Raw model output as Float32Array
Original image dimensions for resizing
Model output shape [batch, channels, height, width] (default: [1, 1, 320, 320])
HTMLCanvasElement containing the processed mask
When canvas context creation fails
// After running ONNX inference
const results = await session.run(input);
const outputTensor = results[Object.keys(results)[0]] as ort.Tensor;
const outputData = outputTensor.data as Float32Array;
const maskCanvas = processModelOutput(
outputData,
{ width: 800, height: 600 },
[1, 1, 320, 320]
);
// Use the mask for background removal
const cutout = naiveCutout(originalCanvas, maskCanvas);
Process ONNX model output to create mask canvas.
Converts raw model output (Float32Array) into a grayscale mask canvas. The output is normalized to 0-255 range and resized to match the original image dimensions.