code: def test_evaluate_regressions_frames():
      dataset = foz.load_zoo_dataset("quickstart-video").clone()
  
      for sample in dataset:
          for frame_number, frame in sample.frames.items():
              ytrue = random.random() * frame_number
              ypred = ytrue + np.random.randn() * np.sqrt(ytrue)
              confidence = random.random()
              frame["ground_truth"] = fo.Regression(value=ytrue)
              frame["predictions"] = fo.Regression(
                  value=ypred, confidence=confidence
              )
              frame["weather"] = random.choice(
                  ["sunny", "cloudy", "rainy"]
              )
              frame.save()
  
          sample.save()
  
      #
      # Simple regression
      #
  
      results = dataset.evaluate_regressions(
          "frames.predictions",
          gt_field="frames.ground_truth",
          eval_key="eval",
      )
  
      results.print_metrics()
  
      print(dataset.bounds("eval"))
      print(dataset.bounds("frames.eval"))
  
      plot = results.plot_results(
          labels="frames.weather", sizes="frames.predictions.confidence"
      )
      plot.show()
  
      input("Press enter to continue...")
  
      #
      # Cleanup
      #
  
      dataset.delete_evaluations()
  
file_path: fiftyone/tests/intensive/evaluation_tests.py
imports: import random
  import unittest
  import numpy
  import eta.core.utils
  import pytest
  import fiftyone
  import fiftyone.zoo
  from fiftyone import ViewField
label_desc: Use image node_id 2 for calling a global function with example usage: test_evaluate_regressions_frames() without return types