本文整理汇总了Python中object_detection.core.box_list_ops.iou方法的典型用法代码示例。如果您正苦于以下问题：Python box_list_ops.iou方法的具体用法？Python box_list_ops.iou怎么用？Python box_list_ops.iou使用的例子？那么, 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.core.box_list_ops的用法示例。
在下文中一共展示了box_list_ops.iou方法的6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: test_iouworks_on_empty_inputs
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def test_iouworks_on_empty_inputs(self):
corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
[0.0, 0.0, 20.0, 20.0]])
boxes1 = box_list.BoxList(corners1)
boxes2 = box_list.BoxList(corners2)
boxes_empty = box_list.BoxList(tf.zeros((0, 4)))
iou_empty_1 = box_list_ops.iou(boxes1, boxes_empty)
iou_empty_2 = box_list_ops.iou(boxes_empty, boxes2)
iou_empty_3 = box_list_ops.iou(boxes_empty, boxes_empty)
with self.test_session() as sess:
iou_output_1, iou_output_2, iou_output_3 = sess.run(
[iou_empty_1, iou_empty_2, iou_empty_3])
self.assertAllEqual(iou_output_1.shape, (2, 0))
self.assertAllEqual(iou_output_2.shape, (0, 3))
self.assertAllEqual(iou_output_3.shape, (0, 0)) 示例2: _compare
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def _compare(self, boxlist1, boxlist2):
"""Compute pairwise IOU similarity between the two BoxLists and score.
Args:
boxlist1: BoxList holding N boxes. Must have a score field.
boxlist2: BoxList holding M boxes.
Returns:
A tensor with shape [N, M] representing scores threholded by pairwise
iou scores.
"""
ious = box_list_ops.iou(boxlist1, boxlist2)
scores = boxlist1.get_field(fields.BoxListFields.scores)
scores = tf.expand_dims(scores, axis=1)
row_replicated_scores = tf.tile(scores, [1, tf.shape(ious)[-1]])
thresholded_ious = tf.where(ious > self._iou_threshold,
row_replicated_scores, tf.zeros_like(ious))
return thresholded_ious 开发者ID:BMW-InnovationLab，项目名称:BMW-TensorFlow-Training-GUI，代码行数:21，代码来源:region_similarity_calculator.py
示例3: test_iou
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def test_iou(self):
corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0],
[0.0, 0.0, 20.0, 20.0]])
exp_output = [[2.0 / 16.0, 0, 6.0 / 400.0], [1.0 / 16.0, 0.0, 5.0 / 400.0]]
boxes1 = box_list.BoxList(corners1)
boxes2 = box_list.BoxList(corners2)
iou = box_list_ops.iou(boxes1, boxes2)
with self.test_session() as sess:
iou_output = sess.run(iou)
self.assertAllClose(iou_output, exp_output) 示例4: test_matched_iou
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def test_matched_iou(self):
corners1 = tf.constant([[4.0, 3.0, 7.0, 5.0], [5.0, 6.0, 10.0, 7.0]])
corners2 = tf.constant([[3.0, 4.0, 6.0, 8.0], [14.0, 14.0, 15.0, 15.0]])
exp_output = [2.0 / 16.0, 0]
boxes1 = box_list.BoxList(corners1)
boxes2 = box_list.BoxList(corners2)
iou = box_list_ops.matched_iou(boxes1, boxes2)
with self.test_session() as sess:
iou_output = sess.run(iou)
self.assertAllClose(iou_output, exp_output) 示例5: _compare
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def _compare(self, boxlist1, boxlist2):
"""Compute pairwise IOU similarity between the two BoxLists.
Args:
boxlist1: BoxList holding N boxes.
boxlist2: BoxList holding M boxes.
Returns:
A tensor with shape [N, M] representing pairwise iou scores.
"""
return box_list_ops.iou(boxlist1, boxlist2) 示例6: test_sample_boxes_by_jittering
# 需要导入模块: from object_detection.core import box_list_ops [as 别名]
# 或者: from object_detection.core.box_list_ops import iou [as 别名]
def test_sample_boxes_by_jittering(self):
boxes = box_list.BoxList(
tf.constant([[0.1, 0.1, 0.4, 0.4],
[0.1, 0.1, 0.5, 0.5],
[0.6, 0.6, 0.8, 0.8],
[0.2, 0.2, 0.3, 0.3]], tf.float32))
sampled_boxes = box_list_ops.sample_boxes_by_jittering(
boxlist=boxes, num_boxes_to_sample=10)
iou = box_list_ops.iou(boxes, sampled_boxes)
iou_max = tf.reduce_max(iou, axis=0)
with self.test_session() as sess:
(np_sampled_boxes, np_iou_max) = sess.run([sampled_boxes.get(), iou_max])
self.assertAllEqual(np_sampled_boxes.shape, [10, 4])
self.assertAllGreater(np_iou_max, 0.5)