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| //load the candle yolo wasm module | |
| import init, { Model, ModelPose } from "./build/m.js"; | |
| 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 modelRes = await fetch(modelURL); | |
| const yoloArrayBuffer = await modelRes.arrayBuffer(); | |
| const weightsArrayU8 = new Uint8Array(yoloArrayBuffer); | |
| 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 }); | |
| } | |
| }); | |