code: def makeplot(rs, ps, outDir, class_name, iou_type):
      cs = np.vstack(
          [
              np.ones((2, 3)),
              np.array([0.31, 0.51, 0.74]),
              np.array([0.75, 0.31, 0.30]),
              np.array([0.36, 0.90, 0.38]),
              np.array([0.50, 0.39, 0.64]),
              np.array([1, 0.6, 0]),
          ]
      )
      areaNames = ["allarea", "small", "medium", "large"]
      types = ["C75", "C50", "Loc", "Sim", "Oth", "BG", "FN"]
      for i in range(len(areaNames)):
          area_ps = ps[..., i, 0]
          figure_title = (
              iou_type + "-" + class_name + "-" + areaNames[i]
          )
          aps = [ps_.mean() for ps_ in area_ps]
          ps_curve = [
              ps_.mean(axis=1) if ps_.ndim > 1 else ps_
              for ps_ in area_ps
          ]
          ps_curve.insert(0, np.zeros(ps_curve[0].shape))
          fig = plt.figure()
          ax = plt.subplot(111)
          for k in range(len(types)):
              ax.plot(
                  rs, ps_curve[k + 1], color=[0, 0, 0], linewidth=0.5
              )
              ax.fill_between(
                  rs,
                  ps_curve[k],
                  ps_curve[k + 1],
                  color=cs[k],
                  label=str(f"[{aps[k]:.3f}]" + types[k]),
              )
          plt.xlabel("recall")
          plt.ylabel("precision")
          plt.xlim(0, 1.0)
          plt.ylim(0, 1.0)
          plt.title(figure_title)
          plt.legend()
          # plt.show()
          fig.savefig(outDir + f"/{figure_title}.png")
          plt.close(fig)
  
file_path: mmdetection/tools/analysis_tools/coco_error_analysis.py
imports: import copy
  import os
  from argparse import ArgumentParser
  from multiprocessing import Pool
  import matplotlib.pyplot
  import numpy
  from pycocotools.coco import COCO
  from pycocotools.cocoeval import COCOeval
label_desc: Use image node_id 1 for calling a global function with example usage: makeplot(rs, ps, outDir, class_name, iou_type) without return types