本文整理汇总了Python中object_detection.builders.box_predictor_builder.build_mask_rcnn_box_predictor方法的典型用法代码示例。如果您正苦于以下问题：Python box_predictor_builder.build_mask_rcnn_box_predictor方法的具体用法？Python box_predictor_builder.build_mask_rcnn_box_predictor怎么用？Python box_predictor_builder.build_mask_rcnn_box_predictor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.builders.box_predictor_builder的用法示例。
在下文中一共展示了box_predictor_builder.build_mask_rcnn_box_predictor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_get_boxes_with_five_classes
# 需要导入模块: from object_detection.builders import box_predictor_builder [as 别名]
# 或者: from object_detection.builders.box_predictor_builder import build_mask_rcnn_box_predictor [as 别名]
def test_get_boxes_with_five_classes(self):
def graph_fn(image_features):
mask_box_predictor = box_predictor_builder.build_mask_rcnn_box_predictor(
is_training=False,
num_classes=5,
fc_hyperparams_fn=self._build_arg_scope_with_hyperparams(),
use_dropout=False,
dropout_keep_prob=0.5,
box_code_size=4,
)
box_predictions = mask_box_predictor.predict(
[image_features],
num_predictions_per_location=[1],
scope='BoxPredictor',
prediction_stage=2)
return (box_predictions[box_predictor.BOX_ENCODINGS],
box_predictions[box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND])
image_features = np.random.rand(2, 7, 7, 3).astype(np.float32)
(box_encodings,
class_predictions_with_background) = self.execute(graph_fn,
[image_features])
self.assertAllEqual(box_encodings.shape, [2, 1, 5, 4])
self.assertAllEqual(class_predictions_with_background.shape, [2, 1, 6]) 示例2: test_get_boxes_with_five_classes_share_box_across_classes
# 需要导入模块: from object_detection.builders import box_predictor_builder [as 别名]
# 或者: from object_detection.builders.box_predictor_builder import build_mask_rcnn_box_predictor [as 别名]
def test_get_boxes_with_five_classes_share_box_across_classes(self):
def graph_fn(image_features):
mask_box_predictor = box_predictor_builder.build_mask_rcnn_box_predictor(
is_training=False,
num_classes=5,
fc_hyperparams_fn=self._build_arg_scope_with_hyperparams(),
use_dropout=False,
dropout_keep_prob=0.5,
box_code_size=4,
share_box_across_classes=True
)
box_predictions = mask_box_predictor.predict(
[image_features],
num_predictions_per_location=[1],
scope='BoxPredictor',
prediction_stage=2)
return (box_predictions[box_predictor.BOX_ENCODINGS],
box_predictions[box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND])
image_features = np.random.rand(2, 7, 7, 3).astype(np.float32)
(box_encodings,
class_predictions_with_background) = self.execute(graph_fn,
[image_features])
self.assertAllEqual(box_encodings.shape, [2, 1, 1, 4])
self.assertAllEqual(class_predictions_with_background.shape, [2, 1, 6]) 示例3: test_get_instance_masks
# 需要导入模块: from object_detection.builders import box_predictor_builder [as 别名]
# 或者: from object_detection.builders.box_predictor_builder import build_mask_rcnn_box_predictor [as 别名]
def test_get_instance_masks(self):
def graph_fn(image_features):
mask_box_predictor = box_predictor_builder.build_mask_rcnn_box_predictor(
is_training=False,
num_classes=5,
fc_hyperparams_fn=self._build_arg_scope_with_hyperparams(),
use_dropout=False,
dropout_keep_prob=0.5,
box_code_size=4,
conv_hyperparams_fn=self._build_arg_scope_with_hyperparams(
op_type=hyperparams_pb2.Hyperparams.CONV),
predict_instance_masks=True)
box_predictions = mask_box_predictor.predict(
[image_features],
num_predictions_per_location=[1],
scope='BoxPredictor',
prediction_stage=3)
return (box_predictions[box_predictor.MASK_PREDICTIONS],)
image_features = np.random.rand(2, 7, 7, 3).astype(np.float32)
mask_predictions = self.execute(graph_fn, [image_features])
self.assertAllEqual(mask_predictions.shape, [2, 1, 5, 14, 14]) 示例4: test_do_not_return_instance_masks_without_request
# 需要导入模块: from object_detection.builders import box_predictor_builder [as 别名]
# 或者: from object_detection.builders.box_predictor_builder import build_mask_rcnn_box_predictor [as 别名]
def test_do_not_return_instance_masks_without_request(self):
image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
mask_box_predictor = box_predictor_builder.build_mask_rcnn_box_predictor(
is_training=False,
num_classes=5,
fc_hyperparams_fn=self._build_arg_scope_with_hyperparams(),
use_dropout=False,
dropout_keep_prob=0.5,
box_code_size=4)
box_predictions = mask_box_predictor.predict(
[image_features],
num_predictions_per_location=[1],
scope='BoxPredictor',
prediction_stage=2)
self.assertEqual(len(box_predictions), 2)
self.assertTrue(box_predictor.BOX_ENCODINGS in box_predictions)
self.assertTrue(box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND
in box_predictions) 示例5: test_value_error_on_predict_instance_masks_with_no_conv_hyperparms
# 需要导入模块: from object_detection.builders import box_predictor_builder [as 别名]
# 或者: from object_detection.builders.box_predictor_builder import build_mask_rcnn_box_predictor [as 别名]
def test_value_error_on_predict_instance_masks_with_no_conv_hyperparms(self):
with self.assertRaises(ValueError):
box_predictor_builder.build_mask_rcnn_box_predictor(
is_training=False,
num_classes=5,
fc_hyperparams_fn=self._build_arg_scope_with_hyperparams(),
use_dropout=False,
dropout_keep_prob=0.5,
box_code_size=4,
predict_instance_masks=True)