Method estimateMultiplePoses

posenet/src/posenet_model.ts:279–324

* Infer through PoseNet, and estimates multiple poses using the outputs. * This does standard ImageNet pre-processing before inferring through the * model. The image should pixels should have values [0-255]. It detects * multiple poses and finds their parts from part scores and displacement

(
      input: PosenetInput,
      config: MultiPersonInferenceConfig = MULTI_PERSON_INFERENCE_CONFIG)

   * in the same scale as the original image
   */
  async estimateMultiplePoses(
      input: PosenetInput,
      config: MultiPersonInferenceConfig = MULTI_PERSON_INFERENCE_CONFIG):
      Promise<Pose[]> {
    const configWithDefaults: MultiPersonInferenceConfig = {
      ...MULTI_PERSON_INFERENCE_CONFIG,
      ...config
    };

    validateMultiPersonInputConfig(config);

    const outputStride = this.baseModel.outputStride;
    const inputResolution = this.inputResolution;

    const [height, width] = getInputTensorDimensions(input);

    const {resized, padding} = padAndResizeTo(input, inputResolution);

    const {heatmapScores, offsets, displacementFwd, displacementBwd} =
        this.baseModel.predict(resized);

    const allTensorBuffers = await toTensorBuffers3D(
        [heatmapScores, offsets, displacementFwd, displacementBwd]);

    const scoresBuffer = allTensorBuffers[0];
    const offsetsBuffer = allTensorBuffers[1];
    const displacementsFwdBuffer = allTensorBuffers[2];
    const displacementsBwdBuffer = allTensorBuffers[3];

    const poses = await decodeMultiplePoses(
        scoresBuffer, offsetsBuffer, displacementsFwdBuffer,
        displacementsBwdBuffer, outputStride, configWithDefaults.maxDetections,
        configWithDefaults.scoreThreshold, configWithDefaults.nmsRadius);

    const resultPoses = scaleAndFlipPoses(
        poses, [height, width], inputResolution, padding,
        configWithDefaults.flipHorizontal);

    heatmapScores.dispose();
    offsets.dispose();
    displacementFwd.dispose();
    displacementBwd.dispose();
    resized.dispose();

    return resultPoses;
  }

  /**
   * Infer through PoseNet, and estimates a single pose using the outputs.