ONNX Model

loadOnnxModel

// Return example
"onnx_8k3j2h9s1d4f6"

// Load ONNX model
const onnxId = await apiInvoke('loadOnnxModel', {
    file: 'C:\\models\\yolov5s.onnx'
});

console.log('Model loaded successfully, ID:', onnxId);
// Output: Model loaded successfully, ID: onnx_8k3j2h9s1d4f6

unloadOnnxModel

// Load model first
const onnxid = await apiInvoke('loadOnnxModel', {
    file: 'C:\\models\\yolov8s.onnx'
});

// Use model for inference...
...

// Unload model after use
await apiInvoke('unloadOnnxModel', {
    onnxid: onnxid
});

console.log('Model unloaded');

predictOnnxModel

// Typical return format for YOLO object detection model
[
    {
        "classId": 0,
        "x": 100,
        "y": 200,
        "confidence": 0.95,
        "boundingBox": { ... }  // [x, y, width, height]
    },
    {
        "classId": 1,
        "x": 100,
        "y": 200,
        "confidence": 0.87,
        "boundingBox": { ... }
    }
]

// 1. Load model
const onnxid = await apiInvoke('loadOnnxModel', {
    file: 'C:\\models\\yolov5s.onnx'
});

// 2. Perform inference
const result = await apiInvoke('predictOnnxModel', {
    onnxid: onnxid,
    deviceId: 'P72578581E07'
});

console.log('Detection results:', result);