventListener("input", () => {
+  scale = Number(scaleSlider.value);
+  setStreamSize(video.videoWidth * scale, video.videoHeight * scale);
+  scaleLabel.textContent = scale;
+});
+scaleSlider.disabled = false;
+let threshold = 0.25;
+thresholdSlider.addEventListener("input", () => {
+  threshold = Number(thresholdSlider.value);
+  thresholdLabel.textContent = threshold.toFixed(2);
+});
+thresholdSlider.disabled = false;
+let size = 640;
+sizeSlider.addEventListener("input", () => {
+  size = Number(sizeSlider.value);
+  processor.feature_extractor.size = { width: size, height: size };
+  sizeLabel.textContent = size;
+});
+sizeSlider.disabled = false;
+status.textContent = "Ready";
+const COLOURS = [
+  "#EF4444",
+  "#4299E1",
+  "#059669",
+  "#FBBF24",
+  "#4B52B1",
+  "#7B3AC2",
+  "#ED507A",
+  "#1DD1A1",
+  "#F3873A",
+  "#4B5563",
+  "#DC2626",
+  "#1852B4",
+  "#18A35D",
+  "#F59E0B",
+  "#4059BE",
+  "#6027A5",
+  "#D63D60",
+  "#00AC9B",
+  "#E64A19",
+  "#272A34",
+];
+// Render a bounding box and label on the image
+function renderBox(detection, canvasWidth, canvasHeight) {
+  const { bbox, score, class: classId } = detection;
+  if (score < threshold) return; // Skip boxes with low confidence
+  const [x, y, width, height] = bbox;
+  const color = COLOURS[classId % COLOURS.length];
+  // Ensure coordinates are within bounds
+  const clampedX = Math.max(0, Math.min(x, canvasWidth - width));
+  const clampedY = Math.max(0, Math.min(y, canvasHeight - height));
+  const clampedWidth = Math.max(1, Math.min(width, canvasWidth - clampedX));
+  const clampedHeight = Math.max(1, Math.min(height, canvasHeight - clampedY));
+  // Draw the box
+  const boxElement = document.createElement("div");
+  boxElement.className = "bounding-box";
+  Object.assign(boxElement.style, {
+    position: "absolute",
+    left: `${clampedX}px`,
+    top: `${clampedY}px`,
+    width: `${clampedWidth}px`,
+    height: `${clampedHeight}px`,
+    border: `2px solid ${color}`,
+    backgroundColor: "transparent",
+    pointerEvents: "none",
+    boxSizing: "border-box"
+  });
+  // Draw label
+  const labelElement = document.createElement("span");
+  labelElement.textContent = `${model.config.id2label[classId]} (${(100 * score).toFixed(1)}%)`;
+  labelElement.className = "bounding-box-label";
+  Object.assign(labelElement.style, {
+    backgroundColor: color,
+    color: "white",
+    padding: "2px 6px",
+    fontSize: "12px",
+    position: "absolute",
+    top: "-22px",
+    left: "0px",
+    whiteSpace: "nowrap",
+    borderRadius: "2px"
+  });
+  boxElement.appendChild(labelElement);
+  overlay.appendChild(boxElement);
+}
+function calculateIoU(boxA, boxB) {
+  const [xA, yA, wA, hA] = boxA;
+  const [xB, yB, wB, hB] = boxB;
+  const x1 = Math.max(xA, xB);
+  const y1 = Math.max(yA, yB);
+  const x2 = Math.min(xA + wA, xB + wB);
+  const y2 = Math.min(yA + hA, yB + hB);
+  const intersection = Math.max(0, x2 - x1) * Math.max(0, y2 - y1);
+  const areaA = wA * hA;
+  const areaB = wB * hB;
+  const union = areaA + areaB - intersection;
+  return intersection / union;
+}
+function applyNMS(detections, iouThreshold = 0.5) {
+  // Sort detections by confidence score in descending order
+  detections.sort((a, b) => b.score - a.score);
+  const filteredDetections = [];
+  const used = new Array(detections.length).fill(false);
+  for (let i = 0; i < detections.length; i++) {
+    if (used[i]) continue;
+    const detectionA = detections[i];
+    filteredDetections.push(detectionA);
+    for (let j = i + 1; j < detections.length; j++) {
+      if (used[j]) continue;
+      const detectionB = detections[j];
+      // Only apply NMS to boxes of the same class
+      if (detectionA.class === detectionB.class) {
+        const iou = calculateIoU(detectionA.bbox, detectionB.bbox);
+        if (iou > iouThreshold) {
+          used[j] = true; // Suppress overlapping box
+        }
+      }
+    }
+  }
+  return filteredDetections;
+}
+function processDetections(outputs, canvasWidth, canvasHeight) {
+  // Clear previous detections
+  overlay.innerHTML = "";
+  // Process YOLOv12 outputs
+  const predictions = outputs.tolist()[0]; // Get the first batch
+  const numClasses = predictions.length - 4; // Subtract 4 for bbox coordinates
+  const numPredictions = predictions[0].length; // Number of predictions
+  let detections = [];
+  // Process each prediction
+  for (let i = 0; i < numPredictions; i++) {
+    const x = predictions[0][i]; // center x (0-640)
+    const y = predictions[1][i]; // center y (0-640)
+    const w = predictions[2][i]; // width (0-640)
+    const h = predictions[3][i]; // height (0-640)
+    let maxScore = 0;
+    let maxClassIndex = -1;
+    for (let c = 0; c < numClasses; c++) {
+      const score = predictions[c + 4][i];
+      if (score > maxScore) {
+        maxScore = score;
+        maxClassIndex = c;
+      }
+    }
+    if (maxScore < threshold) continue;
+    // Convert from center coordinates to top-left coordinates
+    // Scale from 640x640 model output to canvas dimensions
+    const scaleX = canvasWidth / 640;
+    const scaleY = canvasHeight / 640;
+    const centerX = x * scaleX;
+    const centerY = y * scaleY;
+    const boxWidth = w * scaleX;
+    const boxHeight = h * scaleY;
+    const xmin = centerX - (boxWidth / 2);
+    const ymin = centerY - (boxHeight / 2);
+    detections.push({
+      bbox: [xmin, ymin, boxWidth, boxHeight],
+      score: maxScore,
+      class: maxClassIndex,
+    });
+  }
+  // Apply Non-Maximum Suppression to remove duplicate detections
+  const filteredDetections = applyNMS(detections, 0.45); // Lower IoU threshold for better suppression
+  // Debug: Log detection info
+  if (filteredDetections.length > 0) {
+    console.log(`Found ${filteredDetections.length} detections:`,
+      filteredDetections.map(d => ({
+        class: model.config.id2label[d.class],
+        score: d.score.toFixed(3),
+        bbox: d.bbox.map(v => Math.round(v))
+      }))
+    );
+  }
+  // Render filtered detections
+  filteredDetections.forEach((detection) => {
+    renderBox(detection, canvasWidth, canvasHeight);
+  });
+  return filteredDetections.length;
+}
+let isProcessing = false;
+let previousTime;
+const context = canvas.getContext("2d", { willReadFrequently: true });
+function updateCanvas() {
+  const { width, height } = canvas;
+  context.drawImage(video, 0, 0, width, height);
+  if (!isProcessing) {
+    isProcessing = true;
+    (async function () {
+      try {
+        // Read the current frame from the video
+        const pixelData = context.getImageData(0, 0, width, height).data;
+        const image = new RawImage(pixelData, width, height, 4);
+        // Process the image and run the model
+        const inputs = await processor(image);
+        const { outputs } = await model(inputs);
+        // Process detections and render boxes
+        const detectionCount = processDetections(outputs, width, height);
+        if (previousTime !== undefined) {
+          const fps = 1000 / (performance.now() - previousTime);
+          status.textContent = `FPS: ${fps.toFixed(2)} | Detections: ${detectionCount}`;
+        }
+        previousTime = performance.now();
+      } catch (error) {
+        console.error("Detection error:", error);
+        status.textContent = `Error: ${error.message}`;
+      } finally {
+        isProcessing = false;
+      }
+    })();
+  }
+  window.requestAnimationFrame(updateCanvas);
+}
+// Start the video stream
+navigator.mediaDevices
+  .getUserMedia(
+    { video: true }, // Ask for video
+  )
+  .then((stream) => {
+    // Set up the video and canvas elements.
+    video.srcObject = stream;
+    video.play();
+    const videoTrack = stream.getVideoTracks()[0];
+    const { width, height } = videoTrack.getSettings();
+    setStreamSize(width * scale, height * scale);
+    // Set container width and height depending on the image aspect ratio
+    const ar = width / height;
+    const [cw, ch] = ar > 720 / 405 ? [720, 720 / ar] : [405 * ar, 405];
+    container.style.width = `${cw}px`;
+    container.style.height = `${ch}px`;
+    // Start the animation loop
+    window.requestAnimationFrame(updateCanvas);
+  })
+  .catch((error) => {
+    alert(error);
+  });

src/package-lock.json ADDED Viewed

	@@ -0,0 +1,2012 @@

+{
+  "name": "video-object-detection",
+  "version": "0.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "video-object-detection",
+      "version": "0.0.0",
+      "dependencies": {
+        "@huggingface/transformers": "3.7.1",
+        "onnxruntime-node": "^1.21.0"
+      },
+      "devDependencies": {
+        "vite": "^7.1.6"
+      }
+    },
+    "node_modules/@emnapi/runtime": {
+      "version": "1.4.3",
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+      "integrity": "sha512-SRYIB8t/isTwNn8vMB3MR6E+EQZM/WG1aKmmIUCfDXfVvKfc20ZpamngWHKzAmmu9ppsgxsg4b2I7c90JZudIQ==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "esbuild": "^0.25.0",
+        "fdir": "^6.5.0",
+        "picomatch": "^4.0.3",
+        "postcss": "^8.5.6",
+        "rollup": "^4.43.0",
+        "tinyglobby": "^0.2.15"
+      },
+      "bin": {
+        "vite": "bin/vite.js"
+      },
+      "engines": {
+        "node": "^20.19.0 || >=22.12.0"
+      },
+      "funding": {
+        "url": "https://github.com/vitejs/vite?sponsor=1"
+      },
+      "optionalDependencies": {
+        "fsevents": "~2.3.3"
+      },
+      "peerDependencies": {
+        "@types/node": "^20.19.0 || >=22.12.0",
+        "jiti": ">=1.21.0",
+        "less": "^4.0.0",
+        "lightningcss": "^1.21.0",
+        "sass": "^1.70.0",
+        "sass-embedded": "^1.70.0",
+        "stylus": ">=0.54.8",
+        "sugarss": "^5.0.0",
+        "terser": "^5.16.0",
+        "tsx": "^4.8.1",
+        "yaml": "^2.4.2"
+      },
+      "peerDependenciesMeta": {
+        "@types/node": {
+          "optional": true
+        },
+        "jiti": {
+          "optional": true
+        },
+        "less": {
+          "optional": true
+        },
+        "lightningcss": {
+          "optional": true
+        },
+        "sass": {
+          "optional": true
+        },
+        "sass-embedded": {
+          "optional": true
+        },
+        "stylus": {
+          "optional": true
+        },
+        "sugarss": {
+          "optional": true
+        },
+        "terser": {
+          "optional": true
+        },
+        "tsx": {
+          "optional": true
+        },
+        "yaml": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/yallist": {
+      "version": "5.0.0",
+      "resolved": "https://registry.npmjs.org/yallist/-/yallist-5.0.0.tgz",
+      "integrity": "sha512-YgvUTfwqyc7UXVMrB+SImsVYSmTS8X/tSrtdNZMImM+n7+QTriRXyXim0mBrTXNeqzVF0KWGgHPeiyViFFrNDw==",
+      "license": "BlueOak-1.0.0",
+      "engines": {
+        "node": ">=18"
+      }
+    }
+  }
+}

src/package.json ADDED Viewed

	@@ -0,0 +1,18 @@

+{
+  "name": "video-object-detection",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview"
+  },
+  "devDependencies": {
+    "vite": "^7.1.6"
+  },
+  "dependencies": {
+    "@huggingface/transformers": "3.7.1",
+    "onnxruntime-node": "^1.21.0"
+  }
+}

src/style.css ADDED Viewed

	@@ -0,0 +1,104 @@

+* {
+  box-sizing: border-box;
+  padding: 0;
+  margin: 0;
+  font-family: sans-serif;
+}
+html,
+body {
+  height: 100%;
+}
+body {
+  padding: 16px 32px;
+}
+body,
+#container {
+  display: flex;
+  flex-direction: column;
+  justify-content: center;
+  align-items: center;
+}
+#controls {
+  display: flex;
+  padding: 1rem;
+  gap: 1rem;
+}
+#controls > div {
+  text-align: center;
+}
+h1,
+h4 {
+  text-align: center;
+}
+h4 {
+  margin-top: 0.5rem;
+}
+#container {
+  position: relative;
+  width: 540px;
+  height: 405px;
+  max-width: 100%;
+  max-height: 100%;
+  border: 2px dashed #d1d5db;
+  border-radius: 0.75rem;
+  overflow: hidden;
+  margin-top: 1rem;
+  background-size: 100% 100%;
+  background-position: center;
+  background-repeat: no-repeat;
+}
+#overlay,
+canvas {
+  position: absolute;
+  width: 100%;
+  height: 100%;
+}
+#status {
+  min-height: 16px;
+  margin: 8px 0;
+}
+.bounding-box {
+  position: absolute;
+  box-sizing: border-box;
+  border: solid 2px;
+}
+.bounding-box-label {
+  color: white;
+  position: absolute;
+  font-size: 12px;
+  margin: -16px 0 0 -2px;
+  padding: 1px;
+}
+#size-container, #scale-container {
+  display: none;
+}
+a {
+  color: rgba(39, 94, 254, 1);
+  text-decoration: none;
+}
+a:hover {
+  text-decoration: underline;
+}
+#versions {
+  margin-top: 0.5rem;
+  font-size: 0.8rem;
+  color: rgba(0, 0, 0, 0.3);
+}

src/vite.config.js ADDED Viewed

	@@ -0,0 +1,7 @@

+import { defineConfig } from "vite";
+export default defineConfig({
+  build: {
+    target: "esnext",
+    outDir: '../',
+  }
+});