Python coco_evaluation.CocoDetectionEvaluator方法代碼示例

本文整理匯總了Python中object_detection.metrics.coco_evaluation.CocoDetectionEvaluator方法的典型用法代碼示例。如果您正苦於以下問題：Python coco_evaluation.CocoDetectionEvaluator方法的具體用法？Python coco_evaluation.CocoDetectionEvaluator怎麽用？Python coco_evaluation.CocoDetectionEvaluator使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類object_detection.metrics.coco_evaluation的用法示例。

在下文中一共展示了coco_evaluation.CocoDetectionEvaluator方法的9個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: testExceptionRaisedWithMissingGroundtruth

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testExceptionRaisedWithMissingGroundtruth(self):
    """Tests that exception is raised for detection with missing groundtruth."""
    categories = [{'id': 1, 'name': 'cat'},
                  {'id': 2, 'name': 'dog'},
                  {'id': 3, 'name': 'elephant'}]
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(categories)
    with self.assertRaises(ValueError):
      coco_evaluator.add_single_detected_image_info(
          image_id='image1',
          detections_dict={
              standard_fields.DetectionResultFields.detection_boxes:
                  np.array([[100., 100., 200., 200.]]),
              standard_fields.DetectionResultFields.detection_scores:
                  np.array([.8]),
              standard_fields.DetectionResultFields.detection_classes:
                  np.array([1])
          })

開發者ID:ShreyAmbesh，項目名稱:Traffic-Rule-Violation-Detection-System，代碼行數:19，代碼來源:coco_evaluation_test.py

示例2: testGetOneMAPWithMatchingGroundtruthAndDetectionsSkipCrowd

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testGetOneMAPWithMatchingGroundtruthAndDetectionsSkipCrowd(self):
    """Tests computing mAP with is_crowd GT boxes skipped."""
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(
        _get_categories_list())
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
                np.array([[100., 100., 200., 200.], [99., 99., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes:
                np.array([1, 2]),
            standard_fields.InputDataFields.groundtruth_is_crowd:
                np.array([0, 1])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
                np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
                np.array([1])
        })
    metrics = coco_evaluator.evaluate()
    self.assertAlmostEqual(metrics['DetectionBoxes_Precision/mAP'], 1.0)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:28，代碼來源:coco_evaluation_test.py

示例3: testGetOneMAPWithMatchingGroundtruthAndDetectionsEmptyCrowd

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testGetOneMAPWithMatchingGroundtruthAndDetectionsEmptyCrowd(self):
    """Tests computing mAP with empty is_crowd array passed in."""
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(
        _get_categories_list())
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes:
                np.array([1]),
            standard_fields.InputDataFields.groundtruth_is_crowd:
                np.array([])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
                np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
                np.array([1])
        })
    metrics = coco_evaluator.evaluate()
    self.assertAlmostEqual(metrics['DetectionBoxes_Precision/mAP'], 1.0)

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:28，代碼來源:coco_evaluation_test.py

示例4: testRejectionOnDuplicateGroundtruth

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testRejectionOnDuplicateGroundtruth(self):
    """Tests that groundtruth cannot be added more than once for an image."""
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(
        _get_categories_list())
    #  Add groundtruth
    image_key1 = 'img1'
    groundtruth_boxes1 = np.array([[0, 0, 1, 1], [0, 0, 2, 2], [0, 0, 3, 3]],
                                  dtype=float)
    groundtruth_class_labels1 = np.array([1, 3, 1], dtype=int)
    coco_evaluator.add_single_ground_truth_image_info(image_key1, {
        standard_fields.InputDataFields.groundtruth_boxes:
            groundtruth_boxes1,
        standard_fields.InputDataFields.groundtruth_classes:
            groundtruth_class_labels1
    })
    groundtruth_lists_len = len(coco_evaluator._groundtruth_list)

    # Add groundtruth with the same image id.
    coco_evaluator.add_single_ground_truth_image_info(image_key1, {
        standard_fields.InputDataFields.groundtruth_boxes:
            groundtruth_boxes1,
        standard_fields.InputDataFields.groundtruth_classes:
            groundtruth_class_labels1
    })
    self.assertEqual(groundtruth_lists_len,
                     len(coco_evaluator._groundtruth_list))

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:28，代碼來源:coco_evaluation_test.py

示例5: testRejectionOnDuplicateDetections

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testRejectionOnDuplicateDetections(self):
    """Tests that detections cannot be added more than once for an image."""
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(
        _get_categories_list())
    #  Add groundtruth
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
            np.array([[99., 100., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes: np.array([1])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
            np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
            np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
            np.array([1])
        })
    detections_lists_len = len(coco_evaluator._detection_boxes_list)
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',  # Note that this image id was previously added.
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
            np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
            np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
            np.array([1])
        })
    self.assertEqual(detections_lists_len,
                     len(coco_evaluator._detection_boxes_list))

開發者ID:ahmetozlu，項目名稱:vehicle_counting_tensorflow，代碼行數:37，代碼來源:coco_evaluation_test.py

示例6: testGetOneMAPWithMatchingGroundtruthAndDetectionsSkipCrowd

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testGetOneMAPWithMatchingGroundtruthAndDetectionsSkipCrowd(self):
    """Tests computing mAP with is_crowd GT boxes skipped."""
    category_list = [{
        'id': 0,
        'name': 'person'
    }, {
        'id': 1,
        'name': 'cat'
    }, {
        'id': 2,
        'name': 'dog'
    }]
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(category_list)
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
                np.array([[100., 100., 200., 200.], [99., 99., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes:
                np.array([1, 2]),
            standard_fields.InputDataFields.groundtruth_is_crowd:
                np.array([0, 1])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
                np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
                np.array([1])
        })
    metrics = coco_evaluator.evaluate()
    self.assertAlmostEqual(metrics['DetectionBoxes_Precision/mAP'], 1.0)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:37，代碼來源:coco_evaluation_test.py

示例7: testGetOneMAPWithMatchingGroundtruthAndDetectionsEmptyCrowd

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testGetOneMAPWithMatchingGroundtruthAndDetectionsEmptyCrowd(self):
    """Tests computing mAP with empty is_crowd array passed in."""
    category_list = [{
        'id': 0,
        'name': 'person'
    }, {
        'id': 1,
        'name': 'cat'
    }, {
        'id': 2,
        'name': 'dog'
    }]
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(category_list)
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes:
                np.array([1]),
            standard_fields.InputDataFields.groundtruth_is_crowd:
                np.array([])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
                np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
                np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
                np.array([1])
        })
    metrics = coco_evaluator.evaluate()
    self.assertAlmostEqual(metrics['DetectionBoxes_Precision/mAP'], 1.0)

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:37，代碼來源:coco_evaluation_test.py

示例8: testRejectionOnDuplicateGroundtruth

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testRejectionOnDuplicateGroundtruth(self):
    """Tests that groundtruth cannot be added more than once for an image."""
    categories = [{'id': 1, 'name': 'cat'},
                  {'id': 2, 'name': 'dog'},
                  {'id': 3, 'name': 'elephant'}]
    #  Add groundtruth
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(categories)
    image_key1 = 'img1'
    groundtruth_boxes1 = np.array([[0, 0, 1, 1], [0, 0, 2, 2], [0, 0, 3, 3]],
                                  dtype=float)
    groundtruth_class_labels1 = np.array([1, 3, 1], dtype=int)
    coco_evaluator.add_single_ground_truth_image_info(image_key1, {
        standard_fields.InputDataFields.groundtruth_boxes:
            groundtruth_boxes1,
        standard_fields.InputDataFields.groundtruth_classes:
            groundtruth_class_labels1
    })
    groundtruth_lists_len = len(coco_evaluator._groundtruth_list)

    # Add groundtruth with the same image id.
    coco_evaluator.add_single_ground_truth_image_info(image_key1, {
        standard_fields.InputDataFields.groundtruth_boxes:
            groundtruth_boxes1,
        standard_fields.InputDataFields.groundtruth_classes:
            groundtruth_class_labels1
    })
    self.assertEqual(groundtruth_lists_len,
                     len(coco_evaluator._groundtruth_list))

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:30，代碼來源:coco_evaluation_test.py

示例9: testRejectionOnDuplicateDetections

# 需要導入模塊: from object_detection.metrics import coco_evaluation [as 別名]
# 或者: from object_detection.metrics.coco_evaluation import CocoDetectionEvaluator [as 別名]
def testRejectionOnDuplicateDetections(self):
    """Tests that detections cannot be added more than once for an image."""
    categories = [{'id': 1, 'name': 'cat'},
                  {'id': 2, 'name': 'dog'},
                  {'id': 3, 'name': 'elephant'}]
    #  Add groundtruth
    coco_evaluator = coco_evaluation.CocoDetectionEvaluator(categories)
    coco_evaluator.add_single_ground_truth_image_info(
        image_id='image1',
        groundtruth_dict={
            standard_fields.InputDataFields.groundtruth_boxes:
            np.array([[99., 100., 200., 200.]]),
            standard_fields.InputDataFields.groundtruth_classes: np.array([1])
        })
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
            np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
            np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
            np.array([1])
        })
    detections_lists_len = len(coco_evaluator._detection_boxes_list)
    coco_evaluator.add_single_detected_image_info(
        image_id='image1',  # Note that this image id was previously added.
        detections_dict={
            standard_fields.DetectionResultFields.detection_boxes:
            np.array([[100., 100., 200., 200.]]),
            standard_fields.DetectionResultFields.detection_scores:
            np.array([.8]),
            standard_fields.DetectionResultFields.detection_classes:
            np.array([1])
        })
    self.assertEqual(detections_lists_len,
                     len(coco_evaluator._detection_boxes_list))

開發者ID:cagbal，項目名稱:ros_people_object_detection_tensorflow，代碼行數:39，代碼來源:coco_evaluation_test.py

注：本文中的object_detection.metrics.coco_evaluation.CocoDetectionEvaluator方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。