xlearn.transform

Module containing model, predict and train routines

Functions:

model(dim_img, nb_filters, nb_conv) the cnn model for image transformation
train(img_x, img_y, patch_size, patch_step, …) Function description.
predict(mdl, img, patch_size, patch_step, …) the cnn model for image transformation
xlearn.transform.model(dim_img, nb_filters, nb_conv)[source]

the cnn model for image transformation

Parameters:
  • dim_img (int) – The input image dimension
  • nb_filters (int) – Number of filters
  • nb_conv (int) – The convolution weight dimension
Returns:

mdl – Description.

xlearn.transform.train(img_x, img_y, patch_size, patch_step, dim_img, nb_filters, nb_conv, batch_size, nb_epoch)[source]

Function description.

Parameters:
  • parameter_01 (type) – Description.
  • parameter_02 (type) – Description.
  • parameter_03 (type) – Description.
Returns:

return_01 – Description.

xlearn.transform.predict(mdl, img, patch_size, patch_step, batch_size, dim_img)[source]

the cnn model for image transformation

Parameters:
  • img (array) – The image need to be calculated
  • patch_size ((int, int)) – The patches dimension
  • dim_img (int) – The input image dimension
Returns:

img_rec – Description.