| |
| 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 = {}; |
| |
| |
| static async getInstance(modelID, modelURL, modelSize) { |
| |
| if (!this.instance[modelID]) { |
| await init(); |
|
|
| self.postMessage({ status: `loading model ${modelID}:${modelSize}` }); |
| const weightsArrayU8 = await fetchArrayBuffer(modelURL); |
| if (/pose/.test(modelID)) { |
| |
| 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); |
|
|
| |
| self.postMessage({ |
| status: "complete", |
| output: JSON.parse(bboxes), |
| }); |
| } catch (e) { |
| self.postMessage({ error: e }); |
| } |
| }); |