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Spatial Transformer Networks. Refer to daviddao/spatial-transformer-tensorflow.

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Tpatial-Transformer-Networks-pytorch

Statement

  • Do the Experiments on the cluttered MNIST dataset of daviddao.
  • The accuracy and loss records can be find in cnn.out & stn.out.
  • The transform img can be find in transform_img/.
  • py35_pytorch03_version contains the old version code

Environment

  • python3.6
  • pytorch 0.4.0

Accuracy

CNN

  • Testing: epoch[195/200] loss:0.5264 acc:0.9211
  • Testing: epoch[196/200] loss:0.5185 acc:0.9194
  • Testing: epoch[197/200] loss:0.5160 acc:0.9158
  • Testing: epoch[198/200] loss:0.5053 acc:0.9183
  • Testing: epoch[199/200] loss:0.5057 acc:0.9153

STN

  • Testing: epoch[195/200] loss:0.0880 acc:0.9762
  • Testing: epoch[196/200] loss:0.0961 acc:0.9757
  • Testing: epoch[197/200] loss:0.0893 acc:0.9742
  • Testing: epoch[198/200] loss:0.1015 acc:0.9740
  • Testing: epoch[199/200] loss:0.0938 acc:0.9738

Transform Image

(input|transform|input|transform)

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Spatial Transformer Networks. Refer to daviddao/spatial-transformer-tensorflow.

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