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Python box_predictor.MaskRCNNBoxPredictor方法代码示例

本文整理汇总了Python中object_detection.core.box_predictor.MaskRCNNBoxPredictor方法的典型用法代码示例。如果您正苦于以下问题:Python box_predictor.MaskRCNNBoxPredictor方法的具体用法?Python box_predictor.MaskRCNNBoxPredictor怎么用?Python box_predictor.MaskRCNNBoxPredictor使用的例子?那么恭喜您, 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object_detection.core.box_predictor的用法示例。


在下文中一共展示了box_predictor.MaskRCNNBoxPredictor方法的8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.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_boxes_with_five_classes(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        is_training=False,
        num_classes=5,
        fc_hyperparams=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')
    box_encodings = box_predictions[box_predictor.BOX_ENCODINGS]
    class_predictions_with_background = box_predictions[
        box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND]
    init_op = tf.global_variables_initializer()
    with self.test_session() as sess:
      sess.run(init_op)
      (box_encodings_shape,
       class_predictions_with_background_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [2, 1, 5, 4])
      self.assertAllEqual(class_predictions_with_background_shape, [2, 1, 6]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:26,代码来源:box_predictor_test.py

示例2: test_get_instance_masks

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_instance_masks(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        is_training=False,
        num_classes=5,
        fc_hyperparams=self._build_arg_scope_with_hyperparams(),
        use_dropout=False,
        dropout_keep_prob=0.5,
        box_code_size=4,
        conv_hyperparams=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')
    mask_predictions = box_predictions[box_predictor.MASK_PREDICTIONS]
    self.assertListEqual([2, 1, 5, 14, 14],
                         mask_predictions.get_shape().as_list()) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:19,代码来源:box_predictor_test.py

示例3: test_get_boxes_with_five_classes

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_boxes_with_five_classes(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        is_training=False,
        num_classes=5,
        fc_hyperparams=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')
    box_encodings = box_predictions[box_predictor.BOX_ENCODINGS]
    class_predictions_with_background = box_predictions[
        box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND]
    init_op = tf.global_variables_initializer()
    with self.test_session() as sess:
      sess.run(init_op)
      (box_encodings_shape,
       class_predictions_with_background_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [2, 1, 5, 4])
      self.assertAllEqual(class_predictions_with_background_shape, [2, 1, 6]) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:27,代码来源:box_predictor_test.py

示例4: test_get_instance_masks

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_instance_masks(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        is_training=False,
        num_classes=5,
        fc_hyperparams=self._build_arg_scope_with_hyperparams(),
        use_dropout=False,
        dropout_keep_prob=0.5,
        box_code_size=4,
        conv_hyperparams=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',
        predict_boxes_and_classes=True,
        predict_auxiliary_outputs=True)
    mask_predictions = box_predictions[box_predictor.MASK_PREDICTIONS]
    self.assertListEqual([2, 1, 5, 14, 14],
                         mask_predictions.get_shape().as_list()) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:23,代码来源:box_predictor_test.py

示例5: test_do_not_return_instance_masks_without_request

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [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.MaskRCNNBoxPredictor(
        is_training=False,
        num_classes=5,
        fc_hyperparams=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')
    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) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:18,代码来源:box_predictor_test.py

示例6: test_get_boxes_with_five_classes

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_boxes_with_five_classes(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        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')
    box_encodings = box_predictions[box_predictor.BOX_ENCODINGS]
    class_predictions_with_background = box_predictions[
        box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND]
    init_op = tf.global_variables_initializer()
    with self.test_session() as sess:
      sess.run(init_op)
      (box_encodings_shape,
       class_predictions_with_background_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [2, 1, 5, 4])
      self.assertAllEqual(class_predictions_with_background_shape, [2, 1, 6]) 
开发者ID:ambakick,项目名称:Person-Detection-and-Tracking,代码行数:27,代码来源:box_predictor_test.py

示例7: test_get_instance_masks

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [as 别名]
def test_get_instance_masks(self):
    image_features = tf.random_uniform([2, 7, 7, 3], dtype=tf.float32)
    mask_box_predictor = box_predictor.MaskRCNNBoxPredictor(
        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',
        predict_boxes_and_classes=True,
        predict_auxiliary_outputs=True)
    mask_predictions = box_predictions[box_predictor.MASK_PREDICTIONS]
    self.assertListEqual([2, 1, 5, 14, 14],
                         mask_predictions.get_shape().as_list()) 
开发者ID:ambakick,项目名称:Person-Detection-and-Tracking,代码行数:23,代码来源:box_predictor_test.py

示例8: test_do_not_return_instance_masks_without_request

# 需要导入模块: from object_detection.core import box_predictor [as 别名]
# 或者: from object_detection.core.box_predictor import MaskRCNNBoxPredictor [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.MaskRCNNBoxPredictor(
        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')
    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) 
开发者ID:ambakick,项目名称:Person-Detection-and-Tracking,代码行数:18,代码来源:box_predictor_test.py


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