code: def test_pic_curve(self):
      num_data_points = 2000
      mask = pic.generate_random_mask(
          image_height=self.img.shape[0],
          image_width=self.img.shape[1],
          fraction=0.01,
      )
      saliency_map = np.random.random(
          size=(self.img.shape[0], self.img.shape[1])
      )
      saliency_thresholds = [0.01, 0.02, 0.03, 0.05]
      metric_result = pic.compute_pic_metric(
          img=self.img,
          saliency_map=saliency_map,
          random_mask=mask,
          pred_func=self._test_predict_func,
          saliency_thresholds=saliency_thresholds,
          num_data_points=num_data_points,
      )
      self.assertEqual(len(metric_result.curve_x), num_data_points + 1)
      self.assertEqual(len(metric_result.curve_y), num_data_points + 1)
      self.assertGreater(metric_result.auc, 0.0)
      self.assertLess(metric_result.auc, 1.0)
      self.assertEqual(
          len(metric_result.predictions), len(saliency_thresholds) + 2
      )
      self.assertEqual(
          len(metric_result.blurred_images),
          len(saliency_thresholds) + 2,
      )
  
file_path: saliency/saliency/metrics/pic_test.py
imports: import numpy
  import os
  import unittest
  from .None import pic
  from pathlib import Path
  from PIL import Image
label_desc: Use image node_id 8 for calling the PicTest obj's underlying member method code with example usage: obj.test_pic_curve() without return types