Function predict

gpu-pipeline/webgpu/index.js:90–152

()

  device.queue.writeBuffer(sizeParamBuffer, 0, new Int32Array([sizeParams.width, sizeParams.height]));

  const predict = async () => {
    beginEstimateSegmentationStats();
    const segmentationConfig = {flipHorizontal: false, multiSegmentation: false, segmentBodyParts: true,
      segmentationThreshold: 0.5};
    const segmentation = await model.segmentPeople(video, segmentationConfig);

    const tensor = await segmentation[0].mask.toTensor();
    const data = tensor.dataToGPU();

    const uniformBindGroup = device.createBindGroup({
      layout: pipeline.getBindGroupLayout(0),
      entries: [
        {
          binding: 1,
          resource: sampler,
        },
        {
          binding: 2,
          resource: device.importExternalTexture({
            source: video,
          }),
        },
        {
          binding: 3,
          resource: {
            buffer: data.buffer,
          },
        },
        {
          binding: 4,
          resource: {
            buffer: sizeParamBuffer,
          },
        }
      ],
    });

    const commandEncoder = device.createCommandEncoder();
    const textureView = context.getCurrentTexture().createView();

    const renderPassDescriptor = {
      colorAttachments: [
        {
          view: textureView,
          clearValue: { r: 0.0, g: 0.0, b: 0.0, a: 1.0 },
          loadOp: 'clear',
          storeOp: 'store',
        },
      ],
    };

    const passEncoder = commandEncoder.beginRenderPass(renderPassDescriptor);
    passEncoder.setPipeline(pipeline);
    passEncoder.setBindGroup(0, uniformBindGroup);
    passEncoder.draw(6, 1, 0, 0);
    passEncoder.end();
    device.queue.submit([commandEncoder.finish()]);
    tensor.dispose();