def test_iou_threshold(self):
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.5)
predictions = [[
[0, 1.0, 0.5, 0.5, 1, 1], # IOU 0.25
[1, 1.0, 0.5, 0.5, 1, 1]
]]
targets = [[[0, 0, 0, 1, 1], [1, 0.5, 0.5, 1, 1]]]
evaluator.add_predictions(predictions, targets)
report = evaluator.get_report()
self.assertEqual(report["mAP_50"], 0.5)
self.assertTrue(isinstance(report["mAP_50"], float))
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.2)
predictions = [[
[0, 1.0, 0.5, 0.5, 1, 1], # IOU 0.25
[1, 1.0, 0.5, 0.5, 1, 1]
]]
targets = [[[0, 0, 0, 1, 1], [1, 0.5, 0.5, 1, 1]]]
evaluator.add_predictions(predictions, targets)
report = evaluator.get_report()
self.assertEqual(report["mAP_20"], 1.0)
self.assertTrue(isinstance(report["mAP_20"], float))
def test_no_predictions(self):
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.5)
predictions = [[]]
targets = [[[0, 0, 0, 1, 1], [1, 0.5, 0.5, 1, 1],
[2, 0.1, 0.1, 0.5, 0.5]]]
evaluator.add_predictions(predictions, targets)
report = evaluator.get_report()
self.assertEqual(report["mAP_50"], 0.0)
self.assertTrue(isinstance(report["mAP_50"], float))
def test_perfect_one_image_absolute_coordinates(self):
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.5)
predictions = [[[0, 1.0, 0, 0, 10, 10],
[1, 1.0, 5, 5, 10, 10],
[2, 1.0, 1, 1, 5, 5]]]
targets = [[[0, 0, 0, 10, 10],
[1, 5, 5, 10, 10],
[2, 1, 1, 5, 5]]]
evaluator.add_predictions(predictions, targets)
report = evaluator.get_report()
self.assertEqual(report["mAP_50"], 1.0)
self.assertTrue(isinstance(report["mAP_50"], float))
def test_two_batches(self):
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.5, report_tag_wise=True)
predictions = [[[0, 1.0, 0, 0, 1, 1],
[1, 1.0, 0.5, 0.5, 1, 1]],
[[2, 1.0, 0.1, 0.1, 0.5, 0.5]]]
targets = [[[0, 0, 0, 1, 1],
[1, 0.5, 0.5, 1, 1]],
[[2, 0.1, 0.1, 0.5, 0.5]]]
evaluator.add_predictions(predictions, targets)
predictions = [[[0, 1.0, 0.9, 0.9, 1, 1], # Wrong
[1, 1.0, 0.5, 0.5, 1, 1]],
[[2, 1.0, 0.1, 0.1, 0.5, 0.5]]]
targets = [[[0, 0, 0, 1, 1],
[1, 0.5, 0.5, 1, 1]],
[[2, 0.1, 0.1, 0.5, 0.5]]]
evaluator.add_predictions(predictions, targets)
report = evaluator.get_report()
self.assertEqual(report["mAP_50"], 0.75)
self.assertTrue(isinstance(report["mAP_50"], float))
self.assertEqual(len(report["tag_wise_AP_50"]), 3)
def test_empty_result(self):
evaluator = MeanAveragePrecisionEvaluatorForSingleIOU(iou=0.5)
report = evaluator.get_report()
self.assertIn('mAP_50', report)
self.assertEqual(report["mAP_50"], 0.0)
self.assertTrue(isinstance(report["mAP_50"], float))