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//load the candle yolo wasm module
import init, { Model, ModelPose } from "./build/m.js";
async function fetchArrayBuffer(url) {
const cacheName = "yolo-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
if (cachedResponse) {
const data = await cachedResponse.arrayBuffer();
return new Uint8Array(data);
}
const res = await fetch(url, { cache: "force-cache" });
cache.put(url, res.clone());
return new Uint8Array(await res.arrayBuffer());
}
class Yolo {
static instance = {};
// Retrieve the YOLO model. When called for the first time,
// this will load the model and save it for future use.
static async getInstance(modelID, modelURL, modelSize) {
// load individual modelID only once
if (!this.instance[modelID]) {
await init();
self.postMessage({ status: `loading model ${modelID}:${modelSize}` });
const weightsArrayU8 = await fetchArrayBuffer(modelURL);
if (/pose/.test(modelID)) {
// if pose model, use ModelPose
this.instance[modelID] = new ModelPose(weightsArrayU8, modelSize);
} else {
this.instance[modelID] = new Model(weightsArrayU8, modelSize);
}
} else {
self.postMessage({ status: "model already loaded" });
}
return this.instance[modelID];
}
}
self.addEventListener("message", async (event) => {
const { imageURL, modelID, modelURL, modelSize, confidence, iou_threshold } =
event.data;
try {
self.postMessage({ status: "detecting" });
const yolo = await Yolo.getInstance(modelID, modelURL, modelSize);
self.postMessage({ status: "loading image" });
const imgRes = await fetch(imageURL);
const imgData = await imgRes.arrayBuffer();
const imageArrayU8 = new Uint8Array(imgData);
self.postMessage({ status: `running inference ${modelID}:${modelSize}` });
const bboxes = yolo.run(imageArrayU8, confidence, iou_threshold);
// Send the output back to the main thread as JSON
self.postMessage({
status: "complete",
output: JSON.parse(bboxes),
});
} catch (e) {
self.postMessage({ error: e });
}
});
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