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Python box_predictor.RfcnBoxPredictor方法代码示例

本文整理汇总了Python中object_detection.core.box_predictor.RfcnBoxPredictor方法的典型用法代码示例。如果您正苦于以下问题:Python box_predictor.RfcnBoxPredictor方法的具体用法?Python box_predictor.RfcnBoxPredictor怎么用?Python box_predictor.RfcnBoxPredictor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object_detection.core.box_predictor的用法示例。


在下文中一共展示了box_predictor.RfcnBoxPredictor方法的4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_correct_box_encoding_and_class_prediction_shapes

# 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 RfcnBoxPredictor [as 别名]
def test_get_correct_box_encoding_and_class_prediction_shapes(self):
    image_features = tf.random_uniform([4, 8, 8, 64], dtype=tf.float32)
    proposal_boxes = tf.random_normal([4, 2, 4], dtype=tf.float32)
    rfcn_box_predictor = box_predictor.RfcnBoxPredictor(
        is_training=False,
        num_classes=2,
        conv_hyperparams=self._build_arg_scope_with_conv_hyperparams(),
        num_spatial_bins=[3, 3],
        depth=4,
        crop_size=[12, 12],
        box_code_size=4
    )
    box_predictions = rfcn_box_predictor.predict(
        image_features, num_predictions_per_location=1, scope='BoxPredictor',
        proposal_boxes=proposal_boxes)
    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_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [8, 1, 2, 4])
      self.assertAllEqual(class_predictions_shape, [8, 1, 3]) 
开发者ID:ringringyi,项目名称:DOTA_models,代码行数:30,代码来源:box_predictor_test.py

示例2: test_get_correct_box_encoding_and_class_prediction_shapes

# 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 RfcnBoxPredictor [as 别名]
def test_get_correct_box_encoding_and_class_prediction_shapes(self):
    image_features = tf.random_uniform([4, 8, 8, 64], dtype=tf.float32)
    proposal_boxes = tf.random_normal([4, 2, 4], dtype=tf.float32)
    rfcn_box_predictor = box_predictor.RfcnBoxPredictor(
        is_training=False,
        num_classes=2,
        conv_hyperparams=self._build_arg_scope_with_conv_hyperparams(),
        num_spatial_bins=[3, 3],
        depth=4,
        crop_size=[12, 12],
        box_code_size=4
    )
    box_predictions = rfcn_box_predictor.predict(
        [image_features], num_predictions_per_location=[1],
        scope='BoxPredictor',
        proposal_boxes=proposal_boxes)
    box_encodings = tf.concat(
        box_predictions[box_predictor.BOX_ENCODINGS], axis=1)
    class_predictions_with_background = tf.concat(
        box_predictions[box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND],
        axis=1)

    init_op = tf.global_variables_initializer()
    with self.test_session() as sess:
      sess.run(init_op)
      (box_encodings_shape,
       class_predictions_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [8, 1, 2, 4])
      self.assertAllEqual(class_predictions_shape, [8, 1, 3]) 
开发者ID:cagbal,项目名称:ros_people_object_detection_tensorflow,代码行数:33,代码来源:box_predictor_test.py

示例3: test_get_correct_box_encoding_and_class_prediction_shapes

# 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 RfcnBoxPredictor [as 别名]
def test_get_correct_box_encoding_and_class_prediction_shapes(self):
    image_features = tf.random_uniform([4, 8, 8, 64], dtype=tf.float32)
    proposal_boxes = tf.random_normal([4, 2, 4], dtype=tf.float32)
    rfcn_box_predictor = box_predictor.RfcnBoxPredictor(
        is_training=False,
        num_classes=2,
        conv_hyperparams_fn=self._build_arg_scope_with_conv_hyperparams(),
        num_spatial_bins=[3, 3],
        depth=4,
        crop_size=[12, 12],
        box_code_size=4
    )
    box_predictions = rfcn_box_predictor.predict(
        [image_features], num_predictions_per_location=[1],
        scope='BoxPredictor',
        proposal_boxes=proposal_boxes)
    box_encodings = tf.concat(
        box_predictions[box_predictor.BOX_ENCODINGS], axis=1)
    class_predictions_with_background = tf.concat(
        box_predictions[box_predictor.CLASS_PREDICTIONS_WITH_BACKGROUND],
        axis=1)

    init_op = tf.global_variables_initializer()
    with self.test_session() as sess:
      sess.run(init_op)
      (box_encodings_shape,
       class_predictions_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [8, 1, 2, 4])
      self.assertAllEqual(class_predictions_shape, [8, 1, 3]) 
开发者ID:ambakick,项目名称:Person-Detection-and-Tracking,代码行数:33,代码来源:box_predictor_test.py

示例4: test_get_correct_box_encoding_and_class_prediction_shapes

# 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 RfcnBoxPredictor [as 别名]
def test_get_correct_box_encoding_and_class_prediction_shapes(self):
    image_features = tf.random_uniform([4, 8, 8, 64], dtype=tf.float32)
    proposal_boxes = tf.random_normal([4, 2, 4], dtype=tf.float32)
    rfcn_box_predictor = box_predictor.RfcnBoxPredictor(
        is_training=False,
        num_classes=2,
        conv_hyperparams=self._build_arg_scope_with_conv_hyperparams(),
        num_spatial_bins=[3, 3],
        depth=4,
        crop_size=[12, 12],
        box_code_size=4
    )
    box_predictions = rfcn_box_predictor.predict(
        [image_features], num_predictions_per_location=[1],
        scope='BoxPredictor',
        proposal_boxes=proposal_boxes)
    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_shape) = sess.run(
           [tf.shape(box_encodings),
            tf.shape(class_predictions_with_background)])
      self.assertAllEqual(box_encodings_shape, [8, 1, 2, 4])
      self.assertAllEqual(class_predictions_shape, [8, 1, 3]) 
开发者ID:ShreyAmbesh,项目名称:Traffic-Rule-Violation-Detection-System,代码行数:31,代码来源:box_predictor_test.py


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