spatial_image_analysis.py 文件源码

def _neighbors_from_list_with_mask(self, labels, min_contact_area=None, real_area=True):
        if (not self._neighbors is None) and (sum([i in self._neighbors.keys() for i in labels])==len(labels)):
            result = dict([(i,self._neighbors[i]) for i in labels])
            if  min_contact_area is None:
                return result
            else:
                return self._filter_with_area(result, min_contact_area, real_area)

        edges = {}
        for label in labels:
            try:
                slices = self.boundingbox(label)
                ex_slices = dilation(slices)
                mask_img = self.image[ex_slices]
            except:
                mask_img = self.image
            neigh = list(contact_surface(mask_img,label))
            if min_contact_area is not None:
                neigh = self._neighbors_filtering_by_contact_area(label, neigh, min_contact_area, real_area)
            edges[label] = neigh

        return edges