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StarPilot/tinygrad_repo/examples/webgpu/efficientnet/index.html
T
firestar5683 22a8575199 Vendor dependencies and resources for standalone builds
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
2026-10-03 21:01:18 +00:00

124 lines
3.9 KiB
HTML

<html>
<head>
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<style>
#result { font-size: 48px; }
#time { font-size: 16px; color: grey; }
#mybox { padding: 20px; }
#resultbox { padding: 50px; }
.bigggg { font-size: 18px; margin-top: 10px; }
.bigg { font-size: 18px; }
#url { font-size: 18px; width: 70%; }
a { text-decoration: none; }
h1 { padding: 50px; padding-bottom: 0px; font-size: 36px; font-weight: normal; }
#imagebox { height:224px; width:224px; border: 1px dotted black; }
#video { height:0px; width:0px; border: 1px dotted black; object-fit: cover;}
canvas { display: none; }
* { text-align: center; font-family: monospace; }
</style>
<title>tinygrad has WebGPU</title>
<link rel="icon" type="image/x-icon" href="https://raw.githubusercontent.com/tinygrad/tinygrad/master/docs/logo.png">
</head>
<body>
<h1>WebGPU <a href="https://github.com/geohot/tinygrad">tinygrad</a> EfficientNet!</h1>
<div id="mybox">
<input type="text" id="url" placeholder="put url here" value="https://upload.wikimedia.org/wikipedia/commons/d/da/Norwegian_hen.jpg">
<input class="bigg" type="button" onclick="runNetWResource(document.getElementById('url').value)" value="Use URL">
</div>
<br/>
<img id="imagebox"></img>
<canvas id="canvas" width="200" height="200"> </canvas>
<div id="resultbox">
<div id="result">result will go here</div>
<div id="time"></div>
</div>
<script>
const ctx = document.getElementById("canvas").getContext("2d", { willReadFrequently: true });
const resultText = document.getElementById('result');
let labels, net;
const error = (err) => {
resultText.innerHTML = `Error: ${err}`;
throw new Error(err);
}
const getDevice = async () => {
if (!navigator.gpu) error("WebGPU not supported.");
const adapter = await navigator.gpu.requestAdapter();
return await adapter.requestDevice({
requiredFeatures: ["shader-f16"],
powerPreference: "high-performance"
});
};
const timer = async (func, label = "") => {
document.getElementById('time').innerHTML = "";
const start = performance.now();
const out = await func();
const delta = (performance.now() - start).toFixed(1)
console.log(`${delta} ms ${label}`);
document.getElementById('time').innerHTML = `${delta} ms ${label}`;
return out;
}
const getLabels = async () => (await fetch("https://raw.githubusercontent.com/anishathalye/imagenet-simple-labels/master/imagenet-simple-labels.json")).json();
const reorderChannelsAndRemoveAlpha = (data) => {
const out = [];
let i = 0;
for (let c = 0; c < 3; c++) {
for (let x = 0; x < 224 * 224; x++) {
out[i] = data[x * 4 + c];
i++;
}
}
return out;
};
const runNetWResource = async (resource) => {
resultText.innerHTML = "pending..."
if (resource == "") error("sir. please type in a URL");
const response = await fetch(resource)
if (!response.ok) error("sir. that is not a good URL. try a new one");
document.getElementById("imagebox").src = resource
const img = new Image();
img.crossOrigin = "Anonymous";
img.onload = () => {
URL.revokeObjectURL(img.src);
ctx.drawImage(img, 0, 0, 224, 224);
const data = ctx.getImageData(0, 0, 224, 224).data;
runNet(data)
};
img.src = resource;
}
const loadLet = async () => {
try {
resultText.innerHTML = "loading..."
labels = await getLabels();
const device = await getDevice();
const model = (await import("../../net.js")).default;
net = await timer(() => model.load(device, '../../net.safetensors'), "(compilation)");
resultText.innerHTML = "ready"
} catch (e) {
error(e)
}
}
const runNet = async (data) => {
if (!net) error("Net not loaded yet.");
const input = reorderChannelsAndRemoveAlpha(Array.from(data).map((pix) => (pix / 255.0) * 0.45 - 0.225));
const out = await timer(() => net(new Float32Array(input)));
const arr = Array.from(new Float32Array(out[0]));
const index = arr.indexOf(Math.max(...arr));
resultText.textContent = labels[index];
};
loadLet();
</script>
</body>
</html>