示例#1
0
    def templatesyncsegmSegmentation(self, image_source, radius_color,
                                     radius_object, noise_size,
                                     expected_color_segments,
                                     expected_object_segments,
                                     collect_dynamic):
        result_testing = False

        for _ in range(0, 5, 1):
            algorithm = syncsegm(radius_color, radius_object, noise_size)
            analyser = algorithm.process(image_source, collect_dynamic, 0.9995,
                                         0.9995)

            color_segments = analyser.allocate_colors()
            object_segments = analyser.allocate_objects(0.2)

            if ((len(color_segments) != expected_color_segments)
                    or (len(object_segments) != expected_object_segments)):
                continue

            if (collect_dynamic is True):
                syncsegm_visualizer.show_first_layer_dynamic(analyser)
                syncsegm_visualizer.show_second_layer_dynamic(analyser)

            result_testing = True
            break

        assert result_testing
 def templateSyncsegmVisulizationNoFailure(image_source, radius_color, radius_object, noise_size, expected_color_segments, expected_object_segments, collect_dynamic, ccore_flag):
     algorithm = syncsegm(radius_color, radius_object, noise_size, ccore=ccore_flag)
     analyser = algorithm.process(image_source, collect_dynamic, 0.9995, 0.9995)
     
     color_segments = analyser.allocate_colors(0.01, noise_size)
     draw_image_mask_segments(image_source, color_segments)
     
     object_segments = analyser.allocate_objects(0.01, noise_size)
     draw_image_mask_segments(image_source, object_segments)
     
     syncsegm_visualizer.show_first_layer_dynamic(analyser)
     syncsegm_visualizer.show_second_layer_dynamic(analyser)
 def templateSyncsegmVisulizationNoFailure(image_source, radius_color, radius_object, noise_size, expected_color_segments, expected_object_segments, collect_dynamic, ccore_flag):
     algorithm = syncsegm(radius_color, radius_object, noise_size, ccore=ccore_flag)
     analyser = algorithm.process(image_source, collect_dynamic, 0.9995, 0.9995)
     
     color_segments = analyser.allocate_colors(0.01, noise_size)
     draw_image_mask_segments(image_source, color_segments)
     
     object_segments = analyser.allocate_objects(0.01, noise_size)
     draw_image_mask_segments(image_source, object_segments)
     
     syncsegm_visualizer.show_first_layer_dynamic(analyser)
     syncsegm_visualizer.show_second_layer_dynamic(analyser)
def template_segmentation_image(source, color_radius, object_radius, noise_size, show_dyn):
    algorithm = syncsegm(color_radius, object_radius, noise_size, False)
    analyser = algorithm.process(source, show_dyn)
    
    color_segments = analyser.allocate_colors(0.01, noise_size)
    draw_image_mask_segments(source, color_segments)
    
    if object_radius is not None:
        object_segments = analyser.allocate_objects(0.01, noise_size)
        draw_image_mask_segments(source, object_segments)
    
    if show_dyn is True:
        syncsegm_visualizer.show_first_layer_dynamic(analyser)
        syncsegm_visualizer.show_second_layer_dynamic(analyser)
示例#5
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def template_segmentation_image(source, color_radius, object_radius,
                                noise_size, show_dyn):
    algorithm = syncsegm(color_radius, object_radius, noise_size)
    analyser = algorithm.process(source, show_dyn)

    color_segments = analyser.allocate_colors(0.01, noise_size)
    draw_image_mask_segments(source, color_segments)

    if (object_radius is not None):
        object_segments = analyser.allocate_objects(0.01, noise_size)
        draw_image_mask_segments(source, object_segments)

    if (show_dyn is True):
        syncsegm_visualizer.show_first_layer_dynamic(analyser)
        syncsegm_visualizer.show_second_layer_dynamic(analyser)
示例#6
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 def templatesyncsegmSegmentation(self, image_source, radius_color, radius_object, noise_size, expected_color_segments, expected_object_segments, collect_dynamic):
     result_testing = False;
     
     for _ in range(0, 3, 1):
         algorithm = syncsegm(radius_color, radius_object, noise_size);
         analyser = algorithm.process(image_source, collect_dynamic, 0.9995, 0.9995);
         
         color_segments = analyser.allocate_colors();
         object_segments = analyser.allocate_objects(0.2);
         
         if ( (len(color_segments) != expected_color_segments) or (len(object_segments) != expected_object_segments) ):
             continue;
         
         if (collect_dynamic is True):
             syncsegm_visualizer.show_first_layer_dynamic(analyser);
             syncsegm_visualizer.show_second_layer_dynamic(analyser);
         
         result_testing = True;
         break;
     
     assert result_testing;