def get_effective_nonoverlapping_masks(geometries, img_size=None):
'''
Find nonoverlapping objects from given list of geometries
:param geometries: list of geometry type objects(Point, Polygon, PolyLine, Bitmap etc.)
:param img_size: tuple or list of integers
:return: list of bitmaps, numpy array
'''
if img_size is None:
if len(geometries) > 0:
common_bbox = Rectangle.from_geometries_list(geometries)
img_size = (common_bbox.bottom + 1, common_bbox.right + 1)
else:
img_size = (0, 0)
canvas = np.full(shape=img_size,
fill_value=len(geometries),
dtype=np.int32)
for idx, geometry in enumerate(geometries):
geometry.draw(canvas, color=idx)
result_masks = []
for idx, geometry in enumerate(geometries):
effective_indicator = (canvas == idx)
if np.any(effective_indicator):
result_masks.append(Bitmap(effective_indicator))
else:
result_masks.append(None)
return result_masks, canvas
def to_bbox(self):
'''
The function to_bbox create Rectangle class object from current GraphNodes class object
:return: Rectangle class object
'''
return Rectangle.from_geometries_list(
[Point.from_point_location(node.location) for node in self._nodes.values()])
def get_geometries_iou(geometry_1: Geometry, geometry_2: Geometry):
if isinstance(geometry_1, Rectangle):
return get_iou_rect(geometry_1, geometry_2)
elif isinstance(geometry_2, Rectangle):
return get_iou_rect(geometry_2, geometry_1)
else:
common_bbox = Rectangle.from_geometries_list((geometry_1, geometry_2))
g1 = geometry_1.relative_crop(common_bbox)[0]
g2 = geometry_2.relative_crop(common_bbox)[0]
mask_1 = np.full(common_bbox.to_size(), False)
g1.draw(mask_1, color=True)
mask_2 = np.full(common_bbox.to_size(), False)
g2.draw(mask_2, color=True)
return safe_ratio((mask_1 & mask_2).sum(), (mask_1 | mask_2).sum())
def get_effective_nonoverlapping_masks(geometries, img_size=None):
if img_size is None:
if len(geometries) > 0:
common_bbox = Rectangle.from_geometries_list(geometries)
img_size = (common_bbox.bottom + 1, common_bbox.right + 1)
else:
img_size = (0, 0)
canvas = np.full(shape=img_size,
fill_value=len(geometries),
dtype=np.int32)
for idx, geometry in enumerate(geometries):
geometry.draw(canvas, color=idx)
result_masks = []
for idx, geometry in enumerate(geometries):
effective_indicator = (canvas == idx)
if np.any(effective_indicator):
result_masks.append(Bitmap(effective_indicator))
else:
result_masks.append(None)
return result_masks, canvas
def to_bbox(self):
return Rectangle.from_geometries_list([
Point.from_point_location(node.location)
for node in self._nodes.values()
])
