Spaces:

webnn
/

depth-estimation-video

Running

+ *{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,h3{text-align:center}h3{margin-top:.5rem}#container{display:flex;flex-direction:row;position:relative;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}#video,#output-canvas{width:504px;height:504px}canvas{width:100%;height:100%}#status{min-height:16px;margin:8px 0}#size-container{display:none}a{color:#275efe;text-decoration:none}a:hover{text-decoration:underline}#versions{margin-top:.5rem;font-size:.8rem;color:#0000004d}

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 +1,70 @@

+<!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 depth estimation</title>
+    <script type="module" crossorigin src="/assets/index-15ZN9feD.js"></script>
+    <link rel="stylesheet" crossorigin href="/assets/index-CrhkE7SZ.css">
+  </head>
+  <body>
+    <h1>
+      Real-time depth estimation w/
+      <a
+        href="https://huggingface.co/onnx-community/depth-anything-v2-small"
+        target="_blank"
+        >Depth Anything V2</a
+      >
+    </h1>
+    <h3>
+      Runs locally in your browser, powered by
+      <a href="https://github.com/huggingface/transformers.js" target="_blank"
+        >🤗 Transformers.js</a
+      > x <label id="device"></label>
+    </h3>
+    <div id="container">
+      <video id="video" autoplay muted playsinline></video>
+      <canvas id="output-canvas"></canvas>
+    </div>
+    <div id="controls">
+      <div
+        title="Read frames from your webcam and process them at a lower size (lower = faster)"
+      >
+        <label>Stream scale</label>
+        (<label id="scale-value">0.4</label>)
+        <br />
+        <input
+          id="scale"
+          type="range"
+          min="0.1"
+          max="1"
+          step="0.1"
+          value="0.4"
+          disabled
+        />
+      </div>
+      <div id="size-container" title="The width of the image (lower = faster)">
+        <label>Image size</label>
+        (<label id="size-value">504</label>px)
+        <br />
+        <input
+          id="size"
+          type="range"
+          min="140"
+          max="840"
+          step="14"
+          value="504"
+          disabled
+        />
+      </div>
+    </div>
+    <label id="status">Loading model...</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

	@@ -0,0 +1,70 @@

+<!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 depth estimation</title>
+    <link rel="stylesheet" href="/style.css" />
+  </head>
+  <body>
+    <h1>
+      Real-time depth estimation w/
+      <a
+        href="https://huggingface.co/onnx-community/depth-anything-v2-small"
+        target="_blank"
+        >Depth Anything V2</a
+      >
+    </h1>
+    <h3>
+      Runs locally in your browser, powered by
+      <a href="https://github.com/huggingface/transformers.js" target="_blank"
+        >🤗 Transformers.js</a
+      > x <label id="device"></label>
+    </h3>
+    <div id="container">
+      <video id="video" autoplay muted playsinline></video>
+      <canvas id="output-canvas"></canvas>
+    </div>
+    <div id="controls">
+      <div
+        title="Read frames from your webcam and process them at a lower size (lower = faster)"
+      >
+        <label>Stream scale</label>
+        (<label id="scale-value">0.4</label>)
+        <br />
+        <input
+          id="scale"
+          type="range"
+          min="0.1"
+          max="1"
+          step="0.1"
+          value="0.4"
+          disabled
+        />
+      </div>
+      <div id="size-container" title="The width of the image (lower = faster)">
+        <label>Image size</label>
+        (<label id="size-value">504</label>px)
+        <br />
+        <input
+          id="size"
+          type="range"
+          min="140"
+          max="840"
+          step="14"
+          value="504"
+          disabled
+        />
+      </div>
+    </div>
+    <label id="status">Loading model...</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

	@@ -0,0 +1,201 @@

+import {
+  AutoModel,
+  AutoImageProcessor,
+  RawImage,
+} from "@huggingface/transformers";
+// Reference the elements that we will need
+const deviceLabel = document.getElementById("device");
+const status = document.getElementById("status");
+const canvas = document.createElement("canvas");
+const outputCanvas = document.getElementById("output-canvas");
+const video = document.getElementById("video");
+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 = outputCanvas.width = canvas.width = Math.round(width);
+  video.height = outputCanvas.height = canvas.height = Math.round(height);
+}
+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 FREE_DIMENSION_HEIGHT = 504;
+  const FREE_DIMENSION_WIDTH = 504;
+  const sessionOptions = webnnDevices.includes(device)
+    ? {
+        freeDimensionOverrides: {
+          batch_size: 1,
+          height: FREE_DIMENSION_HEIGHT,
+          width: FREE_DIMENSION_WIDTH,
+        },
+        logSeverityLevel: 0
+      }
+    : {
+      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 = "onnx-community/depth-anything-v2-small";
+let model;
+try {
+  model = await AutoModel.from_pretrained(model_id, {
+    device: device,
+    dtype: dtype,
+    session_options: sessionOptions
+  });
+} catch (err) {
+  status.textContent = err.message;
+  alert(err.message);
+  throw err;
+}
+const processor = await AutoImageProcessor.from_pretrained(model_id);
+// Set up controls
+let size = 504;
+processor.size = { width: size, height: size };
+sizeSlider.addEventListener("input", () => {
+  size = Number(sizeSlider.value);
+  processor.size = { width: size, height: size };
+  sizeLabel.textContent = size;
+});
+sizeSlider.disabled = false;
+let scale = 0.4;
+scaleSlider.addEventListener("input", () => {
+  scale = Number(scaleSlider.value);
+  setStreamSize(video.videoWidth * scale, video.videoHeight * scale);
+  scaleLabel.textContent = scale;
+});
+scaleSlider.disabled = false;
+status.textContent = "Ready";
+let isProcessing = false;
+let previousTime;
+const context = canvas.getContext("2d", { willReadFrequently: true });
+const outputContext = outputCanvas.getContext("2d", {
+  willReadFrequently: true,
+});
+function updateCanvas() {
+  const { width, height } = canvas;
+  if (!isProcessing) {
+    isProcessing = true;
+    (async function () {
+      // Read the current frame from the video
+      context.drawImage(video, 0, 0, width, height);
+      const currentFrame = context.getImageData(0, 0, width, height);
+      const image = new RawImage(currentFrame.data, width, height, 4);
+      // Pre-process image
+      const inputs = await processor(image);
+      // Predict depth map
+      const { predicted_depth } = await model(inputs);
+      const data = predicted_depth.data;
+      const [bs, oh, ow] = predicted_depth.dims;
+      // Normalize the depth map
+      let min = Infinity;
+      let max = -Infinity;
+      outputCanvas.width = ow;
+      outputCanvas.height = oh;
+      for (let i = 0; i < data.length; ++i) {
+        const v = data[i];
+        if (v < min) min = v;
+        if (v > max) max = v;
+      }
+      const range = max - min;
+      const imageData = new Uint8ClampedArray(4 * data.length);
+      for (let i = 0; i < data.length; ++i) {
+        const offset = 4 * i;
+        imageData[offset] = 255; // Set base color to red
+        // Set alpha to normalized depth value
+        imageData[offset + 3] = 255 * (1 - (data[i] - min) / range);
+      }
+      const outPixelData = new ImageData(imageData, ow, oh);
+      outputContext.putImageData(outPixelData, 0, 0);
+      if (previousTime !== undefined) {
+        const fps = 1000 / (performance.now() - previousTime);
+        status.textContent = `FPS: ${fps.toFixed(2)}`;
+      }
+      previousTime = performance.now();
+      isProcessing = false;
+    })();
+  }
+  window.requestAnimationFrame(updateCanvas);
+}
+// Start the video stream
+navigator.mediaDevices
+  .getUserMedia(
+    { video: { width: 720, height: 720 } }, // Ask for square 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);
+    // Start the animation loop
+    setTimeout(updateCanvas, 50);
+  })
+  .catch((error) => {
+    alert(error);
+  });

src/package-lock.json ADDED Viewed

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

+{
+  "name": "depth-estimation-video",
+  "version": "0.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "depth-estimation-video",
+      "version": "0.0.0",
+      "dependencies": {
+        "@huggingface/transformers": "3.7.3",
+        "onnxruntime-node": "^1.21.0"
+      },
+      "devDependencies": {
+        "vite": "^7.1.6"
+      }
+    },
+    "node_modules/@emnapi/runtime": {
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+      "license": "BlueOak-1.0.0",
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+}

src/package.json ADDED Viewed

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

+{
+  "name": "depth-estimation-video",
+  "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": "3.7.3",
+    "onnxruntime-node": "^1.21.0"
+  }
+}

src/style.css ADDED Viewed

	@@ -0,0 +1,91 @@

+* {
+  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,
+h3 {
+  text-align: center;
+}
+h3 {
+  margin-top: 0.5rem;
+}
+#container {
+  display: flex;
+  flex-direction: row;
+  position: relative;
+  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;
+}
+#video,
+#output-canvas {
+  width: 504px;
+  height: 504px;
+}
+canvas {
+  width: 100%;
+  height: 100%;
+}
+#status {
+  min-height: 16px;
+  margin: 8px 0;
+}
+#size-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: '../',
+  },
+});