Spatial Transformer Nets in TensorFlow/ TensorLayer

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Deep Learningdeep-learningtensorflowcnntensorflow-tutorialstensorlayerspatial-transformer-network
Overview

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Spatial Transformer Networks

Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or feature maps)including scaling, cropping, rotations, as well as non-rigid deformations. This enables the network to not only select regions of an image that are most relevant (attention), but also to transform those regions to simplify recognition in the following layers.

Video for different transformation click me.

In this repositary, we implemented a STN for 2D Affine Transformation on MNIST dataset. We generated images with size of 40x40 from the original MNIST dataset, and distorted the images by random rotation, shifting, shearing and zoom in/out. The STN was able to learn to automatically apply transformations on distorted images via classification task.


Fig 1：Transformation

Fig 2：Network

Fig 3：Formula

Result

After classification task, the STN is able to transform the distorted image from Fig 4 back to Fig 5.


Fig 4: Input

Fig 5: Output
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Comments
  • Export graph

    Export graph

    Hello,

    I'm trying to export this model and its weights into a frozen graph. So far I did this in the "save images" part of the training loop:

    saver = tf.train.Saver() saver.save(sess, 'my_stn_model_' + str(epoch)) tf.train.write_graph(sess.graph_def, ".", "test.pb", False) #proto

    Then I have my pb and the weights. But I am unable to generate a frozen graph from this because I cannot guess the output node in the graph (which is a really complex one it seems).

    I attached the pb which I am able to visualize using Netron:

    test.zip

    Thanks in advance.

    opened by hvico 0
  • Unexpected Output

    Unexpected Output

    I'm trying to train the STN. The training dataset which I've provided contains MNIST dataset images which are rotated 90 degree and the testing dataset contains simple MNIST dataset images. The output I'm getting is straight MNIST images. I was expecting the output to contain characters which are rotated 90 degrees. Can you please guide me on how this works?

    opened by nabeel3133 4
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Hao
Assistant Professor @ Peking University
Hao
GitHub Repository https://github.com/zsdonghao/tensorlayer
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