def test_background_masks_dont_introduce_instances_but_cover_others(self):
dataset = Dataset.from_iterable([
DatasetItem(1, image=np.zeros((4, 1, 1)), annotations=[
Mask([1, 1, 1, 1], label=1, attributes={'z_order': 1}),
Mask([0, 0, 1, 1], label=2, attributes={'z_order': 2}),
Mask([0, 0, 1, 1], label=0, attributes={'z_order': 3}),
])
], categories=['background', 'a', 'b'])
with TestDir() as test_dir:
VocConverter.convert(dataset, test_dir, apply_colormap=False)
cls_mask = load_mask(
osp.join(test_dir, 'SegmentationClass', '1.png'))
inst_mask = load_mask(
osp.join(test_dir, 'SegmentationObject', '1.png'))
self.assertTrue(np.array_equal([0, 1], np.unique(cls_mask)))
self.assertTrue(np.array_equal([0, 1], np.unique(inst_mask)))
def _parse_annotations(cls, xml_root, dataset_root, categories):
def parse_attributes(attr_str):
parsed = []
if not attr_str:
return parsed
for attr in [a.strip() for a in attr_str.split(',') if a.strip()]:
if '=' in attr:
name, value = attr.split('=', maxsplit=1)
if value.lower() in {'true', 'false'}:
value = value.lower() == 'true'
else:
try:
value = float(value)
except ValueError:
pass
parsed.append((name, value))
else:
parsed.append((attr, True))
return parsed
label_cat = categories[AnnotationType.label]
def get_label_id(label):
if not label:
return None
idx, _ = label_cat.find(label)
if idx is None:
idx = label_cat.add(label)
return idx
image_annotations = []
parsed_annotations = dict()
group_assignments = dict()
root_annotations = set()
for obj_elem in xml_root.iter('object'):
obj_id = int(obj_elem.find('id').text)
ann_items = []
label = get_label_id(obj_elem.find('name').text)
attributes = []
attributes_elem = obj_elem.find('attributes')
if attributes_elem is not None and attributes_elem.text:
attributes = parse_attributes(attributes_elem.text)
occluded = False
occluded_elem = obj_elem.find('occluded')
if occluded_elem is not None and occluded_elem.text:
occluded = (occluded_elem.text == 'yes')
attributes.append(('occluded', occluded))
deleted = False
deleted_elem = obj_elem.find('deleted')
if deleted_elem is not None and deleted_elem.text:
deleted = bool(int(deleted_elem.text))
user = ''
poly_elem = obj_elem.find('polygon')
segm_elem = obj_elem.find('segm')
type_elem = obj_elem.find('type') # the only value is 'bounding_box'
if poly_elem is not None:
user_elem = poly_elem.find('username')
if user_elem is not None and user_elem.text:
user = user_elem.text
attributes.append(('username', user))
points = []
for point_elem in poly_elem.iter('pt'):
x = float(point_elem.find('x').text)
y = float(point_elem.find('y').text)
points.append(x)
points.append(y)
if type_elem is not None and type_elem.text == 'bounding_box':
xmin = min(points[::2])
xmax = max(points[::2])
ymin = min(points[1::2])
ymax = max(points[1::2])
ann_items.append(Bbox(xmin, ymin, xmax - xmin, ymax - ymin,
label=label, attributes=attributes, id=obj_id,
))
else:
ann_items.append(Polygon(points,
label=label, attributes=attributes, id=obj_id,
))
elif segm_elem is not None:
user_elem = segm_elem.find('username')
if user_elem is not None and user_elem.text:
user = user_elem.text
attributes.append(('username', user))
mask_path = osp.join(dataset_root, LabelMePath.MASKS_DIR,
segm_elem.find('mask').text)
if not osp.isfile(mask_path):
raise Exception("Can't find mask at '%s'" % mask_path)
mask = load_mask(mask_path)
mask = np.any(mask, axis=2)
ann_items.append(Mask(image=mask, label=label, id=obj_id,
attributes=attributes))
if not deleted:
parsed_annotations[obj_id] = ann_items
# Find parents and children
parts_elem = obj_elem.find('parts')
if parts_elem is not None:
children_ids = []
hasparts_elem = parts_elem.find('hasparts')
if hasparts_elem is not None and hasparts_elem.text:
children_ids = [int(c) for c in hasparts_elem.text.split(',')]
parent_ids = []
ispartof_elem = parts_elem.find('ispartof')
if ispartof_elem is not None and ispartof_elem.text:
parent_ids = [int(c) for c in ispartof_elem.text.split(',')]
if children_ids and not parent_ids and hasparts_elem.text:
root_annotations.add(obj_id)
group_assignments[obj_id] = [None, children_ids]
# assign single group to all grouped annotations
current_group_id = 0
annotations_to_visit = list(root_annotations)
while annotations_to_visit:
ann_id = annotations_to_visit.pop()
ann_assignment = group_assignments[ann_id]
group_id, children_ids = ann_assignment
if group_id:
continue
if ann_id in root_annotations:
current_group_id += 1 # start a new group
group_id = current_group_id
ann_assignment[0] = group_id
# continue with children
annotations_to_visit.extend(children_ids)
assert current_group_id == len(root_annotations)
for ann_id, ann_items in parsed_annotations.items():
group_id = 0
if ann_id in group_assignments:
ann_assignment = group_assignments[ann_id]
group_id = ann_assignment[0]
for ann_item in ann_items:
if group_id:
ann_item.group = group_id
image_annotations.append(ann_item)
return image_annotations
