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Python feature_pb2.FloatList方法代码示例

本文整理汇总了Python中tensorflow.core.example.feature_pb2.FloatList方法的典型用法代码示例。如果您正苦于以下问题：Python feature_pb2.FloatList方法的具体用法？Python feature_pb2.FloatList怎么用？Python feature_pb2.FloatList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tensorflow.core.example.feature_pb2的用法示例。


在下文中一共展示了feature_pb2.FloatList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: create_tf_record

# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import FloatList [as 别名]
def create_tf_record(self):
    path = os.path.join(self.get_temp_dir(), 'tfrecord')
    writer = tf.python_io.TFRecordWriter(path)

    image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
    with self.test_session():
      encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
    example = example_pb2.Example(features=feature_pb2.Features(feature={
        'image/encoded': feature_pb2.Feature(
            bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
        'image/format': feature_pb2.Feature(
            bytes_list=feature_pb2.BytesList(value=['jpeg'.encode('utf-8')])),
        'image/object/bbox/xmin': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/xmax': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/bbox/ymin': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/ymax': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/class/label': feature_pb2.Feature(
            int64_list=feature_pb2.Int64List(value=[2])),
    }))
    writer.write(example.SerializeToString())
    writer.close()

    return path
开发者ID:ringringyi，项目名称:DOTA_models，代码行数:29，代码来源:input_reader_builder_test.py

示例2: _EncodedFloatFeature

# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import FloatList [as 别名]
def _EncodedFloatFeature(self, ndarray):
    return feature_pb2.Feature(float_list=feature_pb2.FloatList(
        value=ndarray.flatten().tolist()))
开发者ID:abhisuri97，项目名称:auto-alt-text-lambda-api，代码行数:5，代码来源:tfexample_decoder_test.py

示例3: create_tf_record

# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import FloatList [as 别名]
def create_tf_record(self):
    path = os.path.join(self.get_temp_dir(), 'tfrecord')
    writer = tf.python_io.TFRecordWriter(path)

    image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
    flat_mask = (4 * 5) * [1.0]
    with self.test_session():
      encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
    example = example_pb2.Example(features=feature_pb2.Features(feature={
        'image/encoded': feature_pb2.Feature(
            bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
        'image/format': feature_pb2.Feature(
            bytes_list=feature_pb2.BytesList(value=['jpeg'.encode('utf-8')])),
        'image/height': feature_pb2.Feature(
            int64_list=feature_pb2.Int64List(value=[4])),
        'image/width': feature_pb2.Feature(
            int64_list=feature_pb2.Int64List(value=[5])),
        'image/object/bbox/xmin': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/xmax': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/bbox/ymin': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/ymax': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/class/label': feature_pb2.Feature(
            int64_list=feature_pb2.Int64List(value=[2])),
        'image/object/mask': feature_pb2.Feature(
            float_list=feature_pb2.FloatList(value=flat_mask)),
    }))
    writer.write(example.SerializeToString())
    writer.close()

    return path
开发者ID:cagbal，项目名称:ros_people_object_detection_tensorflow，代码行数:36，代码来源:input_reader_builder_test.py

示例4: create_tf_record

# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import FloatList [as 别名]
def create_tf_record(self):
    path = os.path.join(self.get_temp_dir(), 'tfrecord')
    writer = tf.python_io.TFRecordWriter(path)

    image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
    flat_mask = (4 * 5) * [1.0]
    with self.test_session():
      encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
    example = example_pb2.Example(
        features=feature_pb2.Features(
            feature={
                'image/encoded':
                    feature_pb2.Feature(
                        bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
                'image/format':
                    feature_pb2.Feature(
                        bytes_list=feature_pb2.BytesList(
                            value=['jpeg'.encode('utf-8')])),
                'image/height':
                    feature_pb2.Feature(
                        int64_list=feature_pb2.Int64List(value=[4])),
                'image/width':
                    feature_pb2.Feature(
                        int64_list=feature_pb2.Int64List(value=[5])),
                'image/object/bbox/xmin':
                    feature_pb2.Feature(
                        float_list=feature_pb2.FloatList(value=[0.0])),
                'image/object/bbox/xmax':
                    feature_pb2.Feature(
                        float_list=feature_pb2.FloatList(value=[1.0])),
                'image/object/bbox/ymin':
                    feature_pb2.Feature(
                        float_list=feature_pb2.FloatList(value=[0.0])),
                'image/object/bbox/ymax':
                    feature_pb2.Feature(
                        float_list=feature_pb2.FloatList(value=[1.0])),
                'image/object/class/label':
                    feature_pb2.Feature(
                        int64_list=feature_pb2.Int64List(value=[2])),
                'image/object/mask':
                    feature_pb2.Feature(
                        float_list=feature_pb2.FloatList(value=flat_mask)),
            }))
    writer.write(example.SerializeToString())
    writer.close()

    return path
开发者ID:cagbal，项目名称:ros_people_object_detection_tensorflow，代码行数:49，代码来源:dataset_builder_test.py

示例5: create_tf_record

# 需要导入模块: from tensorflow.core.example import feature_pb2 [as 别名]
# 或者: from tensorflow.core.example.feature_pb2 import FloatList [as 别名]
def create_tf_record(self, has_additional_channels=False):
    path = os.path.join(self.get_temp_dir(), 'tfrecord')
    writer = tf.python_io.TFRecordWriter(path)

    image_tensor = np.random.randint(255, size=(4, 5, 3)).astype(np.uint8)
    additional_channels_tensor = np.random.randint(
        255, size=(4, 5, 1)).astype(np.uint8)
    flat_mask = (4 * 5) * [1.0]
    with self.test_session():
      encoded_jpeg = tf.image.encode_jpeg(tf.constant(image_tensor)).eval()
      encoded_additional_channels_jpeg = tf.image.encode_jpeg(
          tf.constant(additional_channels_tensor)).eval()
    features = {
        'image/encoded':
            feature_pb2.Feature(
                bytes_list=feature_pb2.BytesList(value=[encoded_jpeg])),
        'image/format':
            feature_pb2.Feature(
                bytes_list=feature_pb2.BytesList(value=['jpeg'.encode('utf-8')])
            ),
        'image/height':
            feature_pb2.Feature(int64_list=feature_pb2.Int64List(value=[4])),
        'image/width':
            feature_pb2.Feature(int64_list=feature_pb2.Int64List(value=[5])),
        'image/object/bbox/xmin':
            feature_pb2.Feature(float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/xmax':
            feature_pb2.Feature(float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/bbox/ymin':
            feature_pb2.Feature(float_list=feature_pb2.FloatList(value=[0.0])),
        'image/object/bbox/ymax':
            feature_pb2.Feature(float_list=feature_pb2.FloatList(value=[1.0])),
        'image/object/class/label':
            feature_pb2.Feature(int64_list=feature_pb2.Int64List(value=[2])),
        'image/object/mask':
            feature_pb2.Feature(
                float_list=feature_pb2.FloatList(value=flat_mask)),
    }
    if has_additional_channels:
      features['image/additional_channels/encoded'] = feature_pb2.Feature(
          bytes_list=feature_pb2.BytesList(
              value=[encoded_additional_channels_jpeg] * 2))
    example = example_pb2.Example(
        features=feature_pb2.Features(feature=features))
    writer.write(example.SerializeToString())
    writer.close()

    return path
开发者ID:ambakick，项目名称:Person-Detection-and-Tracking，代码行数:50，代码来源:dataset_builder_test.py


注：本文中的tensorflow.core.example.feature_pb2.FloatList方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。