本文整理汇总了Python中object_detection.matchers.bipartite_matcher.GreedyBipartiteMatcher方法的典型用法代码示例。如果您正苦于以下问题:Python bipartite_matcher.GreedyBipartiteMatcher方法的具体用法?Python bipartite_matcher.GreedyBipartiteMatcher怎么用?Python bipartite_matcher.GreedyBipartiteMatcher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.matchers.bipartite_matcher
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在下文中一共展示了bipartite_matcher.GreedyBipartiteMatcher方法的15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_raises_error_on_invalid_groundtruth_labels
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_raises_error_on_invalid_groundtruth_labels(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
unmatched_cls_target = tf.constant([[0, 0], [0, 0], [0, 0]], tf.float32)
target_assigner = targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
unmatched_cls_target=unmatched_cls_target)
prior_means = tf.constant([[0.0, 0.0, 0.5, 0.5]])
prior_stddevs = tf.constant([[1.0, 1.0, 1.0, 1.0]])
priors = box_list.BoxList(prior_means)
priors.add_field('stddev', prior_stddevs)
box_corners = [[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 0.9, 0.9],
[.75, 0, .95, .27]]
boxes = box_list.BoxList(tf.constant(box_corners))
groundtruth_labels = tf.constant([[[0, 1], [1, 0]]], tf.float32)
with self.assertRaises(ValueError):
target_assigner.assign(priors, boxes, groundtruth_labels,
num_valid_rows=3)
示例2: test_raises_error_on_invalid_groundtruth_labels
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_raises_error_on_invalid_groundtruth_labels(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=1.0)
unmatched_class_label = tf.constant([[0, 0], [0, 0], [0, 0]], tf.float32)
target_assigner = targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder)
prior_means = tf.constant([[0.0, 0.0, 0.5, 0.5]])
priors = box_list.BoxList(prior_means)
box_corners = [[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 0.9, 0.9],
[.75, 0, .95, .27]]
boxes = box_list.BoxList(tf.constant(box_corners))
groundtruth_labels = tf.constant([[[0, 1], [1, 0]]], tf.float32)
with self.assertRaises(ValueError):
target_assigner.assign(
priors,
boxes,
groundtruth_labels,
unmatched_class_label=unmatched_class_label)
示例3: test_raises_error_on_invalid_groundtruth_labels
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_raises_error_on_invalid_groundtruth_labels(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
unmatched_cls_target = tf.constant([[0, 0], [0, 0], [0, 0]], tf.float32)
target_assigner = targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
unmatched_cls_target=unmatched_cls_target)
prior_means = tf.constant([[0.0, 0.0, 0.5, 0.5]])
prior_stddevs = tf.constant([[1.0, 1.0, 1.0, 1.0]])
priors = box_list.BoxList(prior_means)
priors.add_field('stddev', prior_stddevs)
box_corners = [[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 0.9, 0.9],
[.75, 0, .95, .27]]
boxes = box_list.BoxList(tf.constant(box_corners))
groundtruth_labels = tf.constant([[[0, 1], [1, 0]]], tf.float32)
with self.assertRaises(ValueError):
target_assigner.assign(priors, boxes, groundtruth_labels,
num_valid_rows=3)
示例4: test_raises_error_on_invalid_groundtruth_labels
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_raises_error_on_invalid_groundtruth_labels(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder(stddev=1.0)
unmatched_cls_target = tf.constant([[0, 0], [0, 0], [0, 0]], tf.float32)
target_assigner = targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
unmatched_cls_target=unmatched_cls_target)
prior_means = tf.constant([[0.0, 0.0, 0.5, 0.5]])
priors = box_list.BoxList(prior_means)
box_corners = [[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 0.9, 0.9],
[.75, 0, .95, .27]]
boxes = box_list.BoxList(tf.constant(box_corners))
groundtruth_labels = tf.constant([[[0, 1], [1, 0]]], tf.float32)
with self.assertRaises(ValueError):
target_assigner.assign(priors, boxes, groundtruth_labels,
num_valid_rows=3)
示例5: test_get_expected_matches_when_all_rows_are_valid
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_expected_matches_when_all_rows_are_valid(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
num_valid_rows = 2
expected_match_results = [-1, 1, 0]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)
示例6: test_get_expected_matches_with_valid_rows_set_to_minus_one
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_expected_matches_with_valid_rows_set_to_minus_one(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
num_valid_rows = -1
expected_match_results = [-1, 1, 0]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)
示例7: test_get_no_matches_with_zero_valid_rows
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_no_matches_with_zero_valid_rows(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
num_valid_rows = 0
expected_match_results = [-1, -1, -1]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)
示例8: test_get_expected_matches_with_only_one_valid_row
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_expected_matches_with_only_one_valid_row(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
num_valid_rows = 1
expected_match_results = [-1, -1, 0]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)
示例9: test_assign_multiclass_unequal_class_weights
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_assign_multiclass_unequal_class_weights(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
unmatched_cls_target = tf.constant([1, 0, 0, 0, 0, 0, 0], tf.float32)
target_assigner = targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
positive_class_weight=1.0, negative_class_weight=0.5,
unmatched_cls_target=unmatched_cls_target)
prior_means = tf.constant([[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 1.0, 0.8],
[0, 0.5, .5, 1.0],
[.75, 0, 1.0, .25]])
prior_stddevs = tf.constant(4 * [4 * [.1]])
priors = box_list.BoxList(prior_means)
priors.add_field('stddev', prior_stddevs)
box_corners = [[0.0, 0.0, 0.5, 0.5],
[0.5, 0.5, 0.9, 0.9],
[.75, 0, .95, .27]]
boxes = box_list.BoxList(tf.constant(box_corners))
groundtruth_labels = tf.constant([[0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0, 0]], tf.float32)
exp_cls_weights = [1, 1, .5, 1]
result = target_assigner.assign(priors, boxes, groundtruth_labels,
num_valid_rows=3)
(_, cls_weights, _, _, _) = result
with self.test_session() as sess:
cls_weights_out = sess.run(cls_weights)
self.assertAllClose(cls_weights_out, exp_cls_weights)
示例10: _get_agnostic_target_assigner
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def _get_agnostic_target_assigner(self):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
return targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
positive_class_weight=1.0,
negative_class_weight=1.0,
unmatched_cls_target=None)
示例11: _get_multi_dimensional_target_assigner
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def _get_multi_dimensional_target_assigner(self, target_dimensions):
similarity_calc = region_similarity_calculator.NegSqDistSimilarity()
matcher = bipartite_matcher.GreedyBipartiteMatcher()
box_coder = mean_stddev_box_coder.MeanStddevBoxCoder()
unmatched_cls_target = tf.constant(np.zeros(target_dimensions),
tf.float32)
return targetassigner.TargetAssigner(
similarity_calc, matcher, box_coder,
positive_class_weight=1.0,
negative_class_weight=1.0,
unmatched_cls_target=unmatched_cls_target)
示例12: test_build_bipartite_matcher
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_build_bipartite_matcher(self):
matcher_text_proto = """
bipartite_matcher {
}
"""
matcher_proto = matcher_pb2.Matcher()
text_format.Merge(matcher_text_proto, matcher_proto)
matcher_object = matcher_builder.build(matcher_proto)
self.assertTrue(
isinstance(matcher_object, bipartite_matcher.GreedyBipartiteMatcher))
示例13: build
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def build(matcher_config):
"""Builds a matcher object based on the matcher config.
Args:
matcher_config: A matcher.proto object containing the config for the desired
Matcher.
Returns:
Matcher based on the config.
Raises:
ValueError: On empty matcher proto.
"""
if not isinstance(matcher_config, matcher_pb2.Matcher):
raise ValueError('matcher_config not of type matcher_pb2.Matcher.')
if matcher_config.WhichOneof('matcher_oneof') == 'argmax_matcher':
matcher = matcher_config.argmax_matcher
matched_threshold = unmatched_threshold = None
if not matcher.ignore_thresholds:
matched_threshold = matcher.matched_threshold
unmatched_threshold = matcher.unmatched_threshold
return argmax_matcher.ArgMaxMatcher(
matched_threshold=matched_threshold,
unmatched_threshold=unmatched_threshold,
negatives_lower_than_unmatched=matcher.negatives_lower_than_unmatched,
force_match_for_each_row=matcher.force_match_for_each_row)
if matcher_config.WhichOneof('matcher_oneof') == 'bipartite_matcher':
return bipartite_matcher.GreedyBipartiteMatcher()
raise ValueError('Empty matcher.')
示例14: test_get_expected_matches_when_all_rows_are_valid
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_expected_matches_when_all_rows_are_valid(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
valid_rows = tf.ones([2], dtype=tf.bool)
expected_match_results = [-1, 1, 0]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix, valid_rows=valid_rows)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)
示例15: test_get_expected_matches_with_all_rows_be_default
# 需要导入模块: from object_detection.matchers import bipartite_matcher [as 别名]
# 或者: from object_detection.matchers.bipartite_matcher import GreedyBipartiteMatcher [as 别名]
def test_get_expected_matches_with_all_rows_be_default(self):
similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
expected_match_results = [-1, 1, 0]
matcher = bipartite_matcher.GreedyBipartiteMatcher()
match = matcher.match(similarity_matrix)
with self.test_session() as sess:
match_results_out = sess.run(match._match_results)
self.assertAllEqual(match_results_out, expected_match_results)