niftynet.engine.sampler_grid module

Sampling image by a sliding window.

class GridSampler(reader, data_param, batch_size, spatial_window_size=(), window_border=(), queue_length=10)[source]

Bases: niftynet.layer.base_layer.Layer, niftynet.engine.image_window_buffer.InputBatchQueueRunner

This class generators ND image samples with a sliding window.

layer_op()[source]
grid_spatial_coordinates(subject_id, img_sizes, win_sizes, border_size)[source]

This function generates all coordinates of feasible windows, with step sizes specified in grid_size parameter.

The border size changes the sampling locations but not the corresponding window sizes of the coordinates.

Parameters:
  • subject_id – integer value indicates the position of of this image in image_reader.file_list
  • img_sizes – a dictionary of image shapes, {input_name: shape}
  • win_sizes – a dictionary of window shapes, {input_name: shape}
  • border_size – size of padding on both sides of each dim
Returns: