本文整理汇总了Python中object_detection.utils.np_box_ops.intersection方法的典型用法代码示例。如果您正苦于以下问题：Python np_box_ops.intersection方法的具体用法？Python np_box_ops.intersection怎么用？Python np_box_ops.intersection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.np_box_ops的用法示例。
在下文中一共展示了np_box_ops.intersection方法的4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: testIntersection
# 需要导入模块: from object_detection.utils import np_box_ops [as 别名]
# 或者: from object_detection.utils.np_box_ops import intersection [as 别名]
def testIntersection(self):
intersection = np_box_ops.intersection(self.boxes1, self.boxes2)
expected_intersection = np.array([[2.0, 0.0, 6.0], [1.0, 0.0, 5.0]],
dtype=float)
self.assertAllClose(intersection, expected_intersection) 示例2: intersection
# 需要导入模块: from object_detection.utils import np_box_ops [as 别名]
# 或者: from object_detection.utils.np_box_ops import intersection [as 别名]
def intersection(boxlist1, boxlist2):
"""Compute pairwise intersection areas between boxes.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N*M] representing pairwise intersection area
"""
return np_box_ops.intersection(boxlist1.get(), boxlist2.get()) 示例3: iou
# 需要导入模块: from object_detection.utils import np_box_ops [as 别名]
# 或者: from object_detection.utils.np_box_ops import intersection [as 别名]
def iou(boxlist1, boxlist2):
"""Computes pairwise intersection-over-union between box collections.
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_box_ops.iou(boxlist1.get(), boxlist2.get()) 示例4: ioa
# 需要导入模块: from object_detection.utils import np_box_ops [as 别名]
# 或者: from object_detection.utils.np_box_ops import intersection [as 别名]
def ioa(boxlist1, boxlist2):
"""Computes pairwise intersection-over-area between box collections.
Intersection-over-area (ioa) between two boxes box1 and box2 is defined as
their intersection area over box2's area. Note that ioa is not symmetric,
that is, IOA(box1, box2) != IOA(box2, box1).
Args:
boxlist1: BoxList holding N boxes
boxlist2: BoxList holding M boxes
Returns:
a numpy array with shape [N, M] representing pairwise ioa scores.
"""
return np_box_ops.ioa(boxlist1.get(), boxlist2.get())