本文整理匯總了Python中object_detection.protos.box_predictor_pb2.BoxPredictor方法的典型用法代碼示例。如果您正苦於以下問題:Python box_predictor_pb2.BoxPredictor方法的具體用法?Python box_predictor_pb2.BoxPredictor怎麽用?Python box_predictor_pb2.BoxPredictor使用的例子?那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類object_detection.protos.box_predictor_pb2
的用法示例。
在下文中一共展示了box_predictor_pb2.BoxPredictor方法的15個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_build_default_mask_rcnn_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_build_default_mask_rcnn_box_predictor(self):
box_predictor_proto = box_predictor_pb2.BoxPredictor()
box_predictor_proto.mask_rcnn_box_predictor.fc_hyperparams.op = (
hyperparams_pb2.Hyperparams.FC)
box_predictor = box_predictor_builder.build(
argscope_fn=mock.Mock(return_value='arg_scope'),
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertFalse(box_predictor._use_dropout)
self.assertAlmostEqual(box_predictor._dropout_keep_prob, 0.5)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertEqual(box_predictor._box_code_size, 4)
self.assertFalse(box_predictor._predict_instance_masks)
self.assertFalse(box_predictor._predict_keypoints)
示例2: _get_second_stage_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def _get_second_stage_box_predictor(self, num_classes, is_training,
predict_masks, masks_are_class_agnostic):
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(self._get_second_stage_box_predictor_text_proto(),
box_predictor_proto)
if predict_masks:
text_format.Merge(
self._add_mask_to_second_stage_box_predictor_text_proto(
masks_are_class_agnostic),
box_predictor_proto)
return box_predictor_builder.build(
hyperparams_builder.build,
box_predictor_proto,
num_classes=num_classes,
is_training=is_training)
示例3: build_score_converter
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def build_score_converter(score_converter_config, is_training):
"""Builds score converter based on the config.
Builds one of [tf.identity, tf.sigmoid] score converters based on the config
and whether the BoxPredictor is for training or inference.
Args:
score_converter_config:
box_predictor_pb2.WeightSharedConvolutionalBoxPredictor.score_converter.
is_training: Indicates whether the BoxPredictor is in training mode.
Returns:
Callable score converter op.
Raises:
ValueError: On unknown score converter.
"""
if score_converter_config == (
box_predictor_pb2.WeightSharedConvolutionalBoxPredictor.IDENTITY):
return tf.identity
if score_converter_config == (
box_predictor_pb2.WeightSharedConvolutionalBoxPredictor.SIGMOID):
return tf.identity if is_training else tf.sigmoid
raise ValueError('Unknown score converter.')
示例4: test_build_default_mask_rcnn_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_build_default_mask_rcnn_box_predictor(self):
box_predictor_proto = box_predictor_pb2.BoxPredictor()
box_predictor_proto.mask_rcnn_box_predictor.fc_hyperparams.op = (
hyperparams_pb2.Hyperparams.FC)
box_predictor = box_predictor_builder.build(
argscope_fn=mock.Mock(return_value='arg_scope'),
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
box_head = box_predictor._box_prediction_head
class_head = box_predictor._class_prediction_head
self.assertFalse(box_head._use_dropout)
self.assertFalse(class_head._use_dropout)
self.assertAlmostEqual(box_head._dropout_keep_prob, 0.5)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertEqual(box_head._box_code_size, 4)
self.assertEqual(len(box_predictor._third_stage_heads.keys()), 0)
示例5: test_construct_default_conv_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_default_conv_box_predictor(self):
box_predictor_text_proto = """
weight_shared_convolutional_box_predictor {
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertEqual(box_predictor._depth, 0)
self.assertEqual(box_predictor._num_layers_before_predictor, 0)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
示例6: _get_second_stage_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def _get_second_stage_box_predictor(self, num_classes, is_training):
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(self._get_second_stage_box_predictor_text_proto(),
box_predictor_proto)
return box_predictor_builder.build(
hyperparams_builder.build,
box_predictor_proto,
num_classes=num_classes,
is_training=is_training)
示例7: test_construct_default_conv_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_default_conv_box_predictor(self):
box_predictor_text_proto = """
convolutional_box_predictor {
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertEqual(box_predictor._min_depth, 0)
self.assertEqual(box_predictor._max_depth, 0)
self.assertEqual(box_predictor._num_layers_before_predictor, 0)
self.assertTrue(box_predictor._use_dropout)
self.assertAlmostEqual(box_predictor._dropout_keep_prob, 0.8)
self.assertFalse(box_predictor._apply_sigmoid_to_scores)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
示例8: test_box_predictor_builder_calls_fc_argscope_fn
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_box_predictor_builder_calls_fc_argscope_fn(self):
fc_hyperparams_text_proto = """
regularizer {
l1_regularizer {
weight: 0.0003
}
}
initializer {
truncated_normal_initializer {
mean: 0.0
stddev: 0.3
}
}
activation: RELU_6
op: FC
"""
hyperparams_proto = hyperparams_pb2.Hyperparams()
text_format.Merge(fc_hyperparams_text_proto, hyperparams_proto)
box_predictor_proto = box_predictor_pb2.BoxPredictor()
box_predictor_proto.mask_rcnn_box_predictor.fc_hyperparams.CopyFrom(
hyperparams_proto)
mock_argscope_fn = mock.Mock(return_value='arg_scope')
box_predictor = box_predictor_builder.build(
argscope_fn=mock_argscope_fn,
box_predictor_config=box_predictor_proto,
is_training=False,
num_classes=10)
mock_argscope_fn.assert_called_with(hyperparams_proto, False)
self.assertEqual(box_predictor._fc_hyperparams, 'arg_scope')
示例9: test_build_box_predictor_with_mask_branch
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_build_box_predictor_with_mask_branch(self):
box_predictor_proto = box_predictor_pb2.BoxPredictor()
box_predictor_proto.mask_rcnn_box_predictor.fc_hyperparams.op = (
hyperparams_pb2.Hyperparams.FC)
box_predictor_proto.mask_rcnn_box_predictor.conv_hyperparams.op = (
hyperparams_pb2.Hyperparams.CONV)
box_predictor_proto.mask_rcnn_box_predictor.predict_instance_masks = True
box_predictor_proto.mask_rcnn_box_predictor.mask_prediction_conv_depth = 512
mock_argscope_fn = mock.Mock(return_value='arg_scope')
box_predictor = box_predictor_builder.build(
argscope_fn=mock_argscope_fn,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
mock_argscope_fn.assert_has_calls(
[mock.call(box_predictor_proto.mask_rcnn_box_predictor.fc_hyperparams,
True),
mock.call(box_predictor_proto.mask_rcnn_box_predictor.conv_hyperparams,
True)], any_order=True)
self.assertFalse(box_predictor._use_dropout)
self.assertAlmostEqual(box_predictor._dropout_keep_prob, 0.5)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertEqual(box_predictor._box_code_size, 4)
self.assertTrue(box_predictor._predict_instance_masks)
self.assertEqual(box_predictor._mask_prediction_conv_depth, 512)
self.assertFalse(box_predictor._predict_keypoints)
示例10: test_non_default_rfcn_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_non_default_rfcn_box_predictor(self):
conv_hyperparams_text_proto = """
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
activation: RELU_6
"""
box_predictor_text_proto = """
rfcn_box_predictor {
num_spatial_bins_height: 4
num_spatial_bins_width: 4
depth: 4
box_code_size: 3
crop_height: 16
crop_width: 16
}
"""
hyperparams_proto = hyperparams_pb2.Hyperparams()
text_format.Merge(conv_hyperparams_text_proto, hyperparams_proto)
def mock_conv_argscope_builder(conv_hyperparams_arg, is_training):
return (conv_hyperparams_arg, is_training)
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor_proto.rfcn_box_predictor.conv_hyperparams.CopyFrom(
hyperparams_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=mock_conv_argscope_builder,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertEqual(box_predictor._box_code_size, 3)
self.assertEqual(box_predictor._num_spatial_bins, [4, 4])
self.assertEqual(box_predictor._crop_size, [16, 16])
示例11: test_default_rfcn_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_default_rfcn_box_predictor(self):
conv_hyperparams_text_proto = """
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
activation: RELU_6
"""
hyperparams_proto = hyperparams_pb2.Hyperparams()
text_format.Merge(conv_hyperparams_text_proto, hyperparams_proto)
def mock_conv_argscope_builder(conv_hyperparams_arg, is_training):
return (conv_hyperparams_arg, is_training)
box_predictor_proto = box_predictor_pb2.BoxPredictor()
box_predictor_proto.rfcn_box_predictor.conv_hyperparams.CopyFrom(
hyperparams_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=mock_conv_argscope_builder,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertEqual(box_predictor._box_code_size, 4)
self.assertEqual(box_predictor._num_spatial_bins, [3, 3])
self.assertEqual(box_predictor._crop_size, [12, 12])
示例12: test_construct_default_conv_box_predictor
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_default_conv_box_predictor(self):
box_predictor_text_proto = """
convolutional_box_predictor {
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
class_head = box_predictor._class_prediction_head
self.assertEqual(box_predictor._min_depth, 0)
self.assertEqual(box_predictor._max_depth, 0)
self.assertEqual(box_predictor._num_layers_before_predictor, 0)
self.assertTrue(class_head._use_dropout)
self.assertAlmostEqual(class_head._dropout_keep_prob, 0.8)
self.assertFalse(class_head._apply_sigmoid_to_scores)
self.assertEqual(class_head._num_class_slots, 91)
self.assertEqual(box_predictor.num_classes, 90)
self.assertTrue(box_predictor._is_training)
self.assertFalse(class_head._use_depthwise)
示例13: test_construct_default_conv_box_predictor_with_custom_mask_head
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_default_conv_box_predictor_with_custom_mask_head(self):
box_predictor_text_proto = """
convolutional_box_predictor {
mask_head {
mask_height: 7
mask_width: 7
masks_are_class_agnostic: false
}
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertTrue(convolutional_box_predictor.MASK_PREDICTIONS in
box_predictor._other_heads)
mask_prediction_head = (
box_predictor._other_heads[convolutional_box_predictor.MASK_PREDICTIONS]
)
self.assertEqual(mask_prediction_head._mask_height, 7)
self.assertEqual(mask_prediction_head._mask_width, 7)
self.assertFalse(mask_prediction_head._masks_are_class_agnostic)
示例14: test_construct_weight_shared_predictor_with_default_mask_head
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_weight_shared_predictor_with_default_mask_head(self):
box_predictor_text_proto = """
weight_shared_convolutional_box_predictor {
mask_head {
}
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertTrue(convolutional_box_predictor.MASK_PREDICTIONS in
box_predictor._other_heads)
weight_shared_convolutional_mask_head = (
box_predictor._other_heads[convolutional_box_predictor.MASK_PREDICTIONS]
)
self.assertIsInstance(weight_shared_convolutional_mask_head,
mask_head.WeightSharedConvolutionalMaskHead)
self.assertEqual(weight_shared_convolutional_mask_head._mask_height, 15)
self.assertEqual(weight_shared_convolutional_mask_head._mask_width, 15)
self.assertTrue(
weight_shared_convolutional_mask_head._masks_are_class_agnostic)
示例15: test_construct_weight_shared_predictor_with_custom_mask_head
# 需要導入模塊: from object_detection.protos import box_predictor_pb2 [as 別名]
# 或者: from object_detection.protos.box_predictor_pb2 import BoxPredictor [as 別名]
def test_construct_weight_shared_predictor_with_custom_mask_head(self):
box_predictor_text_proto = """
weight_shared_convolutional_box_predictor {
mask_head {
mask_height: 7
mask_width: 7
masks_are_class_agnostic: false
}
conv_hyperparams {
regularizer {
l1_regularizer {
}
}
initializer {
truncated_normal_initializer {
}
}
}
}"""
box_predictor_proto = box_predictor_pb2.BoxPredictor()
text_format.Merge(box_predictor_text_proto, box_predictor_proto)
box_predictor = box_predictor_builder.build(
argscope_fn=hyperparams_builder.build,
box_predictor_config=box_predictor_proto,
is_training=True,
num_classes=90)
self.assertTrue(convolutional_box_predictor.MASK_PREDICTIONS in
box_predictor._other_heads)
weight_shared_convolutional_mask_head = (
box_predictor._other_heads[convolutional_box_predictor.MASK_PREDICTIONS]
)
self.assertIsInstance(weight_shared_convolutional_mask_head,
mask_head.WeightSharedConvolutionalMaskHead)
self.assertEqual(weight_shared_convolutional_mask_head._mask_height, 7)
self.assertEqual(weight_shared_convolutional_mask_head._mask_width, 7)
self.assertFalse(
weight_shared_convolutional_mask_head._masks_are_class_agnostic)