Watershed 2.2.2

请参阅模块API页面

https://engineering.purdue.edu/kak/distWatershed/Watershed-2.2.2.html

有关此模块的所有信息，包括代码的最新更改信息。上面显示的网页列出了您可以在自己的代码中调用的所有模块功能。该页面还描述了您如何直接访问自己的代码中的分割区域以及如何在分割之前对图像应用颜色过滤器。

关于模块的基本目的，它是对图像分割的watershed算法的Python实现。此实现允许对图像进行完全自动和标记辅助的分割。

典型使用语法

    from Watershed import *
    shed = Watershed(
               data_image = "orchid0001.jpg",
               binary_or_gray_or_color = "color",
               size_for_calculations = 128,
               sigma = 1,
               gradient_threshold_as_fraction = 0.1,
               level_decimation_factor = 16,
               padding = 20,
           )
    shed.extract_data_pixels()
    shed.display_data_image()
    shed.mark_image_regions_for_gradient_mods()                     #(A)
    shed.compute_gradient_image()
    shed.modify_gradients_with_marker_minima()                      #(B)
    shed.compute_Z_level_sets_for_gradient_image()
    shed.propagate_influence_zones_from_bottom_to_top_of_Z_levels()
    shed.display_watershed()
    shed.display_watershed_in_color()
    shed.extract_watershed_contours_seperated()
    shed.display_watershed_contours_in_color()

The statements in lines (A) and (B) are needed only for marker-assisted
segmentation with the module.  For a fully automated implemented of the
BLM algorithm, you would need to delete those two statements.