def from_json(cls, data):
'''
The function from_json convert ProjectMeta from json format to ProjectMeta class object. Generate exception error if all project tags not in a single collection
:param data: input ProjectMeta in json format
:return: ProjectMeta class object
'''
tag_metas_json = data.get(ProjectMetaJsonFields.TAGS, [])
img_tag_metas_json = data.get(ProjectMetaJsonFields.IMG_TAGS, [])
obj_tag_metas_json = data.get(ProjectMetaJsonFields.OBJ_TAGS, [])
project_type = data.get(ProjectMetaJsonFields.PROJECT_TYPE, None)
if len(tag_metas_json) > 0:
# New format - all project tags in a single collection.
if any(len(x) > 0 for x in [img_tag_metas_json, obj_tag_metas_json]):
raise ValueError(
'Project meta JSON contains both the {!r} section (current format merged tags for all of '
'the project) and {!r} or {!r} sections (legacy format with separate collections for images '
'and labeled objects). Either new format only or legacy format only are supported, but not a '
'mix.'.format(
ProjectMetaJsonFields.TAGS, ProjectMetaJsonFields.IMG_TAGS, ProjectMetaJsonFields.OBJ_TAGS))
tag_metas = TagMetaCollection.from_json(tag_metas_json)
else:
img_tag_metas = TagMetaCollection.from_json(img_tag_metas_json)
obj_tag_metas = TagMetaCollection.from_json(obj_tag_metas_json)
tag_metas = _merge_img_obj_tag_metas(img_tag_metas, obj_tag_metas)
return cls(obj_classes=ObjClassCollection.from_json(data[ProjectMetaJsonFields.OBJ_CLASSES]),
tag_metas=tag_metas, project_type=project_type)
def _model_out_tags(self):
temp_collection = TagMetaCollection.from_json(
self.train_config[self.classification_tags_key])
res_collection = TagMetaCollection([
TagMeta(x.name, TagValueType.ANY_NUMBER) for x in temp_collection
])
return res_collection
def __init__(self,
obj_classes=None,
img_tag_metas=None,
obj_tag_metas=None):
self._obj_classes = take_with_default(obj_classes,
ObjClassCollection())
# TODO do we actualy need two sets of tags?
self._img_tag_metas = take_with_default(img_tag_metas,
TagMetaCollection())
self._obj_tag_metas = take_with_default(obj_tag_metas,
TagMetaCollection())
def __init__(self, obj_classes=None, tag_metas=None):
'''
:param obj_classes: Collection that stores ObjClass instances with unique names.
:param tag_metas: Collection that stores TagMeta instances with unique names.
'''
self._obj_classes = ObjClassCollection() if obj_classes is None else obj_classes
self._tag_metas = take_with_default(tag_metas, TagMetaCollection())
def delete_tag_metas(self, tag_names):
'''
The function delete_tag_metas delete tags with given list of names from ProjectMeta collection that stores TagMeta instances and return copy of ProjectMeta
:param tag_names: list of names TagMeta objects to delete
:return: ProjectMeta class object
'''
res_items = self._delete_items(self._tag_metas, tag_names)
return self.clone(tag_metas=TagMetaCollection(res_items))
def _replace_labels_classes(labels,
obj_class_mapper: ObjClassMapper,
tags_meta_mapper: TagMetaMapper,
skip_missing=False) -> list:
result = []
for label in labels:
dest_obj_class = obj_class_mapper.map(label.obj_class)
if dest_obj_class is not None:
mapped_tags = TagMetaCollection(items=[
Tag(meta=tags_meta_mapper.map(tag.meta), value=tag.value)
for tag in label.tags
])
result.append(
label.clone(obj_class=dest_obj_class, tags=mapped_tags))
elif not skip_missing:
raise KeyError(
'Object class {} could not be mapped to a destination object class.'
.format(label.obj_class.name))
return result
def setUp(self):
self._obj_class_gt = ObjClass(name='a', geometry_type=Rectangle)
self._obj_class_pred = ObjClass(name='b', geometry_type=Rectangle)
self._confidence_tag_meta = TagMeta(name='confidence', value_type=TagValueType.ANY_NUMBER)
self._meta = ProjectMeta(
obj_classes=ObjClassCollection([self._obj_class_gt, self._obj_class_pred]),
tag_metas=TagMetaCollection([self._confidence_tag_meta]))
# Will match self._pred_obj_1
self._gt_obj_1 = Label(obj_class=self._obj_class_gt, geometry=Rectangle(0, 0, 10, 10))
# Will match self._pred_obj_3
self._gt_obj_2 = Label(obj_class=self._obj_class_gt, geometry=Rectangle(13, 13, 15, 15))
# Will be a false negative
self._gt_obj_3 = Label(obj_class=self._obj_class_gt, geometry=Rectangle(43, 43, 45, 45))
# Will match self._gt_obj_1
self._pred_obj_1 = Label(
obj_class=self._obj_class_pred,
geometry=Rectangle(0, 0, 9, 9),
tags=TagCollection([Tag(meta=self._confidence_tag_meta, value=0.7)]))
# Will be a false positive (self._pred_obj_1 has higher IoU).
self._pred_obj_2 = Label(
obj_class=self._obj_class_pred,
geometry=Rectangle(0, 0, 8, 8),
tags=TagCollection([Tag(meta=self._confidence_tag_meta, value=0.6)]))
# Will match self._gt_obj_2
self._pred_obj_3 = Label(
obj_class=self._obj_class_pred,
geometry=Rectangle(13, 13, 15, 15),
tags=TagCollection([Tag(meta=self._confidence_tag_meta, value=0.1)]))
# More false positives.
self._pred_objs_fp = [
Label(obj_class=self._obj_class_pred,
geometry=Rectangle(20, 20, 30, 30),
tags=TagCollection([Tag(meta=self._confidence_tag_meta, value=v / 100)]))
for v in range(15, 85, 10)]
self._metric_calculator = MAPMetric(class_mapping={'a': 'b'}, iou_threshold=0.5)
def from_json(cls, data):
return cls(
ObjClassCollection.from_json(
data[ProjectMetaJsonFields.OBJ_CLASSES]),
TagMetaCollection.from_json(data[ProjectMetaJsonFields.IMG_TAGS]),
TagMetaCollection.from_json(data[ProjectMetaJsonFields.OBJ_TAGS]))
def delete_obj_tag_metas(self, tag_names):
res_items = self._delete_items(self._obj_tag_metas, tag_names)
return self.clone(obj_tag_metas=TagMetaCollection(res_items))
def _model_out_tags(self):
return TagMetaCollection() # Empty by default