from?keras.layers.core?import?layer
import?tensorflow?as?tf

class?SpatialTransformer（layer）:
????“““Spatial?Transformer?layer
????Implements?a?spatial?transformer?layer?as?described?in?[1]_.
????Borrowed?from?[2]_:
????downsample_fator?:?float
????????A?value?of?1?will?keep?the?orignal?size?of?the?image.
????????Values?larger?than?1?will?down?sample?the?image.?Values?below?1?will
????????upsample?the?image.
????????example?image:?height=?100?width?=?200
????????downsample_factor?=?2
????????output?image?will?then?be?50?100
????References
????----------
????..?[1]??Spatial?Transformer?Networks
????????????Max?Jaderberg?Karen?Simonyan?Andrew?Zisserman?Koray?Kavukcuoglu
????????????Submitted?on?5?Jun?2015
????..?[2]??https://github.com/skaae/transformer_network/blob/master/transformerlayer.py

????..?[3]??https://github.com/EderSantana/seya/blob/keras1/seya/layers/attention.py
????“““

????def?__init__（self
?????????????????localization_net
?????????????????output_size
?????????????????**kwargs）:
????????self.locnet?=?localization_net
????????self.output_size?=?output_size
????????super（SpatialTransformer?self）.__init__（**kwargs）

????def?build（self?input_shape）:
????????self.locnet.build（input_shape）
????????self.trainable_weights?=?self.locnet.trainable_weights
????????#self.regularizers?=?self.locnet.regularizers?//NOT?SUER?ABOUT?THIS?THERE?IS?NO?MORE?SUCH?PARAMETR?AT?self.locnet
????????self.constraints?=?self.locnet.constraints

????def?compute_output_shape（self?input_shape）:
????????output_size?=?self.output_size
????????return?（None
????????????????int（output_size[0]）
????????????????int（output_size[1]）
????????????????int（input_shape[-1]））

????def?call（self?X?mask=None）:
????????affine_transformation?=?self.locnet.call（X）
????????output?=?self._transform（affine_transformation?X?self.output_size）
????????return?output

????def?_repeat（self?x?num_repeats）:
????????ones?=?tf.ones（（1?num_repeats）?dtype=‘int32‘）
????????x?=?tf.reshape（x?shape=（-11））
????????x?=?tf.matmul（x?ones）
????????return?tf.reshape（x?[-1]）

????def?_interpolate（self?image?x?y?output_size）:
????????batch_size?=?tf.shape（image）[0]
????????height?=?tf.shape（image）[1]
????????width?=?tf.shape（image）[2]
????????num_channels?=?tf.shape（image）[3]

????????x?=?tf.cast（x??dtype=‘float32‘）
????????y?=?tf.cast（y??dtype=‘float32‘）

????????height_float?=?tf.cast（height?dtype=‘float32‘）
????????width_float?=?tf.cast（width?dtype=‘float32‘）

????????output_height?=?output_size[0]
????????output_width??=?output_size[1]

????????x?=?.5*（x?+?1.0）*（width_float）
????????y?=?.5*（y?+?1.0）*（height_float）

????????x0?=?tf.cast（tf.floor（x）?‘int32‘）
????????x1?=?x0?+?1
????????y0?=?tf.cast（tf.floor（y）?‘int32‘）
????????y1?=?y0?+?1

????????max_y?=?tf.cast（height?-?1?dtype=‘int32‘）
????????max_x?=?tf.cast（width?-?1??dtype=‘int32‘）
????????zero?=?tf.zeros（[]?dtype=‘int32‘）

????????x0?=?tf.clip_by_value（x0?zero?max_x）
????????x1?=?tf.clip_by_value（x1?zero?m

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2019-01-02?21:02??spatial_transformer（注意力模型）\
?????目錄???????????0??2018-01-24?13:13??spatial_transformer（注意力模型）\.ipynb_checkpoints\
?????文件??????132831??2018-01-24?13:13??spatial_transformer（注意力模型）\.ipynb_checkpoints\Attention實例-Spatial?Transformer-checkpoint.ipynb
?????文件???????89843??2019-01-02?21:02??spatial_transformer（注意力模型）\Attention實例-Spatial?Transformer.ipynb
?????文件????43046126??2018-01-24?13:14??spatial_transformer（注意力模型）\mnist_cluttered_60x60_6distortions.npz
?????文件????????6851??2018-01-24?13:13??spatial_transformer（注意力模型）\spatial_transformer.py
?????文件??????182198??2018-01-24?13:14??spatial_transformer（注意力模型）\st_cnn.png
?????目錄???????????0??2018-01-24?13:13??spatial_transformer（注意力模型）\__pycache__\
?????文件????????5093??2018-01-24?13:13??spatial_transformer（注意力模型）\__pycache__\spatial_transformer.cpython-36.pyc