dsdl.geometry.segmap

SegmentationMap

Bases: Image

A Geometry class for semantic segmentation map.

Source code in /Users/bin/anaconda3/envs/dsdl/lib/python3.10/site-packages/dsdl/geometry/segmap.py

class SegmentationMap(Image):
    """
    A Geometry class for semantic segmentation map.
    """

    def __init__(self, value, dom, file_reader):
        """A Geometry class which abstracts a semantic segmentation map object.

        Args:
            value: The relative path of the current semantic segmentation map image.
            file_reader: The file reader object of the current semantic segmentation map image.
            dom: The current semantic segmentation map's class domain.
        """
        super().__init__(value, file_reader)
        if isinstance(dom, list):
            assert len(dom) == 1, "You can only assign one class dom in LabelMapField."
            dom = dom[0]
        self._dom = dom

    @property
    def class_domain(self):
        """
        Returns:
            The current semantic segmentation map's class domain.
        """
        return self._dom

    def visualize(self, image, palette, **kwargs):
        """Draw the current semantic segmentation map on an given image.

        Args:
            image: The image where the semantic segmentation map to be drawn.
            palette: The palette which stores the color of different category name.
            **kwargs: Other annotations which may be used when drawing the current semantic segmentation map.

        Returns:
            The image where the current semantic segmentation map has been drawn on.
        """
        seg = self.to_array()
        color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)
        category_ids = np.unique(seg)
        if self.class_domain.__name__ == "_LabelMapDefaultDomain":
            category_ids = category_ids + 1
        label_lst = []
        for category_id in category_ids:
            if int(category_id) > len(self._dom) or int(category_id) < 1:
                continue
            label = self._dom.get_label(int(category_id))
            category_name = label.category_name
            if category_name not in palette:
                palette[category_name] = tuple(np.random.randint(0, 255, size=[3]))
            label_lst.append(label)
            color_seg[seg == category_id, :] = np.array(palette[category_name])
        overlay = Image_.fromarray(color_seg).convert("RGBA")
        overlayed = Image_.blend(image, overlay, 0.5)
        LabelList(label_lst).visualize(image=overlayed, palette=palette, bbox={"temp": BBox([0, 0, 0, 0])})
        return overlayed

class_domain property

Returns:

Type	Description
	The current semantic segmentation map's class domain.

__init__(value, dom, file_reader)

A Geometry class which abstracts a semantic segmentation map object.

Parameters:

Name	Type	Description	Default
value		The relative path of the current semantic segmentation map image.	required
file_reader		The file reader object of the current semantic segmentation map image.	required
dom		The current semantic segmentation map's class domain.	required

Source code in /Users/bin/anaconda3/envs/dsdl/lib/python3.10/site-packages/dsdl/geometry/segmap.py

def __init__(self, value, dom, file_reader):
    """A Geometry class which abstracts a semantic segmentation map object.

    Args:
        value: The relative path of the current semantic segmentation map image.
        file_reader: The file reader object of the current semantic segmentation map image.
        dom: The current semantic segmentation map's class domain.
    """
    super().__init__(value, file_reader)
    if isinstance(dom, list):
        assert len(dom) == 1, "You can only assign one class dom in LabelMapField."
        dom = dom[0]
    self._dom = dom

visualize(image, palette, **kwargs)

Draw the current semantic segmentation map on an given image.

Parameters:

Name	Type	Description	Default
image		The image where the semantic segmentation map to be drawn.	required
palette		The palette which stores the color of different category name.	required
**kwargs		Other annotations which may be used when drawing the current semantic segmentation map.	{}

Returns:

Type	Description
	The image where the current semantic segmentation map has been drawn on.

Source code in /Users/bin/anaconda3/envs/dsdl/lib/python3.10/site-packages/dsdl/geometry/segmap.py

def visualize(self, image, palette, **kwargs):
    """Draw the current semantic segmentation map on an given image.

    Args:
        image: The image where the semantic segmentation map to be drawn.
        palette: The palette which stores the color of different category name.
        **kwargs: Other annotations which may be used when drawing the current semantic segmentation map.

    Returns:
        The image where the current semantic segmentation map has been drawn on.
    """
    seg = self.to_array()
    color_seg = np.zeros((seg.shape[0], seg.shape[1], 3), dtype=np.uint8)
    category_ids = np.unique(seg)
    if self.class_domain.__name__ == "_LabelMapDefaultDomain":
        category_ids = category_ids + 1
    label_lst = []
    for category_id in category_ids:
        if int(category_id) > len(self._dom) or int(category_id) < 1:
            continue
        label = self._dom.get_label(int(category_id))
        category_name = label.category_name
        if category_name not in palette:
            palette[category_name] = tuple(np.random.randint(0, 255, size=[3]))
        label_lst.append(label)
        color_seg[seg == category_id, :] = np.array(palette[category_name])
    overlay = Image_.fromarray(color_seg).convert("RGBA")
    overlayed = Image_.blend(image, overlay, 0.5)
    LabelList(label_lst).visualize(image=overlayed, palette=palette, bbox={"temp": BBox([0, 0, 0, 0])})
    return overlayed