def post(self):
print("hannahhh du geiles stück")
""" Creates an annotation """
args = create_annotation.parse_args()
image_id = args.get('image_id')
category_id = args.get('category_id')
isbbox = args.get('isbbox')
metadata = args.get('metadata', {})
segmentation = args.get('segmentation', [])
keypoints = args.get('keypoints', [])
image = current_user.images.filter(id=image_id, deleted=False).first()
if image is None:
return {"message": "Invalid image id"}, 400
logger.info(
f'{current_user.username} has created an annotation for image {image_id} with {isbbox}'
)
logger.info(
f'{current_user.username} has created an annotation for image {image_id}'
)
try:
annotation = AnnotationModel(image_id=image_id,
category_id=category_id,
metadata=metadata,
segmentation=segmentation,
keypoints=keypoints,
isbbox=isbbox)
annotation.save()
annotation.mask()
except (ValueError, TypeError) as e:
return {'message': str(e)}, 400
return query_util.fix_ids(annotation)
def create_annotation(image_id):
annotation = AnnotationModel(
image_id=image_id,
category_id=0,
metadata={},
segmentation=[[1, 2, 3, 4]],
keypoints=[1, 2, 3, 4],
isbbox=False
)
annotation.save()
return annotation.id
def post(self):
""" Creates an annotation """
args = create_annotation.parse_args()
image_id = args.get('image_id')
category_id = args.get('category_id')
isbbox = args.get('isbbox')
metadata = args.get('metadata', {})
segmentation = args.get('segmentation', [])
bbox = args.get('bbox', [])
keypoints = args.get('keypoints', [])
# change appro after setting login_user
# image = current_user.images.filter(id=image_id, deleted=False).first()
# image = ImageModel.objects.get(id=image_id, deleted=False).first()
image = ImageModel.objects(id=image_id).first()
if image is None:
return {"message": "Invalid image id"}, 400
logger.info(
f'{current_user.username} has created an annotation for image {image_id} with {isbbox}'
)
logger.info(
f'{current_user.username} has created an annotation for image {image_id}'
)
# add condition if user is not authenticed or dataset is public
try:
annotation = AnnotationModel(image_id=image_id,
category_id=category_id,
metadata=metadata,
segmentation=segmentation,
bbox=bbox,
keypoints=keypoints,
isbbox=isbbox)
annotation.save()
except (ValueError, TypeError) as e:
return {'message': str(e)}, 400
return query_util.fix_ids(annotation)
def create_annotation_from(self, annotation_data, image_id):
collect_annotation_data = {}
self.append_events_ant_times_to(collect_annotation_data,
annotation_data)
self.append_papers_object_to(collect_annotation_data, annotation_data,
image_id)
self.append_other_data_to(collect_annotation_data, annotation_data,
image_id)
return AnnotationModel(
image_id=image_id,
category_id=annotation_data['category_id'],
events=collect_annotation_data['events'],
milliseconds=collect_annotation_data['milliseconds'],
paper_object=collect_annotation_data['paper_object'],
segmentation=collect_annotation_data['segmentation'],
area=collect_annotation_data['area'],
bbox=collect_annotation_data['bbox'],
isbbox=collect_annotation_data['isbbox'],
keypoints=collect_annotation_data['keypoints'],
metadata=collect_annotation_data['metadata'],
color=collect_annotation_data['color'],
)
def post(self):
""" Creates an annotation """
args = create_annotation.parse_args()
image_id = args.get('image_id')
category_id = args.get('category_id')
metadata = args.get('metadata', {})
segmentation = args.get('segmentation', [])
keypoints = args.get('keypoints', [])
logger.info(
f'{current_user.username} has created an annotation for image {image_id}'
)
try:
annotation = AnnotationModel(image_id=image_id,
category_id=category_id,
metadata=metadata,
segmentation=segmentation,
keypoints=keypoints)
annotation.save()
except (ValueError, TypeError) as e:
return {'message': str(e)}, 400
return query_util.fix_ids(annotation)
def import_annotations(task_id, dataset_id, coco_json):
task = TaskModel.objects.get(id=task_id)
dataset = DatasetModel.objects.get(id=dataset_id)
task.update(status="PROGRESS")
socket = create_socket()
task.info("Beginning Import")
images = ImageModel.objects(dataset_id=dataset.id)
categories = CategoryModel.objects
coco_images = coco_json.get('images', [])
coco_annotations = coco_json.get('annotations', [])
coco_categories = coco_json.get('categories', [])
task.info(f"Importing {len(coco_categories)} categories, "
f"{len(coco_images)} images, and "
f"{len(coco_annotations)} annotations")
total_items = sum(
[len(coco_categories),
len(coco_annotations),
len(coco_images)])
progress = 0
task.info("===== Importing Categories =====")
# category id mapping ( file : database )
categories_id = {}
# Create any missing categories
for category in coco_categories:
category_name = category.get('name')
category_id = category.get('id')
category_model = categories.filter(name__iexact=category_name).first()
if category_model is None:
task.warning(
f"{category_name} category not found (creating a new one)")
new_category = CategoryModel(
name=category_name,
keypoint_edges=category.get('skeleton', []),
keypoint_labels=category.get('keypoints', []))
new_category.save()
category_model = new_category
dataset.categories.append(new_category.id)
task.info(f"{category_name} category found")
# map category ids
categories_id[category_id] = category_model.id
# update progress
progress += 1
task.set_progress((progress / total_items) * 100, socket=socket)
dataset.update(set__categories=dataset.categories)
task.info("===== Loading Images =====")
# image id mapping ( file: database )
images_id = {}
categories_by_image = {}
# Find all images
for image in coco_images:
image_id = image.get('id')
image_filename = image.get('file_name')
# update progress
progress += 1
task.set_progress((progress / total_items) * 100, socket=socket)
image_model = images.filter(file_name__exact=image_filename).all()
if len(image_model) == 0:
task.warning(f"Could not find image {image_filename}")
continue
if len(image_model) > 1:
task.error(
f"Too many images found with the same file name: {image_filename}"
)
continue
task.info(f"Image {image_filename} found")
image_model = image_model[0]
images_id[image_id] = image_model
categories_by_image[image_id] = list()
task.info("===== Import Annotations =====")
for annotation in coco_annotations:
image_id = annotation.get('image_id')
category_id = annotation.get('category_id')
segmentation = annotation.get('segmentation', [])
keypoints = annotation.get('keypoints', [])
# is_crowd = annotation.get('iscrowed', False)
area = annotation.get('area', 0)
bbox = annotation.get('bbox', [0, 0, 0, 0])
isbbox = annotation.get('isbbox', False)
progress += 1
task.set_progress((progress / total_items) * 100, socket=socket)
has_segmentation = len(segmentation) > 0
has_keypoints = len(keypoints) > 0
if not has_segmentation and not has_keypoints:
task.warning(
f"Annotation {annotation.get('id')} has no segmentation or keypoints"
)
continue
try:
image_model = images_id[image_id]
category_model_id = categories_id[category_id]
image_categories = categories_by_image[image_id]
except KeyError:
task.warning(
f"Could not find image assoicated with annotation {annotation.get('id')}"
)
continue
annotation_model = AnnotationModel.objects(
image_id=image_model.id,
category_id=category_model_id,
segmentation=segmentation,
keypoints=keypoints).first()
if annotation_model is None:
task.info(f"Creating annotation data ({image_id}, {category_id})")
annotation_model = AnnotationModel(image_id=image_model.id)
annotation_model.category_id = category_model_id
annotation_model.color = annotation.get('color')
annotation_model.metadata = annotation.get('metadata', {})
if has_segmentation:
annotation_model.segmentation = segmentation
annotation_model.area = area
annotation_model.bbox = bbox
if has_keypoints:
annotation_model.keypoints = keypoints
annotation_model.isbbox = isbbox
annotation_model.save()
image_categories.append(category_id)
else:
annotation_model.update(deleted=False, isbbox=isbbox)
task.info(
f"Annotation already exists (i:{image_id}, c:{category_id})")
for image_id in images_id:
image_model = images_id[image_id]
category_ids = categories_by_image[image_id]
all_category_ids = list(image_model.category_ids)
all_category_ids += category_ids
num_annotations = AnnotationModel.objects(
Q(image_id=image_id) & Q(deleted=False)
& (Q(area__gt=0) | Q(keypoints__size__gt=0))).count()
image_model.update(set__annotated=True,
set__category_ids=list(set(all_category_ids)),
set__num_annotations=num_annotations)
task.set_progress(100, socket=socket)
