Model Annotations
Add
Adding model metadata to annotations will help filter for model annotations in the studios, using a DQL, and more.
Add the model information to the annotation like this:
detections = model.predict(image)
collection = item.anntoationds.builder()
for detection in detections:
x1, y1, x2, y2, label_ind, confidence = detection
collection.add(annotation_definition=dl.Box(left=x1,
top=y1,
right=x2,
bottom=y2,
label=model_entity.id_to_label_map[label_ind]
),
model_info={'name': model_entity.name,
'model_id': model_entity.id,
'confidence': float(confidence)})
item.annotations.upload(collection)
This will add the information to the annotation.metadata.user.model
.
Filter
In the studio, you can group annotation by creator to see each model's annotations:
Using the SDK you can query and get only the models annotations:
import dtlpy as dl
dl.setenv('prod')
dataset = dl.datasets.get(dataset_id='')
model = dl.models.sget(model_id='')
filters = dl.Filters(resource=dl.FILTERS_RESOURCE_ANNOTATION)
filters.add(field='metadata.user.model.name', values=model.name)
# list to get the number
pages = dataset.annotations.list(filters=filters)
print(f'dataset has {pages.items_count} annotations from the model')
Delete
WARNING This script will delete annotations from the entire dataset! make sure you delete what you want. There's no
way to restore deleted annotations!!
import dtlpy as dl
dl.setenv('prod')
dataset = dl.datasets.get(dataset_id='')
model = dl.models.sget(model_id='')
filters = dl.Filters(resource=dl.FILTERS_RESOURCE_ANNOTATION)
filters.add(field='metadata.user.model.name', values=model.name)
# list to get the number
pages = dataset.annotations.list(filters=filters)
print(f'dataset has {pages.items_count} annotations from the model')
# bulk delete using a DQL
dataset.annotations.delete(filters=filters)