本文整理汇总了Python中object_detection.utils.object_detection_evaluation.ObjectDetectionEvaluation方法的典型用法代码示例。如果您正苦于以下问题：Python object_detection_evaluation.ObjectDetectionEvaluation方法的具体用法？Python object_detection_evaluation.ObjectDetectionEvaluation怎么用？Python object_detection_evaluation.ObjectDetectionEvaluation使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.utils.object_detection_evaluation的用法示例。
在下文中一共展示了object_detection_evaluation.ObjectDetectionEvaluation方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: setUp
# 需要导入模块: from object_detection.utils import object_detection_evaluation [as 别名]
# 或者: from object_detection.utils.object_detection_evaluation import ObjectDetectionEvaluation [as 别名]
def setUp(self):
num_groundtruth_classes = 3
self.od_eval = object_detection_evaluation.ObjectDetectionEvaluation(
num_groundtruth_classes)
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([0, 2, 0], dtype=int)
self.od_eval.add_single_ground_truth_image_info(
image_key1, groundtruth_boxes1, groundtruth_class_labels1)
image_key2 = "img2"
groundtruth_boxes2 = np.array([[10, 10, 11, 11], [500, 500, 510, 510],
[10, 10, 12, 12]], dtype=float)
groundtruth_class_labels2 = np.array([0, 0, 2], dtype=int)
groundtruth_is_difficult_list2 = np.array([False, True, False], dtype=bool)
self.od_eval.add_single_ground_truth_image_info(
image_key2, groundtruth_boxes2, groundtruth_class_labels2,
groundtruth_is_difficult_list2)
image_key3 = "img3"
groundtruth_boxes3 = np.array([[0, 0, 1, 1]], dtype=float)
groundtruth_class_labels3 = np.array([1], dtype=int)
self.od_eval.add_single_ground_truth_image_info(
image_key3, groundtruth_boxes3, groundtruth_class_labels3)
image_key = "img2"
detected_boxes = np.array(
[[10, 10, 11, 11], [100, 100, 120, 120], [100, 100, 220, 220]],
dtype=float)
detected_class_labels = np.array([0, 0, 2], dtype=int)
detected_scores = np.array([0.7, 0.8, 0.9], dtype=float)
self.od_eval.add_single_detected_image_info(
image_key, detected_boxes, detected_scores, detected_class_labels) 示例2: setUp
# 需要导入模块: from object_detection.utils import object_detection_evaluation [as 别名]
# 或者: from object_detection.utils.object_detection_evaluation import ObjectDetectionEvaluation [as 别名]
def setUp(self):
num_groundtruth_classes = 3
self.od_eval = object_detection_evaluation.ObjectDetectionEvaluation(
num_groundtruth_classes)
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([0, 2, 0], dtype=int)
self.od_eval.add_single_ground_truth_image_info(
image_key1, groundtruth_boxes1, groundtruth_class_labels1)
image_key2 = 'img2'
groundtruth_boxes2 = np.array([[10, 10, 11, 11], [500, 500, 510, 510],
[10, 10, 12, 12]], dtype=float)
groundtruth_class_labels2 = np.array([0, 0, 2], dtype=int)
groundtruth_is_difficult_list2 = np.array([False, True, False], dtype=bool)
groundtruth_is_group_of_list2 = np.array([False, False, True], dtype=bool)
self.od_eval.add_single_ground_truth_image_info(
image_key2, groundtruth_boxes2, groundtruth_class_labels2,
groundtruth_is_difficult_list2, groundtruth_is_group_of_list2)
image_key3 = 'img3'
groundtruth_boxes3 = np.array([[0, 0, 1, 1]], dtype=float)
groundtruth_class_labels3 = np.array([1], dtype=int)
self.od_eval.add_single_ground_truth_image_info(
image_key3, groundtruth_boxes3, groundtruth_class_labels3)
image_key = 'img2'
detected_boxes = np.array(
[[10, 10, 11, 11], [100, 100, 120, 120], [100, 100, 220, 220]],
dtype=float)
detected_class_labels = np.array([0, 0, 2], dtype=int)
detected_scores = np.array([0.7, 0.8, 0.9], dtype=float)
self.od_eval.add_single_detected_image_info(
image_key, detected_boxes, detected_scores, detected_class_labels) 示例3: test_value_error_on_zero_classes
# 需要导入模块: from object_detection.utils import object_detection_evaluation [as 别名]
# 或者: from object_detection.utils.object_detection_evaluation import ObjectDetectionEvaluation [as 别名]
def test_value_error_on_zero_classes(self):
with self.assertRaises(ValueError):
object_detection_evaluation.ObjectDetectionEvaluation(
num_groundtruth_classes=0)