def api_generate_next_task():
""" Generate next task to label
"""
# try to find task is not presented in completions
completions = db.get_completions_ids()
for (task_id, task) in db.get_tasks().items():
if task_id not in completions:
log.info(msg='New task for labeling', extra=task)
analytics.send(getframeinfo(currentframe()).function)
return make_response(jsonify(task), 200)
# no tasks found
analytics.send(getframeinfo(currentframe()).function, error=404)
return make_response('', 404)
def api_generate_next_task():
""" Generate next task to label
"""
# try to find task is not presented in completions
completions = db.get_completions_ids()
for task_id, task in db.iter_tasks():
if task_id not in completions:
log.info(msg='New task for labeling', extra=task)
analytics.send(getframeinfo(currentframe()).function)
# try to use ml backend for predictions
if ml_backend:
task = deepcopy(task)
task['predictions'] = ml_backend.make_predictions(
task, project)
return make_response(jsonify(task), 200)
# no tasks found
analytics.send(getframeinfo(currentframe()).function, error=404)
return make_response('', 404)
def tasks_page():
""" Tasks and completions page: tasks.html
"""
global c
reload_config()
label_config = open(
c['label_config']).read() # load editor config from XML
task_ids = db.get_tasks().keys()
completed_at = db.get_completed_at(task_ids)
# sort by completed time
task_ids = sorted([(i, completed_at[i] if i in completed_at else '9')
for i in task_ids],
key=lambda x: x[1])
task_ids = [i[0] for i in task_ids] # take only id back
analytics.send(getframeinfo(currentframe()).function)
return flask.render_template('tasks.html',
config=c,
label_config=label_config,
task_ids=task_ids,
completions=db.get_completions_ids(),
completed_at=completed_at)
def api_all_completion_ids():
""" Get all completion ids
"""
ids = db.get_completions_ids()
analytics.send(getframeinfo(currentframe()).function)
return make_response(jsonify(ids), 200)