class_docstr: Get peak values and coordinate from input.
  
  Args:
      thresh(float): Threshold value for selecting peak value, default is 0.1.
code: def __call__(self, heatmap: np.ndarray):
      all_peaks = []
      peak_counter = 0
      for part in range(18):
          map_ori = heatmap[:, :, part]
          one_heatmap = gaussian_filter(map_ori, sigma=3)
  
          map_left = np.zeros(one_heatmap.shape)
          map_left[1:, :] = one_heatmap[:-1, :]
          map_right = np.zeros(one_heatmap.shape)
          map_right[:-1, :] = one_heatmap[1:, :]
          map_up = np.zeros(one_heatmap.shape)
          map_up[:, 1:] = one_heatmap[:, :-1]
          map_down = np.zeros(one_heatmap.shape)
          map_down[:, :-1] = one_heatmap[:, 1:]
  
          peaks_binary = np.logical_and.reduce(
              (
                  one_heatmap >= map_left,
                  one_heatmap >= map_right,
                  one_heatmap >= map_up,
                  one_heatmap >= map_down,
                  one_heatmap > self.thresh,
              )
          )
          peaks = list(
              zip(
                  np.nonzero(peaks_binary)[1],
                  np.nonzero(peaks_binary)[0],
              )
          )  # note reverse
          peaks_with_score = [x + (map_ori[x[1], x[0]],) for x in peaks]
          peak_id = range(peak_counter, peak_counter + len(peaks))
          peaks_with_score_and_id = [
              peaks_with_score[i] + (peak_id[i],)
              for i in range(len(peak_id))
          ]
  
          all_peaks.append(peaks_with_score_and_id)
          peak_counter += len(peaks)
  
      return all_peaks
  
imports: import base64
  import math
  from typing import Callable
  import cv2
  import numpy
  from scipy.ndimage import gaussian_filter
label_desc: Use image node_id 2 for calling the GetPeak obj's underlying member method code with example usage: obj.__call__(heatmap) and returns: all_peaks