本文整理汇总了Python中object_detection.core.post_processing.multiclass_non_max_suppression方法的典型用法代码示例。如果您正苦于以下问题：Python post_processing.multiclass_non_max_suppression方法的具体用法？Python post_processing.multiclass_non_max_suppression怎么用？Python post_processing.multiclass_non_max_suppression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.post_processing的用法示例。
在下文中一共展示了post_processing.multiclass_non_max_suppression方法的5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_with_invalid_scores_size
# 需要导入模块: from object_detection.core import post_processing [as 别名]
# 或者: from object_detection.core.post_processing import multiclass_non_max_suppression [as 别名]
def test_with_invalid_scores_size(self):
boxes = tf.constant([[[0, 0, 1, 1]],
[[0, 0.1, 1, 1.1]],
[[0, -0.1, 1, 0.9]],
[[0, 10, 1, 11]],
[[0, 10.1, 1, 11.1]],
[[0, 100, 1, 101]]], tf.float32)
scores = tf.constant([[.9], [.75], [.6], [.95], [.5]])
iou_thresh = .5
score_thresh = 0.6
max_output_size = 3
nms = post_processing.multiclass_non_max_suppression(
boxes, scores, score_thresh, iou_thresh, max_output_size)
with self.test_session() as sess:
with self.assertRaisesWithPredicateMatch(
tf.errors.InvalidArgumentError, 'Incorrect scores field length'):
sess.run(nms.get()) 示例2: test_multiclass_nms_select_with_clip_window
# 需要导入模块: from object_detection.core import post_processing [as 别名]
# 或者: from object_detection.core.post_processing import multiclass_non_max_suppression [as 别名]
def test_multiclass_nms_select_with_clip_window(self):
boxes = tf.constant([[[0, 0, 10, 10]],
[[1, 1, 11, 11]]], tf.float32)
scores = tf.constant([[.9], [.75]])
clip_window = tf.constant([5, 4, 8, 7], tf.float32)
score_thresh = 0.0
iou_thresh = 0.5
max_output_size = 100
exp_nms_corners = [[5, 4, 8, 7]]
exp_nms_scores = [.9]
exp_nms_classes = [0]
nms = post_processing.multiclass_non_max_suppression(
boxes, scores, score_thresh, iou_thresh, max_output_size,
clip_window=clip_window)
with self.test_session() as sess:
nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
[nms.get(), nms.get_field(fields.BoxListFields.scores),
nms.get_field(fields.BoxListFields.classes)])
self.assertAllClose(nms_corners_output, exp_nms_corners)
self.assertAllClose(nms_scores_output, exp_nms_scores)
self.assertAllClose(nms_classes_output, exp_nms_classes) 示例3: test_multiclass_nms_select_with_clip_window_change_coordinate_frame
# 需要导入模块: from object_detection.core import post_processing [as 别名]
# 或者: from object_detection.core.post_processing import multiclass_non_max_suppression [as 别名]
def test_multiclass_nms_select_with_clip_window_change_coordinate_frame(self):
boxes = tf.constant([[[0, 0, 10, 10]],
[[1, 1, 11, 11]]], tf.float32)
scores = tf.constant([[.9], [.75]])
clip_window = tf.constant([5, 4, 8, 7], tf.float32)
score_thresh = 0.0
iou_thresh = 0.5
max_output_size = 100
exp_nms_corners = [[0, 0, 1, 1]]
exp_nms_scores = [.9]
exp_nms_classes = [0]
nms = post_processing.multiclass_non_max_suppression(
boxes, scores, score_thresh, iou_thresh, max_output_size,
clip_window=clip_window, change_coordinate_frame=True)
with self.test_session() as sess:
nms_corners_output, nms_scores_output, nms_classes_output = sess.run(
[nms.get(), nms.get_field(fields.BoxListFields.scores),
nms.get_field(fields.BoxListFields.classes)])
self.assertAllClose(nms_corners_output, exp_nms_corners)
self.assertAllClose(nms_scores_output, exp_nms_scores)
self.assertAllClose(nms_classes_output, exp_nms_classes) 示例4: test_multiclass_nms_threshold_then_select_with_shared_boxes
# 需要导入模块: from object_detection.core import post_processing [as 别名]
# 或者: from object_detection.core.post_processing import multiclass_non_max_suppression [as 别名]
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
boxes = tf.constant([[[0, 0, 1, 1]],
[[0, 0.1, 1, 1.1]],
[[0, -0.1, 1, 0.9]],
[[0, 10, 1, 11]],
[[0, 10.1, 1, 11.1]],
[[0, 100, 1, 101]],
[[0, 1000, 1, 1002]],
[[0, 1000, 1, 1002.1]]], tf.float32)
scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
score_thresh = 0.1
iou_thresh = .5
max_output_size = 3
exp_nms = [[0, 10, 1, 11],
[0, 0, 1, 1],
[0, 100, 1, 101]]
nms = post_processing.multiclass_non_max_suppression(
boxes, scores, score_thresh, iou_thresh, max_output_size)
with self.test_session() as sess:
nms_output = sess.run(nms.get())
self.assertAllClose(nms_output, exp_nms) 示例5: test_multiclass_nms_threshold_then_select_with_shared_boxes
# 需要导入模块: from object_detection.core import post_processing [as 别名]
# 或者: from object_detection.core.post_processing import multiclass_non_max_suppression [as 别名]
def test_multiclass_nms_threshold_then_select_with_shared_boxes(self):
boxes = tf.constant([[[0, 0, 1, 1]],
[[0, 0.1, 1, 1.1]],
[[0, -0.1, 1, 0.9]],
[[0, 10, 1, 11]],
[[0, 10.1, 1, 11.1]],
[[0, 100, 1, 101]],
[[0, 1000, 1, 1002]],
[[0, 1000, 1, 1002.1]]], tf.float32)
scores = tf.constant([[.9], [.75], [.6], [.95], [.5], [.3], [.01], [.01]])
score_thresh = 0.1
iou_thresh = .5
max_output_size = 3
exp_nms = [[0, 10, 1, 11],
[0, 0, 1, 1],
[0, 100, 1, 101]]
nms, _ = post_processing.multiclass_non_max_suppression(
boxes, scores, score_thresh, iou_thresh, max_output_size)
with self.test_session() as sess:
nms_output = sess.run(nms.get())
self.assertAllClose(nms_output, exp_nms)