Spaces:
Running
Running
| ; | |
| importScripts('./vendor/ort.wasm.min.js', './detection-core.js'); | |
| ort.env.wasm.numThreads = 1; // Works inside HF frames without cross-origin isolation. | |
| ort.env.wasm.proxy = false; | |
| ort.env.wasm.wasmPaths = new URL('./vendor/', self.location.href).href; | |
| let currentSession; | |
| let currentPath; | |
| let running = false; | |
| self.onmessage = async ({ data }) => { | |
| if (running) { | |
| self.postMessage({ requestId: data.requestId, error: 'A comparison is already running on this device.' }); | |
| return; | |
| } | |
| running = true; | |
| const { requestId, model, size, input, transform, confidence } = data; | |
| try { | |
| // Keep model versions in the URL, not the filename. | |
| const modelUrl = new URL(model.files[String(size)], self.location.href); | |
| if (model.checkpoint_sha256) { | |
| modelUrl.searchParams.set('v', model.checkpoint_sha256.slice(0, 12)); | |
| } | |
| const path = modelUrl.href; | |
| if (!currentSession || currentPath !== path) { | |
| self.postMessage({ requestId, stage: 'Downloading/loading ' + model.label + ' on your device…' }); | |
| if (currentSession) await currentSession.release(); | |
| currentSession = null; | |
| currentPath = null; | |
| currentSession = await ort.InferenceSession.create(path, { | |
| executionProviders: ['wasm'], graphOptimizationLevel: 'all', | |
| }); | |
| currentPath = path; | |
| } | |
| self.postMessage({ requestId, stage: 'Running ' + model.label + ' on your device…' }); | |
| const tensor = new ort.Tensor('float32', new Float32Array(input), [1, 3, size, size]); | |
| const outputs = await currentSession.run({ [currentSession.inputNames[0]]: tensor }); | |
| const output = outputs[currentSession.outputNames[0]]; | |
| const detections = PaddyDetectionCore.decode(output, model.names, transform, confidence); | |
| tensor.dispose(); | |
| for (const value of Object.values(outputs)) value.dispose(); | |
| self.postMessage({ requestId, detections }); | |
| } catch (error) { | |
| self.postMessage({ requestId, error: model.label + ': ' + error.message }); | |
| } finally { | |
| running = false; | |
| } | |
| }; | |