def create_thread(tid, labels_mapping, user):
try:
# If detected object accuracy bigger than threshold it will returend
TRESHOLD = 0.5
# Init rq job
job = rq.get_current_job()
job.meta['progress'] = 0
job.save_meta()
# Get job indexes and segment length
db_task = TaskModel.objects.get(pk=tid)
# Get image list
image_list = make_image_list(db_task.get_data_dirname())
# Run auto segmentation by tf
result = None
slogger.glob.info("auto segmentation with tensorflow framework for task {}".format(tid))
result = run_tensorflow_auto_segmentation(image_list, labels_mapping, TRESHOLD)
if result is None:
slogger.glob.info('auto segmentation for task {} canceled by user'.format(tid))
return
# Modify data format and save
result = convert_to_cvat_format(result)
serializer = LabeledDataSerializer(data = result)
if serializer.is_valid(raise_exception=True):
put_task_data(tid, user, result)
slogger.glob.info('auto segmentation for task {} done'.format(tid))
except Exception as ex:
try:
slogger.task[tid].exception('exception was occured during auto segmentation of the task', exc_info=True)
except Exception:
slogger.glob.exception('exception was occured during auto segmentation of the task {}'.format(tid), exc_info=True)
raise ex
def run_inference_thread(tid, model_file, weights_file, labels_mapping, attributes, convertation_file, reset, user, restricted=True):
def update_progress(job, progress):
job.refresh()
if "cancel" in job.meta:
del job.meta["cancel"]
job.save()
return False
job.meta["progress"] = progress
job.save_meta()
return True
try:
job = rq.get_current_job()
job.meta["progress"] = 0
job.save_meta()
db_task = TaskModel.objects.get(pk=tid)
result = None
slogger.glob.info("auto annotation with openvino toolkit for task {}".format(tid))
result = run_inference_engine_annotation(
data=get_image_data(db_task.get_data_dirname()),
model_file=model_file,
weights_file=weights_file,
labels_mapping=labels_mapping,
attribute_spec=attributes,
convertation_file= convertation_file,
job=job,
update_progress=update_progress,
restricted=restricted
)
if result is None:
slogger.glob.info("auto annotation for task {} canceled by user".format(tid))
return
serializer = LabeledDataSerializer(data = result)
if serializer.is_valid(raise_exception=True):
if reset:
put_task_data(tid, user, result)
else:
patch_task_data(tid, user, result, "create")
slogger.glob.info("auto annotation for task {} done".format(tid))
except Exception as e:
try:
slogger.task[tid].exception("exception was occurred during auto annotation of the task", exc_info=True)
except Exception as ex:
slogger.glob.exception("exception was occurred during auto annotation of the task {}: {}".format(tid, str(ex)), exc_info=True)
raise ex
raise e