def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self._fetchProjectSettings()
self.sqlBuilder = SQLStringBuilder(config)
self.annoParser = AnnotationParser(config)
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.project_immutables = {} # project settings that cannot be changed (project shorthand -> {settings})
self._fetchProjectSettings()
self.sqlBuilder = SQLStringBuilder()
self.annoParser = AnnotationParser()
def __init__(self, config, passiveMode=False):
self.config = config
self.dbConnector = Database(config)
self.countPattern = re.compile('\_[0-9]+$')
self.passiveMode = passiveMode
self.tempDir = self.config.getProperty('FileServer',
'tempfiles_dir',
type=str,
fallback=tempfile.gettempdir())
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
# load default UI settings
try:
# check if custom default styles are provided
self.defaultUIsettings = json.load(open('config/default_ui_settings.json', 'r'))
except:
# resort to built-in styles
self.defaultUIsettings = json.load(open('modules/ProjectAdministration/static/json/default_ui_settings.json', 'r'))
def __init__(self, config):
self.config = config
self.dbConn = Database(config)
self.sqlBuilder = SQLStringBuilder(config)
self.training = False # will be set to True once start_training is called (and False as soon as everything about the training process has finished)
self.celery_app = current_app
self.celery_app.set_current()
self.celery_app.set_default()
self.watchdog = None # note: watchdog only created if users poll status (i.e., if there's activity)
#TODO
self.messageProcessor = MessageProcessor(self.celery_app)
self.messageProcessor.start()
def __init__(self, config, passiveMode=False, verbose_start=False):
self.config = config
if verbose_start:
print('AIWorker'.ljust(22), end='')
try:
self.dbConnector = Database(config)
self.passiveMode = passiveMode
self._init_fileserver()
except Exception as e:
if verbose_start:
LogDecorator.print_status('fail')
raise Exception(
f'Could not launch AIWorker (message: "{str(e)}").')
if verbose_start:
LogDecorator.print_status('ok')
def __init__(self, config, app):
if config.getProperty('Project', 'demoMode', type=bool,
fallback=False):
raise Exception('AIWorker cannot be launched in demo mode.')
self.config = config
self.dbConnector = Database(config)
self._init_fileserver()
self._init_model_instance()
self._init_al_instance()
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.celery_app = current_app
self.celery_app.set_current()
self.celery_app.set_default()
self.dataWorker = DataWorker(config)
self.jobs = {} # dict per project of jobs
class AdminMiddleware:
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
def getServiceDetails(self, warn_error=False):
'''
Queries the indicated AIController and FileServer
modules for availability and their version. Returns
metadata about the setup of AIDE accordingly.
Raises an Exception if not running on the main host.
If "warn_error" is True, a warning statement is printed
to the command line if the version of AIDE on the attached
AIController and/or FileServer is not the same as on the
host, or if the servers cannot be contacted.
'''
if warn_error:
print('Contacting AIController...', end='')
# check if running on the main host
modules = os.environ['AIDE_MODULES'].strip().split(',')
modules = set([m.strip() for m in modules])
if not 'LabelUI' in modules:
# not running on main host
raise Exception('Not a main host; cannot query service details.')
aic_uri = self.config.getProperty('Server',
'aiController_uri',
type=str,
fallback=None)
fs_uri = self.config.getProperty('Server',
'dataServer_uri',
type=str,
fallback=None)
if not is_localhost(aic_uri):
# AIController runs on a different machine; poll for version of AIDE
try:
aic_response = requests.get(os.path.join(aic_uri, 'version'))
aic_version = aic_response.text
if warn_error and aic_version != AIDE_VERSION:
print(
'WARNING: AIDE version of connected AIController differs from main host.'
)
print(f'\tAIController URI: {aic_uri}')
print(f'\tAIController AIDE version: {aic_version}')
print(f'\tAIDE version on this machine: {AIDE_VERSION}')
elif warn_error:
LogDecorator.print_status('ok')
except Exception as e:
if warn_error:
LogDecorator.print_status('fail')
print(
f'WARNING: error connecting to AIController (message: "{str(e)}").'
)
aic_version = None
else:
aic_version = AIDE_VERSION
if warn_error:
LogDecorator.print_status('ok')
if not is_localhost(fs_uri):
# same for the file server
if warn_error:
print('Contacting FileServer...', end='')
try:
fs_response = requests.get(os.path.join(fs_uri, 'version'))
fs_version = fs_response.text
if warn_error and fs_version != AIDE_VERSION:
LogDecorator.print_status('warn')
print(
'WARNING: AIDE version of connected FileServer differs from main host.'
)
print(f'\tFileServer URI: {fs_uri}')
print(f'\tFileServer AIDE version: {fs_version}')
print(f'\tAIDE version on this machine: {AIDE_VERSION}')
elif warn_error:
LogDecorator.print_status('ok')
except Exception as e:
if warn_error:
LogDecorator.print_status('fail')
print(
f'WARNING: error connecting to FileServer (message: "{str(e)}").'
)
fs_version = None
else:
fs_version = AIDE_VERSION
if warn_error:
LogDecorator.print_status('ok')
# query database
dbVersion = self.dbConnector.execute('SHOW server_version;', None,
1)[0]['server_version']
try:
dbVersion = dbVersion.split(' ')[0].strip()
except:
pass
dbInfo = self.dbConnector.execute('SELECT version() AS version;', None,
1)[0]['version']
return {
'aide_version': AIDE_VERSION,
'AIController': {
'uri': aic_uri,
'aide_version': aic_version
},
'FileServer': {
'uri': fs_uri,
'aide_version': fs_version
},
'Database': {
'version': dbVersion,
'details': dbInfo
}
}
def getCeleryWorkerDetails(self):
'''
Queries all Celery workers for their details (name,
URL, capabilities, AIDE version, etc.)
'''
result = {}
i = current_app.control.inspect()
workers = i.stats()
if workers is None or not len(workers):
return result
for w in workers:
aiwV = celeryWorkerCommons.get_worker_details.s()
try:
res = aiwV.apply_async(queue=w)
res = res.get(timeout=20) #TODO: timeout (in seconds)
result[w] = res
result[w]['online'] = True
except Exception as e:
result[w] = {'online': False, 'message': str(e)}
return result
def getProjectDetails(self):
'''
Returns projects and statistics about them
(number of images, disk usage, etc.).
'''
# get all projects
projects = {}
response = self.dbConnector.execute(
'''
SELECT shortname, name, owner, annotationtype, predictiontype,
ispublic, demomode, ai_model_enabled, interface_enabled, archived,
COUNT(username) AS num_users
FROM aide_admin.project AS p
JOIN aide_admin.authentication AS auth
ON p.shortname = auth.project
GROUP BY shortname
''', None, 'all')
for r in response:
projDef = {}
for key in r.keys():
if key == 'interface_enabled':
projDef[key] = r['interface_enabled'] and not r['archived']
if key != 'shortname':
projDef[key] = r[key]
projects[r['shortname']] = projDef
# get statistics (number of annotations, predictions, prediction models, etc.)
for project in projects.keys():
stats = self.dbConnector.execute(
sql.SQL('''
SELECT COUNT(*) AS count
FROM {id_img}
UNION ALL
SELECT COUNT(*)
FROM {id_anno}
UNION ALL
SELECT COUNT(*)
FROM {id_pred}
UNION ALL
SELECT SUM(viewcount)
FROM {id_iu}
UNION ALL
SELECT COUNT(*)
FROM {id_cnnstate}
''').format(id_img=sql.Identifier(project, 'image'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'),
id_iu=sql.Identifier(project, 'image_user'),
id_cnnstate=sql.Identifier(project, 'cnnstate')),
None, 'all')
projects[project]['num_img'] = stats[0]['count']
projects[project]['num_anno'] = stats[1]['count']
projects[project]['num_pred'] = stats[2]['count']
projects[project]['total_viewcount'] = stats[3]['count']
projects[project]['num_cnnstates'] = stats[4]['count']
# time statistics (last viewed)
stats = self.dbConnector.execute(
sql.SQL('''
SELECT MIN(first_checked) AS first_checked,
MAX(last_checked) AS last_checked
FROM {id_iu};
''').format(id_iu=sql.Identifier(project, 'image_user')), None, 1)
try:
projects[project]['first_checked'] = stats[0][
'first_checked'].timestamp()
except:
projects[project]['first_checked'] = None
try:
projects[project]['last_checked'] = stats[0][
'last_checked'].timestamp()
except:
projects[project]['last_checked'] = None
return projects
def getUserDetails(self):
'''
Returns details about the user (name, number of
enrolled projects, last activity, etc.).
'''
users = {}
userData = self.dbConnector.execute(
'''
SELECT name, email, isSuperUser, canCreateProjects,
last_login, project, isAdmin, admitted_until, blocked_until
FROM aide_admin.user AS u
LEFT OUTER JOIN aide_admin.authentication AS auth
ON u.name = auth.username
''', None, 'all')
for ud in userData:
if not ud['name'] in users:
users[ud['name']] = {
'email':
ud['email'],
'canCreateProjects':
ud['cancreateprojects'],
'isSuperUser':
ud['issuperuser'],
'last_login': (None if ud['last_login'] is None else
ud['last_login'].timestamp()),
'enrolled_projects': {}
}
if ud['project'] is not None:
admitted_until = ud['admitted_until']
if isinstance(admitted_until, datetime.datetime):
admitted_until = admitted_until.timestamp()
blocked_until = ud['admitted_until']
if isinstance(blocked_until, datetime.datetime):
blocked_until = blocked_until.timestamp()
users[ud['name']]['enrolled_projects'][ud['project']] = {
'admitted_until': admitted_until,
'blocked_until': blocked_until
}
return users
def setCanCreateProjects(self, username, allowCreateProjects):
'''
Sets or unsets the flag on whether a user
can create new projects or not.
'''
# check if user exists
userExists = self.dbConnector.execute(
'''
SELECT * FROM aide_admin.user
WHERE name = %s;
''', (username, ), 1)
if not len(userExists):
return {
'success': False,
'message': f'User with name "{username}" does not exist.'
}
result = self.dbConnector.execute(
'''
UPDATE aide_admin.user
SET cancreateprojects = %s
WHERE name = %s;
SELECT cancreateprojects
FROM aide_admin.user
WHERE name = %s;
''', (allowCreateProjects, username, username), 1)
result = result[0]['cancreateprojects']
return {'success': (result == allowCreateProjects)}
'--modelPath',
type=str,
help=
'Directory (absolute path) on this machine of the model state file to be considered.'
)
args = parser.parse_args()
# setup
print('Setup...')
if not 'AIDE_CONFIG_PATH' in os.environ:
os.environ['AIDE_CONFIG_PATH'] = str(args.settings_filepath)
from util.configDef import Config
from modules.Database.app import Database
config = Config()
dbConn = Database(config)
# load model class function
print('Load and verify state dict...')
from util.helpers import get_class_executable, current_time
modelClass = getattr(
get_class_executable(
config.getProperty('AIController', 'model_lib_path')),
'model_class')
# load state dict
stateDict = torch.load(open(args.modelPath, 'rb'))
# verify model state
model = modelClass.loadFromStateDict(stateDict)
class AIControllerWorker:
def __init__(self, config, celery_app):
self.config = config
self.dbConn = Database(config)
self.sqlBuilder = SQLStringBuilder(config)
self.celery_app = celery_app
def _get_num_available_workers(self):
#TODO: filter for right tasks and queues
#TODO: limit to n tasks per worker
i = self.celery_app.control.inspect()
if i is not None:
stats = i.stats()
if stats is not None:
return len(i.stats())
return 1 #TODO
def get_training_images(self,
project,
epoch=None,
numEpochs=None,
minTimestamp='lastState',
includeGoldenQuestions=True,
minNumAnnoPerImage=0,
maxNumImages=None,
numChunks=1):
'''
Queries the database for the latest images to be used for model training.
Returns a list with image UUIDs accordingly, split into the number of
available workers.
#TODO: includeGoldenQuestions
'''
# sanity checks
if not (isinstance(minTimestamp, datetime) or minTimestamp
== 'lastState' or minTimestamp == -1 or minTimestamp is None):
raise ValueError(
'{} is not a recognized property for variable "minTimestamp"'.
format(str(minTimestamp)))
# query image IDs
queryVals = []
if minTimestamp is None:
timestampStr = sql.SQL('')
elif minTimestamp == 'lastState':
timestampStr = sql.SQL('''
WHERE iu.last_checked > COALESCE(to_timestamp(0),
(SELECT MAX(timecreated) FROM {id_cnnstate}))''').format(
id_cnnstate=sql.Identifier(project, 'cnnstate'))
elif isinstance(minTimestamp, datetime):
timestampStr = sql.SQL(
'WHERE iu.last_checked > COALESCE(to_timestamp(0), %s)')
queryVals.append(minTimestamp)
elif isinstance(minTimestamp, int) or isinstance(minTimestamp, float):
timestampStr = sql.SQL(
'WHERE iu.last_checked > COALESCE(to_timestamp(0), to_timestamp(%s))'
)
queryVals.append(minTimestamp)
if minNumAnnoPerImage > 0:
queryVals.append(minNumAnnoPerImage)
if maxNumImages is None or maxNumImages <= 0:
limitStr = sql.SQL('')
else:
limitStr = sql.SQL('LIMIT %s')
queryVals.append(maxNumImages)
if minNumAnnoPerImage <= 0:
queryStr = sql.SQL('''
SELECT newestAnno.image FROM (
SELECT image, last_checked FROM {id_iu} AS iu
JOIN (
SELECT id AS iid
FROM {id_img}
WHERE corrupt IS NULL OR corrupt = FALSE
) AS imgQ
ON iu.image = imgQ.iid
{timestampStr}
ORDER BY iu.last_checked ASC
{limitStr}
) AS newestAnno;
''').format(id_iu=sql.Identifier(project, 'image_user'),
id_img=sql.Identifier(project, 'image'),
timestampStr=timestampStr,
limitStr=limitStr)
else:
queryStr = sql.SQL('''
SELECT newestAnno.image FROM (
SELECT image, last_checked FROM {id_iu} AS iu
JOIN (
SELECT id AS iid
FROM {id_img}
WHERE corrupt IS NULL OR corrupt = FALSE
) AS imgQ
ON iu.image = imgQ.iid
{timestampStr}
{conjunction} image IN (
SELECT image FROM (
SELECT image, COUNT(*) AS cnt
FROM {id_anno}
GROUP BY image
) AS annoCount
WHERE annoCount.cnt >= %s
)
ORDER BY iu.last_checked ASC
{limitStr}
) AS newestAnno;
''').format(id_iu=sql.Identifier(project, 'image_user'),
id_img=sql.Identifier(project, 'image'),
id_anno=sql.Identifier(project, 'annotation'),
timestampStr=timestampStr,
conjunction=(sql.SQL('WHERE') if minTimestamp is None
else sql.SQL('AND')),
limitStr=limitStr)
imageIDs = self.dbConn.execute(queryStr, tuple(queryVals), 'all')
imageIDs = [i['image'] for i in imageIDs]
if numChunks > 1:
# split for distribution across workers (TODO: also specify subset size for multiple jobs; randomly draw if needed)
imageIDs = array_split(imageIDs, max(1,
len(imageIDs) // numChunks))
else:
imageIDs = [imageIDs]
print("Assembled training images into {} chunks (length of first: {})".
format(len(imageIDs), len(imageIDs[0])))
return imageIDs
def get_inference_images(self,
project,
epoch=None,
numEpochs=None,
goldenQuestionsOnly=False,
forceUnlabeled=False,
maxNumImages=None,
numChunks=1):
'''
Queries the database for the latest images to be used for inference after model training.
Returns a list with image UUIDs accordingly, split into the number of available workers.
#TODO: goldenQuestionsOnly
'''
if maxNumImages is None or maxNumImages <= 0:
queryResult = self.dbConn.execute(
'''
SELECT maxNumImages_inference
FROM aide_admin.project
WHERE shortname = %s;''', (project, ), 1)
maxNumImages = queryResult[0]['maxnumimages_inference']
queryVals = (maxNumImages, )
# load the IDs of the images that are being subjected to inference
sql = self.sqlBuilder.getInferenceQueryString(project, forceUnlabeled,
maxNumImages)
imageIDs = self.dbConn.execute(sql, queryVals, 'all')
imageIDs = [i['image'] for i in imageIDs]
# # split for distribution across workers
# if maxNumWorkers != 1:
# # only query the number of available workers if more than one is specified to save time
# num_available = self._get_num_available_workers()
# if maxNumWorkers == -1:
# maxNumWorkers = num_available #TODO: more than one process per worker?
# else:
# maxNumWorkers = min(maxNumWorkers, num_available)
if numChunks > 1:
imageIDs = array_split(imageIDs, max(1,
len(imageIDs) // numChunks))
else:
imageIDs = [imageIDs]
return imageIDs
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.usersLoggedIn = {} # username -> {timestamp, sessionToken}
Wrapper for the Celery message broker concerning
the Model Marketplace module.
2020-21 Benjamin Kellenberger
'''
import os
from celery import current_app
from .marketplaceWorker import ModelMarketplaceWorker
from modules.Database.app import Database
from util.configDef import Config
# initialize Model Marketplace worker
modules = os.environ['AIDE_MODULES']
config = Config()
worker = ModelMarketplaceWorker(config, Database(config))
@current_app.task(name='ModelMarketplace.shareModel')
def share_model(project, username, modelID, modelName, modelDescription, tags,
public, anonymous):
return worker.shareModel(project, username, modelID, modelName,
modelDescription, tags, public, anonymous)
@current_app.task(name='ModelMarketplace.importModelDatabase')
def import_model_database(modelID, project, username):
return worker.importModelDatabase(project, username, modelID)
@current_app.task(name='ModelMarketplace.importModelURI')
def __init__(self, config, passiveMode=False):
self.config = config
self.dbConnector = Database(config)
self.passiveMode = passiveMode
self._init_fileserver()
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.labelUImiddleware = DBMiddleware(config)
self._init_available_ai_models()
class DataWorker:
FILENAMES_PROHIBITED_CHARS = (
'<',
'<',
'>',
'>',
'..',
'/',
'\\',
'|',
'?',
'*',
':' # for macOS
)
NUM_IMAGES_LIMIT = 4096 # maximum number of images that can be queried at once (to avoid bottlenecks)
def __init__(self, config, passiveMode=False):
self.config = config
self.dbConnector = Database(config)
self.countPattern = re.compile('\_[0-9]+$')
self.passiveMode = passiveMode
self.tempDir = self.config.getProperty('FileServer',
'tempfiles_dir',
type=str,
fallback=tempfile.gettempdir())
def aide_internal_notify(self, message):
'''
Used for AIDE administrative communication,
e.g. for setting up queues.
'''
if self.passiveMode:
return
if 'task' in message:
if message['task'] == 'create_project_folders':
# set up folders for a newly created project
if 'projectName' in message:
destPath = os.path.join(
self.config.getProperty('FileServer',
'staticfiles_dir'),
message['projectName'])
os.makedirs(destPath, exist_ok=True)
''' Image administration functionalities '''
def listImages(self,
project,
folder=None,
imageAddedRange=None,
lastViewedRange=None,
viewcountRange=None,
numAnnoRange=None,
numPredRange=None,
orderBy=None,
order='desc',
startFrom=None,
limit=None):
'''
Returns a list of images, with ID, filename,
date image was added, viewcount, number of annotations,
number of predictions, and last time viewed, for a given
project.
The list can be filtered by all those properties (e.g.
date and time image was added, last checked; number of
annotations, etc.), as well as limited in length (images
are sorted by date_added).
'''
queryArgs = []
filterStr = ''
if folder is not None and isinstance(folder, str):
filterStr += ' filename LIKE %s '
queryArgs.append(folder + '%')
if imageAddedRange is not None: #TODO
filterStr += 'AND date_added >= to_timestamp(%s) AND date_added <= to_timestamp(%s) '
queryArgs.append(imageAddedRange[0])
queryArgs.append(imageAddedRange[1])
if lastViewedRange is not None: #TODO
filterStr += 'AND last_viewed >= to_timestamp(%s) AND last_viewed <= to_timestamp(%s) '
queryArgs.append(lastViewedRange[0])
queryArgs.append(lastViewedRange[1])
if viewcountRange is not None:
filterStr += 'AND viewcount >= %s AND viewcount <= %s '
queryArgs.append(viewcountRange[0])
queryArgs.append(viewcountRange[1])
if numAnnoRange is not None:
filterStr += 'AND num_anno >= %s AND numAnno <= %s '
queryArgs.append(numAnnoRange[0])
queryArgs.append(numAnnoRange[1])
if numPredRange is not None:
filterStr += 'AND num_pred >= %s AND num_pred <= %s '
queryArgs.append(numPredRange[0])
queryArgs.append(numPredRange[1])
if startFrom is not None:
if not isinstance(startFrom, UUID):
try:
startFrom = UUID(startFrom)
except:
startFrom = None
if startFrom is not None:
filterStr += ' AND img.id > %s '
queryArgs.append(startFrom)
filterStr = filterStr.strip()
if filterStr.startswith('AND'):
filterStr = filterStr[3:]
if len(filterStr.strip()):
filterStr = 'WHERE ' + filterStr
filterStr = sql.SQL(filterStr)
orderStr = sql.SQL('ORDER BY img.id ASC')
if orderBy is not None:
orderStr = sql.SQL('ORDER BY {} {}, img.id ASC').format(
sql.SQL(orderBy), sql.SQL(order))
limitStr = sql.SQL('')
if isinstance(limit, float):
if not math.isnan(limit):
limit = int(limit)
else:
limit = self.NUM_IMAGES_LIMIT
elif isinstance(limit, str):
try:
limit = int(limit)
except:
limit = self.NUM_IMAGES_LIMIT
elif not isinstance(limit, int):
limit = self.NUM_IMAGES_LIMIT
limit = max(min(limit, self.NUM_IMAGES_LIMIT), 1)
limitStr = sql.SQL('LIMIT %s')
queryArgs.append(limit)
queryStr = sql.SQL('''
SELECT img.id, filename, EXTRACT(epoch FROM date_added) AS date_added,
COALESCE(viewcount, 0) AS viewcount,
EXTRACT(epoch FROM last_viewed) AS last_viewed,
COALESCE(num_anno, 0) AS num_anno,
COALESCE(num_pred, 0) AS num_pred,
img.isGoldenQuestion
FROM {id_img} AS img
FULL OUTER JOIN (
SELECT image, COUNT(*) AS viewcount, MAX(last_checked) AS last_viewed
FROM {id_iu}
GROUP BY image
) AS iu
ON img.id = iu.image
FULL OUTER JOIN (
SELECT image, COUNT(*) AS num_anno
FROM {id_anno}
GROUP BY image
) AS anno
ON img.id = anno.image
FULL OUTER JOIN (
SELECT image, COUNT(*) AS num_pred
FROM {id_pred}
GROUP BY image
) AS pred
ON img.id = pred.image
{filter}
{order}
{limit}
''').format(id_img=sql.Identifier(project, 'image'),
id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'),
filter=filterStr,
order=orderStr,
limit=limitStr)
result = self.dbConnector.execute(queryStr, tuple(queryArgs), 'all')
for idx in range(len(result)):
result[idx]['id'] = str(result[idx]['id'])
return result
def uploadImages(self,
project,
images,
existingFiles='keepExisting',
splitImages=False,
splitProperties=None):
'''
Receives a dict of files (bottle.py file format),
verifies their file extension and checks if they
are loadable by PIL.
If they are, they are saved to disk in the project's
image folder, and registered in the database.
Parameter "existingFiles" can be set as follows:
- "keepExisting" (default): if an image already exists on
disk with the same path/file name, the new image will be
renamed with an underscore and trailing number.
- "skipExisting": do not save images that already exist on
disk under the same path/file name.
- "replaceExisting": overwrite images that exist with the
same path/file name. Note: in this case all existing anno-
tations, predictions, and other metadata about those images,
will be removed from the database.
If "splitImages" is True, the uploaded images will be automati-
cally divided into patches on a regular grid according to what
is defined in "splitProperties". For example, the following
definition:
splitProperties = {
'patchSize': (800, 600),
'stride': (400, 300),
'tight': True
}
would divide the images into patches of size 800x600, with over-
lap of 50% (denoted by the "stride" being half the "patchSize"),
and with all patches completely inside the original image (para-
meter "tight" makes the last patches to the far left and bottom
of the image being fully inside the original image; they are shif-
ted if needed).
Instead of the full images, the patches are stored on disk and re-
ferenced through the database. The name format for patches is
"imageName_x_y.jpg", with "imageName" denoting the name of the ori-
ginal image, and "x" and "y" the left and top position of the patch
inside the original image.
Returns image keys for images that were successfully
saved, and keys and error messages for those that
were not.
'''
imgPaths_valid = []
imgs_valid = []
imgs_warn = {}
imgs_error = {}
for key in images.keys():
try:
nextUpload = images[key]
nextFileName = nextUpload.raw_filename
#TODO: check if raw_filename is compatible with uploads made from Windows
# check if correct file suffix
_, ext = os.path.splitext(nextFileName)
if not ext.lower() in valid_image_extensions:
raise Exception(f'Invalid file type (*{ext})')
# check if loadable as image
cache = io.BytesIO()
nextUpload.save(cache)
try:
image = Image.open(cache)
except Exception:
raise Exception('File is not a valid image.')
# prepare image(s) to save to disk
parent, filename = os.path.split(nextFileName)
destFolder = os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'),
project, parent)
os.makedirs(destFolder, exist_ok=True)
images = []
filenames = []
if not splitImages:
# upload the single image directly
images.append(image)
filenames.append(filename)
else:
# split image into patches instead
images, coords = split_image(image,
splitProperties['patchSize'],
splitProperties['stride'],
splitProperties['tight'])
bareFileName, ext = os.path.splitext(filename)
filenames = [
f'{bareFileName}_{c[0]}_{c[1]}{ext}' for c in coords
]
# register and save all the images
for i in range(len(images)):
subImage = images[i]
subFilename = filenames[i]
absFilePath = os.path.join(destFolder, subFilename)
# check if an image with the same name does not already exist
newFileName = subFilename
fileExists = os.path.exists(absFilePath)
if fileExists:
if existingFiles == 'keepExisting':
# rename new file
while (os.path.exists(absFilePath)):
# rename file
fn, ext = os.path.splitext(newFileName)
match = self.countPattern.search(fn)
if match is None:
newFileName = fn + '_1' + ext
else:
# parse number
number = int(fn[match.span()[0] +
1:match.span()[1]])
newFileName = fn[:match.span(
)[0]] + '_' + str(number + 1) + ext
absFilePath = os.path.join(
destFolder, newFileName)
if not os.path.exists(absFilePath):
imgs_warn[
key] = 'An image with name "{}" already exists under given path on disk. Image has been renamed to "{}".'.format(
subFilename, newFileName)
elif existingFiles == 'skipExisting':
# ignore new file
imgs_warn[
key] = f'Image "{newFileName}" already exists on disk and has been skipped.'
imgs_valid.append(key)
imgPaths_valid.append(
os.path.join(parent, newFileName))
continue
elif existingFiles == 'replaceExisting':
# overwrite new file; first remove metadata
queryStr = sql.SQL('''
DELETE FROM {id_iu}
WHERE image = (
SELECT id FROM {id_img}
WHERE filename = %s
);
DELETE FROM {id_anno}
WHERE image = (
SELECT id FROM {id_img}
WHERE filename = %s
);
DELETE FROM {id_pred}
WHERE image = (
SELECT id FROM {id_img}
WHERE filename = %s
);
DELETE FROM {id_img}
WHERE filename = %s;
''').format(
id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'),
id_img=sql.Identifier(project, 'image'))
self.dbConnector.execute(queryStr,
tuple([nextFileName] * 4),
None)
# remove file
try:
os.remove(absFilePath)
imgs_warn[key] = 'Image "{}" already existed on disk and has been deleted.\n'.format(newFileName) + \
'All metadata (views, annotations, predictions) have been removed from the database.'
except:
imgs_warn[key] = 'Image "{}" already existed on disk but could not be deleted.\n'.format(newFileName) + \
'All metadata (views, annotations, predictions) have been removed from the database.'
# write to disk
fileParent, _ = os.path.split(absFilePath)
if len(fileParent):
os.makedirs(fileParent, exist_ok=True)
subImage.save(absFilePath)
imgs_valid.append(key)
imgPaths_valid.append(os.path.join(parent, newFileName))
except Exception as e:
imgs_error[key] = str(e)
# register valid images in database
if len(imgPaths_valid):
queryStr = sql.SQL('''
INSERT INTO {id_img} (filename)
VALUES %s
ON CONFLICT (filename) DO NOTHING;
''').format(id_img=sql.Identifier(project, 'image'))
self.dbConnector.insert(queryStr, [(i, ) for i in imgPaths_valid])
result = {
'imgs_valid': imgs_valid,
'imgPaths_valid': imgPaths_valid,
'imgs_warn': imgs_warn,
'imgs_error': imgs_error
}
return result
def scanForImages(self, project):
'''
Searches the project image folder on disk for
files that are valid, but have not (yet) been added
to the database.
Returns a list of paths with files.
'''
# scan disk for files
projectFolder = os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'), project)
if (not os.path.isdir(projectFolder)) and (
not os.path.islink(projectFolder)):
# no folder exists for the project (should not happen due to broadcast at project creation)
return []
imgs_disk = listDirectory(projectFolder, recursive=True)
# get all existing file paths from database
imgs_database = set()
queryStr = sql.SQL('''
SELECT filename FROM {id_img};
''').format(id_img=sql.Identifier(project, 'image'))
result = self.dbConnector.execute(queryStr, None, 'all')
for r in range(len(result)):
imgs_database.add(result[r]['filename'])
# filter
imgs_candidates = imgs_disk.difference(imgs_database)
return list(imgs_candidates)
def addExistingImages(self, project, imageList=None):
'''
Scans the project folder on the file system
for images that are physically saved, but not
(yet) added to the database.
Adds them to the project's database schema.
If an imageList iterable is provided, only
the intersection between identified images on
disk and in the iterable are added.
If 'imageList' is a string with contents 'all',
all untracked images will be added.
Returns a list of image IDs and file names that
were eventually added to the project database schema.
'''
# get all images on disk that are not in database
imgs_candidates = self.scanForImages(project)
if imageList is None or (isinstance(imageList, str)
and imageList.lower() == 'all'):
imgs_add = imgs_candidates
else:
if isinstance(imageList, dict):
imageList = list(imageList.keys())
imgs_add = list(set(imgs_candidates).intersection(set(imageList)))
if not len(imgs_add):
return 0, []
# add to database
queryStr = sql.SQL('''
INSERT INTO {id_img} (filename)
VALUES %s;
''').format(id_img=sql.Identifier(project, 'image'))
self.dbConnector.insert(queryStr, tuple([(i, ) for i in imgs_add]))
# get IDs of newly added images
queryStr = sql.SQL('''
SELECT id, filename FROM {id_img}
WHERE filename IN %s;
''').format(id_img=sql.Identifier(project, 'image'))
result = self.dbConnector.execute(queryStr, (tuple(imgs_add), ), 'all')
status = (0 if result is not None and len(result) else 1) #TODO
return status, result
def removeImages(self,
project,
imageList,
forceRemove=False,
deleteFromDisk=False):
'''
Receives an iterable of image IDs and removes them
from the project database schema, including associated
user views, annotations, and predictions made.
Only removes entries if no user views, annotations, and
predictions exist, or else if "forceRemove" is True.
If "deleteFromDisk" is True, the image files are also
deleted from the project directory on the file system.
Returns a list of images that were deleted.
'''
imageList = tuple([(UUID(i), ) for i in imageList])
queryArgs = []
deleteArgs = []
if forceRemove:
queryStr = sql.SQL('''
SELECT id, filename
FROM {id_img}
WHERE id IN %s;
''').format(id_img=sql.Identifier(project, 'image'))
queryArgs = tuple([imageList])
deleteStr = sql.SQL('''
DELETE FROM {id_iu} WHERE image IN %s;
DELETE FROM {id_anno} WHERE image IN %s;
DELETE FROM {id_pred} WHERE image IN %s;
DELETE FROM {id_img} WHERE id IN %s;
''').format(id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'),
id_img=sql.Identifier(project, 'image'))
deleteArgs = tuple([imageList] * 4)
else:
queryStr = sql.SQL('''
SELECT id, filename
FROM {id_img}
WHERE id IN %s
AND id NOT IN (
SELECT image FROM {id_iu}
WHERE image IN %s
UNION ALL
SELECT image FROM {id_anno}
WHERE image IN %s
UNION ALL
SELECT image FROM {id_pred}
WHERE image IN %s
);
''').format(id_img=sql.Identifier(project, 'image'),
id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'))
queryArgs = tuple([imageList] * 4)
deleteStr = sql.SQL('''
DELETE FROM {id_img}
WHERE id IN %s
AND id NOT IN (
SELECT image FROM {id_iu}
WHERE image IN %s
UNION ALL
SELECT image FROM {id_anno}
WHERE image IN %s
UNION ALL
SELECT image FROM {id_pred}
WHERE image IN %s
);
''').format(id_img=sql.Identifier(project, 'image'),
id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'))
deleteArgs = tuple([imageList] * 4)
# retrieve images to be deleted
imgs_del = self.dbConnector.execute(queryStr, queryArgs, 'all')
if imgs_del is None:
imgs_del = []
if len(imgs_del):
# delete images
self.dbConnector.execute(deleteStr, deleteArgs, None)
if deleteFromDisk:
projectFolder = os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'),
project)
if os.path.isdir(projectFolder) or os.path.islink(
projectFolder):
for i in imgs_del:
filePath = os.path.join(projectFolder, i['filename'])
if os.path.isfile(filePath):
os.remove(filePath)
# convert UUID
for idx in range(len(imgs_del)):
imgs_del[idx]['id'] = str(imgs_del[idx]['id'])
return imgs_del
def removeOrphanedImages(self, project):
'''
Queries the project's image entries in the database and retrieves
entries for which no image can be found on disk anymore. Removes
and returns those entries and all associated (meta-) data from the
database.
'''
imgs_DB = self.dbConnector.execute(
sql.SQL('''
SELECT id, filename FROM {id_img};
''').format(id_img=sql.Identifier(project, 'image')), None, 'all')
projectFolder = os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'), project)
if (not os.path.isdir(projectFolder)) and (
not os.path.islink(projectFolder)):
return []
imgs_disk = listDirectory(projectFolder, recursive=True)
imgs_disk = set(imgs_disk)
# get orphaned images
imgs_orphaned = []
for i in imgs_DB:
if i['filename'] not in imgs_disk:
imgs_orphaned.append(i['id'])
# imgs_orphaned = list(set(imgs_DB).difference(imgs_disk))
if not len(imgs_orphaned):
return []
# remove
self.dbConnector.execute(
sql.SQL('''
DELETE FROM {id_iu} WHERE image IN %s;
DELETE FROM {id_anno} WHERE image IN %s;
DELETE FROM {id_pred} WHERE image IN %s;
DELETE FROM {id_img} WHERE id IN %s;
''').format(id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'),
id_img=sql.Identifier(project, 'image')),
tuple([tuple(imgs_orphaned)] * 4), None)
return imgs_orphaned
def prepareDataDownload(self,
project,
dataType='annotation',
userList=None,
dateRange=None,
extraFields=None,
segmaskFilenameOptions=None,
segmaskEncoding='rgb'):
'''
Polls the database for project data according to the
specified restrictions:
- dataType: "annotation" or "prediction"
- userList: for type "annotation": None (all users) or
an iterable of user names
- dateRange: None (all dates) or two values for a mini-
mum and maximum timestamp
- extraFields: None (no field) or dict of keywords and bools for
additional fields (e.g. browser meta) to be queried.
- segmaskFilenameOptions: customization parameters for segmentation
mask images' file names.
- segmaskEncoding: encoding of the segmentation mask pixel
values ("rgb" or "indexed")
Creates a file in this machine's temporary directory
and returns the file name to it.
Note that in some cases (esp. for semantic segmentation),
the number of queryable entries may be limited due to
file size and free disk space restrictions. An upper cei-
ling is specified in the configuration *.ini file ('TODO')
'''
now = datetime.now(tz=pytz.utc)
# argument check
if userList is None:
userList = []
elif isinstance(userList, str):
userList = [userList]
if dateRange is None:
dateRange = []
elif len(dateRange) == 1:
dateRange = [dateRange, now]
if extraFields is None or not isinstance(extraFields, dict):
extraFields = {'meta': False}
else:
if not 'meta' in extraFields or not isinstance(
extraFields['meta'], bool):
extraFields['meta'] = False
if segmaskFilenameOptions is None:
segmaskFilenameOptions = {
'baseName': 'filename',
'prefix': '',
'suffix': ''
}
else:
if not 'baseName' in segmaskFilenameOptions or \
segmaskFilenameOptions['baseName'] not in ('filename', 'id'):
segmaskFilenameOptions['baseName'] = 'filename'
try:
segmaskFilenameOptions['prefix'] = str(
segmaskFilenameOptions['prefix'])
except:
segmaskFilenameOptions['prefix'] = ''
try:
segmaskFilenameOptions['suffix'] = str(
segmaskFilenameOptions['suffix'])
except:
segmaskFilenameOptions['suffix'] = ''
for char in self.FILENAMES_PROHIBITED_CHARS:
segmaskFilenameOptions['prefix'] = segmaskFilenameOptions[
'prefix'].replace(char, '_')
segmaskFilenameOptions['suffix'] = segmaskFilenameOptions[
'suffix'].replace(char, '_')
# check metadata type: need to deal with segmentation masks separately
if dataType == 'annotation':
metaField = 'annotationtype'
elif dataType == 'prediction':
metaField = 'predictiontype'
else:
raise Exception('Invalid dataType specified ({})'.format(dataType))
metaType = self.dbConnector.execute(
'''
SELECT {} FROM aide_admin.project
WHERE shortname = %s;
'''.format(metaField), (project, ), 1)[0][metaField]
if metaType.lower() == 'segmentationmasks':
is_segmentation = True
fileExtension = '.zip'
# create indexed color palette for segmentation masks
if segmaskEncoding == 'indexed':
try:
indexedColors = []
labelClasses = self.dbConnector.execute(
sql.SQL('''
SELECT idx, color FROM {id_lc} ORDER BY idx ASC;
''').format(
id_lc=sql.Identifier(project, 'labelclass')), None,
'all')
currentIndex = 1
for lc in labelClasses:
if lc['idx'] == 0:
# background class
continue
while currentIndex < lc['idx']:
# gaps in label classes; fill with zeros
indexedColors.extend([0, 0, 0])
currentIndex += 1
color = lc['color']
if color is None:
# no color specified; add from defaults
#TODO
indexedColors.extend([0, 0, 0])
else:
# convert to RGB format
indexedColors.extend(helpers.hexToRGB(color))
except:
# an error occurred; don't convert segmentation mask to indexed colors
indexedColors = None
else:
indexedColors = None
else:
is_segmentation = False
fileExtension = '.txt' #TODO: support JSON?
# prepare output file
filename = 'aide_query_{}'.format(
now.strftime('%Y-%m-%d_%H-%M-%S')) + fileExtension
destPath = os.path.join(self.tempDir, 'aide/downloadRequests', project)
os.makedirs(destPath, exist_ok=True)
destPath = os.path.join(destPath, filename)
# generate query
queryArgs = []
tableID = sql.Identifier(project, dataType)
userStr = sql.SQL('')
iuStr = sql.SQL('')
dateStr = sql.SQL('')
queryFields = [
'filename',
'isGoldenQuestion',
'date_image_added',
'last_requested_image',
'image_corrupt' # default image fields
]
if dataType == 'annotation':
iuStr = sql.SQL('''
JOIN (SELECT image AS iu_image, username AS iu_username, viewcount, last_checked, last_time_required FROM {id_iu}) AS iu
ON t.image = iu.iu_image
AND t.username = iu.iu_username
''').format(id_iu=sql.Identifier(project, 'image_user'))
if len(userList):
userStr = sql.SQL('WHERE username IN %s')
queryArgs.append(tuple(userList))
queryFields.extend(
getattr(QueryStrings_annotation, metaType).value)
queryFields.extend([
'username', 'viewcount', 'last_checked', 'last_time_required'
]) #TODO: make customizable
else:
queryFields.extend(
getattr(QueryStrings_prediction, metaType).value)
if len(dateRange):
if len(userStr.string):
dateStr = sql.SQL(
' AND timecreated >= to_timestamp(%s) AND timecreated <= to_timestamp(%s)'
)
else:
dateStr = sql.SQL(
'WHERE timecreated >= to_timestamp(%s) AND timecreated <= to_timestamp(%s)'
)
queryArgs.extend(dateRange)
if not is_segmentation:
# join label classes
lcStr = sql.SQL('''
JOIN (SELECT id AS lcID, name AS labelclass_name, idx AS labelclass_index
FROM {id_lc}
) AS lc
ON label = lc.lcID
''').format(id_lc=sql.Identifier(project, 'labelclass'))
queryFields.extend(['labelclass_name', 'labelclass_index'])
else:
lcStr = sql.SQL('')
# remove redundant query fields
queryFields = set(queryFields)
for key in extraFields.keys():
if not extraFields[key]:
queryFields.remove(key)
queryFields = list(queryFields)
queryStr = sql.SQL('''
SELECT * FROM {tableID} AS t
JOIN (
SELECT id AS imgID, filename, isGoldenQuestion, date_added AS date_image_added, last_requested AS last_requested_image, corrupt AS image_corrupt
FROM {id_img}
) AS img ON t.image = img.imgID
{lcStr}
{iuStr}
{userStr}
{dateStr}
''').format(tableID=tableID,
id_img=sql.Identifier(project, 'image'),
lcStr=lcStr,
iuStr=iuStr,
userStr=userStr,
dateStr=dateStr)
# query and process data
if is_segmentation:
mainFile = zipfile.ZipFile(destPath, 'w', zipfile.ZIP_DEFLATED)
else:
mainFile = open(destPath, 'w')
metaStr = '; '.join(queryFields) + '\n'
with self.dbConnector.execute_cursor(queryStr,
tuple(queryArgs)) as cursor:
while True:
b = cursor.fetchone()
if b is None:
break
if is_segmentation:
# convert and store segmentation mask separately
segmask_filename = 'segmentation_masks/'
if segmaskFilenameOptions['baseName'] == 'id':
innerFilename = b['image']
parent = ''
else:
innerFilename = b['filename']
parent, innerFilename = os.path.split(innerFilename)
finalFilename = os.path.join(
parent,
segmaskFilenameOptions['prefix'] + innerFilename +
segmaskFilenameOptions['suffix'] + '.tif')
segmask_filename += finalFilename
segmask = base64ToImage(b['segmentationmask'], b['width'],
b['height'])
if indexedColors is not None and len(indexedColors) > 0:
# convert to indexed color and add color palette from label classes
segmask = segmask.convert('RGB').convert(
'P', palette=Image.ADAPTIVE, colors=3)
segmask.putpalette(indexedColors)
# save
bio = io.BytesIO()
segmask.save(bio, 'TIFF')
mainFile.writestr(segmask_filename, bio.getvalue())
# store metadata
metaLine = ''
for field in queryFields:
if field.lower() == 'segmentationmask':
continue
metaLine += '{}; '.format(b[field.lower()])
metaStr += metaLine + '\n'
if is_segmentation:
mainFile.writestr('query.txt', metaStr)
else:
mainFile.write(metaStr)
if is_segmentation:
# append separate text file for label classes
labelclassQuery = sql.SQL('''
SELECT id, name, color, labelclassgroup, idx AS labelclass_index
FROM {id_lc};
''').format(id_lc=sql.Identifier(project, 'labelclass'))
result = self.dbConnector.execute(labelclassQuery, None, 'all')
lcStr = 'id,name,color,labelclassgroup,labelclass_index\n'
for r in result:
lcStr += '{},{},{},{},{}\n'.format(r['id'], r['name'],
r['color'],
r['labelclassgroup'],
r['labelclass_index'])
mainFile.writestr('labelclasses.csv', lcStr)
mainFile.close()
return filename
def watchImageFolders(self):
'''
Queries all projects that have the image folder watch functionality
enabled and updates the projects, one by one, with the latest image
changes.
'''
projects = self.dbConnector.execute(
'''
SELECT shortname, watch_folder_remove_missing_enabled
FROM aide_admin.project
WHERE watch_folder_enabled IS TRUE;
''', None, 'all')
for p in projects:
pName = p['shortname']
# add new images
_, imgs_added = self.addExistingImages(pName, None)
# remove orphaned images (if enabled)
if p['watch_folder_remove_missing_enabled']:
imgs_orphaned = self.removeOrphanedImages(pName)
if len(imgs_added) or len(imgs_orphaned):
print(
f'[Project {pName}] {len(imgs_added)} new images found and added, {len(imgs_orphaned)} orphaned images removed from database.'
)
elif len(imgs_added):
print(
f'[Project {pName}] {len(imgs_added)} new images found and added.'
)
def deleteProject(self, project, deleteFiles=False):
'''
Irreproducibly deletes a project, including all data and metadata, from the database.
If "deleteFiles" is True, then any data on disk (images, etc.) are also deleted.
This cannot be undone.
'''
print(f'Deleting project with shortname "{project}"...')
# remove database entries
print('\tRemoving database entries...')
self.dbConnector.execute(
'''
DELETE FROM aide_admin.authentication
WHERE project = %s;
DELETE FROM aide_admin.project
WHERE shortname = %s;
''', (
project,
project,
), None
) # already done by DataAdministration.middleware, but we do it again to be sure
self.dbConnector.execute('''
DROP SCHEMA IF EXISTS {} CASCADE;
'''.format(project), None, None) #TODO: Identifier?
if deleteFiles:
print('\tRemoving files...')
messages = []
def _onError(function, path, excinfo):
#TODO
from celery.contrib import rdb
rdb.set_trace()
messages.append({
'function': function,
'path': path,
'excinfo': excinfo
})
try:
shutil.rmtree(os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'),
project),
onerror=_onError)
except Exception as e:
messages.append(str(e))
return messages
return 0
class ProjectConfigMiddleware:
# prohibited project shortnames
PROHIBITED_SHORTNAMES = [
'con', # for MS Windows
'prn',
'aux',
'nul',
'com1',
'com2',
'com3',
'com4',
'com5',
'com6',
'com7',
'com8',
'com9',
'lpt1',
'lpt2',
'lpt3',
'lpt4',
'lpt5',
'lpt6',
'lpt7',
'lpt8',
'lpt9'
]
# prohibited project names (both as a whole and for shortnames)
PROHIBITED_NAMES = [
'', 'project', 'getavailableaimodels', 'getbackdrops',
'verifyprojectname', 'verifyprojectshort', 'newproject',
'createproject', 'statistics', 'static', 'getcreateaccountunrestricted'
'getprojects', 'about', 'favicon.ico', 'logincheck', 'logout', 'login',
'dologin', 'createaccount', 'loginscreen', 'accountexists',
'getauthentication', 'getusernames', 'docreateaccount', 'admin',
'getservicedetails', 'getceleryworkerdetails', 'getprojectdetails',
'getuserdetails', 'setpassword'
]
# prohibited name prefixes
PROHIBITED_NAME_PREFIXES = ['/', '?', '&']
# patterns that are prohibited anywhere for shortnames (replaced with underscores)
SHORTNAME_PATTERNS_REPLACE = [
'|',
'?',
'*',
':' # for macOS
]
# patterns that are prohibited anywhere for both short and long names (no replacement)
PROHIBITED_STRICT = ['<', '<', '>', '>', '..', '/', '\\']
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
# load default UI settings
try:
# check if custom default styles are provided
self.defaultUIsettings = json.load(
open('config/default_ui_settings.json', 'r'))
except:
# resort to built-in styles
self.defaultUIsettings = json.load(
open(
'modules/ProjectAdministration/static/json/default_ui_settings.json',
'r'))
@staticmethod
def _recursive_update(dictObject, target):
'''
Recursively iterates over all keys and sub-keys of "dictObject"
and its sub-dicts and copies over values from dict "target", if
they are available.
'''
for key in dictObject.keys():
if key in target:
if isinstance(dictObject[key], dict):
ProjectConfigMiddleware._recursive_update(
dictObject[key], target[key])
else:
dictObject[key] = target[key]
def getPlatformInfo(self, project, parameters=None):
'''
AIDE setup-specific platform metadata.
'''
# parse parameters (if provided) and compare with mutable entries
allParams = set(['server_uri', 'server_dir', 'watch_folder_interval'])
if parameters is not None and parameters != '*':
if isinstance(parameters, str):
parameters = [parameters.lower()]
else:
parameters = [p.lower() for p in parameters]
set(parameters).intersection_update(allParams)
else:
parameters = allParams
parameters = list(parameters)
response = {}
for param in parameters:
if param.lower() == 'server_uri':
uri = os.path.join(
self.config.getProperty('Server', 'dataServer_uri'),
project, 'files')
response[param] = uri
elif param.lower() == 'server_dir':
sdir = os.path.join(
self.config.getProperty('FileServer', 'staticfiles_dir'),
project)
response[param] = sdir
elif param.lower() == 'watch_folder_interval':
interval = self.config.getProperty('FileServer',
'watch_folder_interval',
type=float,
fallback=60)
response[param] = interval
return response
def getProjectImmutables(self, project):
queryStr = 'SELECT annotationType, predictionType, demoMode FROM aide_admin.project WHERE shortname = %s;'
result = self.dbConnector.execute(queryStr, (project, ), 1)
if result and len(result):
return {
'annotationType': result[0]['annotationtype'],
'predictionType': result[0]['predictiontype']
}
else:
return None
def getProjectInfo(self, project, parameters=None):
# parse parameters (if provided) and compare with mutable entries
allParams = set([
'name', 'description', 'ispublic', 'secret_token', 'demomode',
'interface_enabled', 'ui_settings',
'segmentation_ignore_unlabeled', 'ai_model_enabled',
'ai_model_library', 'ai_model_settings', 'ai_alcriterion_library',
'ai_alcriterion_settings', 'numimages_autotrain',
'minnumannoperimage', 'maxnumimages_train', 'watch_folder_enabled',
'watch_folder_remove_missing_enabled'
])
if parameters is not None and parameters != '*':
if isinstance(parameters, str):
parameters = [parameters.lower()]
else:
parameters = [p.lower() for p in parameters]
set(parameters).intersection_update(allParams)
else:
parameters = allParams
parameters = list(parameters)
sqlParameters = ','.join(parameters)
queryStr = sql.SQL('''
SELECT {} FROM aide_admin.project
WHERE shortname = %s;
''').format(sql.SQL(sqlParameters))
result = self.dbConnector.execute(queryStr, (project, ), 1)
result = result[0]
# assemble response
response = {}
for param in parameters:
value = result[param]
if param == 'ui_settings':
value = json.loads(value)
# auto-complete with defaults where missing
value = check_args(value, self.defaultUIsettings)
response[param] = value
return response
def renewSecretToken(self, project):
'''
Creates a new secret token, invalidating the old one.
'''
try:
newToken = secrets.token_urlsafe(32)
result = self.dbConnector.execute(
'''UPDATE aide_admin.project
SET secret_token = %s
WHERE shortname = %s;
SELECT secret_token FROM aide_admin.project
WHERE shortname = %s;
''', (
newToken,
project,
project,
), 1)
return result[0]['secret_token']
except:
# this normally should not happen, since we checked for the validity of the project
return None
def getProjectUsers(self, project):
'''
Returns a list of users that are enrolled in the project,
as well as their roles within the project.
'''
queryStr = sql.SQL(
'SELECT * FROM aide_admin.authentication WHERE project = %s;')
result = self.dbConnector.execute(queryStr, (project, ), 'all')
return result
def createProject(self, username, properties):
'''
Receives the most basic, mostly non-changeable settings for a new project
("properties") with the following entries:
- shortname
- owner (the current username)
- name
- description
- annotationType
- predictionType
More advanced settings (UI config, AI model, etc.) will be configured after
the initial project creation stage.
Verifies whether these settings are available for a new project. If they are,
it creates a new database schema for the project, adds an entry for it to the
admin schema table and makes the current user admin. Returns True in this case.
Otherwise raises an exception.
'''
shortname = properties['shortname']
# verify availability of the project name and shortname
if not self.getProjectNameAvailable(properties['name']):
raise Exception('Project name "{}" unavailable.'.format(
properties['name']))
if not self.getProjectShortNameAvailable(shortname):
raise Exception(
'Project shortname "{}" unavailable.'.format(shortname))
# load base SQL
with open('modules/ProjectAdministration/static/sql/create_schema.sql',
'r') as f:
queryStr = sql.SQL(f.read())
# determine annotation and prediction types and add fields accordingly
annotationFields = list(
getattr(Fields_annotation, properties['annotationType']).value)
predictionFields = list(
getattr(Fields_prediction, properties['predictionType']).value)
# create project schema
self.dbConnector.execute(
queryStr.format(
id_schema=sql.Identifier(shortname),
id_auth=sql.Identifier(
self.config.getProperty('Database', 'user')),
id_image=sql.Identifier(shortname, 'image'),
id_iu=sql.Identifier(shortname, 'image_user'),
id_labelclassGroup=sql.Identifier(shortname,
'labelclassgroup'),
id_labelclass=sql.Identifier(shortname, 'labelclass'),
id_annotation=sql.Identifier(shortname, 'annotation'),
id_cnnstate=sql.Identifier(shortname, 'cnnstate'),
id_prediction=sql.Identifier(shortname, 'prediction'),
id_workflow=sql.Identifier(shortname, 'workflow'),
id_workflowHistory=sql.Identifier(shortname,
'workflowhistory'),
annotation_fields=sql.SQL(', ').join(
[sql.SQL(field) for field in annotationFields]),
prediction_fields=sql.SQL(', ').join(
[sql.SQL(field) for field in predictionFields])), None,
None)
# register project
self.dbConnector.execute(
'''
INSERT INTO aide_admin.project (shortname, name, description,
owner,
secret_token,
interface_enabled,
annotationType, predictionType,
isPublic, demoMode,
ui_settings)
VALUES (
%s, %s, %s,
%s,
%s,
%s,
%s, %s,
%s, %s,
%s
);
''', (shortname, properties['name'],
(properties['description'] if 'description' in properties
else ''), username, secrets.token_urlsafe(32), False,
properties['annotationType'], properties['predictionType'],
False, False, json.dumps(self.defaultUIsettings)), None)
# register user in project
self.dbConnector.execute(
'''
INSERT INTO aide_admin.authentication (username, project, isAdmin)
VALUES (%s, %s, true);
''', (
username,
shortname,
), None)
# notify FileServer instance(s) to set up project folders
process = fileServer_interface.aide_internal_notify.si({
'task':
'create_project_folders',
'projectName':
shortname
})
process.apply_async(queue='aide_broadcast', ignore_result=True)
return True
def updateProjectSettings(self, project, projectSettings):
'''
TODO
'''
# check UI settings first
if 'ui_settings' in projectSettings:
if isinstance(projectSettings['ui_settings'], str):
projectSettings['ui_settings'] = json.loads(
projectSettings['ui_settings'])
fieldNames = [('welcomeMessage', str), ('numImagesPerBatch', int),
('minImageWidth', int), ('numImageColumns_max', int),
('defaultImage_w', int), ('defaultImage_h', int),
('styles', dict), ('enableEmptyClass', bool),
('showPredictions', bool),
('showPredictions_minConf', float),
('carryOverPredictions', bool),
('carryOverRule', str),
('carryOverPredictions_minConf', float),
('defaultBoxSize_w', int), ('defaultBoxSize_h', int),
('minBoxSize_w', int), ('minBoxSize_h', int)]
uiSettings_new, uiSettingsKeys_new = parse_parameters(
projectSettings['ui_settings'],
fieldNames,
absent_ok=True,
escape=True) #TODO: escape
# adopt current settings and replace values accordingly
uiSettings = self.dbConnector.execute(
'''SELECT ui_settings
FROM aide_admin.project
WHERE shortname = %s;
''', (project, ), 1)
uiSettings = json.loads(uiSettings[0]['ui_settings'])
for kIdx in range(len(uiSettingsKeys_new)):
if isinstance(uiSettings[uiSettingsKeys_new[kIdx]], dict):
ProjectConfigMiddleware._recursive_update(
uiSettings[uiSettingsKeys_new[kIdx]],
uiSettings_new[kIdx])
else:
uiSettings[uiSettingsKeys_new[kIdx]] = uiSettings_new[kIdx]
# auto-complete with defaults where missing
uiSettings = check_args(uiSettings, self.defaultUIsettings)
projectSettings['ui_settings'] = json.dumps(uiSettings)
# parse remaining parameters
fieldNames = [('description', str), ('isPublic', bool),
('secret_token', str), ('demoMode', bool),
('ui_settings', str), ('interface_enabled', bool),
('watch_folder_enabled', bool),
('watch_folder_remove_missing_enabled', bool)]
vals, params = parse_parameters(projectSettings,
fieldNames,
absent_ok=True,
escape=False)
vals.append(project)
# commit to DB
queryStr = sql.SQL('''UPDATE aide_admin.project
SET
{}
WHERE shortname = %s;
''').format(
sql.SQL(',').join(
[sql.SQL('{} = %s'.format(item)) for item in params]))
self.dbConnector.execute(queryStr, tuple(vals), None)
return True
def updateClassDefinitions(self, project, classdef, removeMissing=False):
'''
Updates the project's class definitions.
if "removeMissing" is set to True, label classes that are present
in the database, but not in "classdef," will be removed. Label
class groups will only be removed if they do not reference any
label class present in "classdef." This functionality is disallowed
in the case of segmentation masks.
'''
# check if project contains segmentation masks
metaType = self.dbConnector.execute(
'''
SELECT annotationType, predictionType FROM aide_admin.project
WHERE shortname = %s;
''', (project, ), 1)[0]
is_segmentation = any(
['segmentationmasks' in m.lower() for m in metaType.values()])
if is_segmentation:
removeMissing = False
# get current classes from database
db_classes = {}
db_groups = {}
if removeMissing:
queryStr = sql.SQL('''
SELECT * FROM {id_lc} AS lc
FULL OUTER JOIN (
SELECT id AS lcgid, name AS lcgname, parent, color
FROM {id_lcg}
) AS lcg
ON lc.labelclassgroup = lcg.lcgid
''').format(id_lc=sql.Identifier(project, 'labelclass'),
id_lcg=sql.Identifier(project, 'labelclassgroup'))
result = self.dbConnector.execute(queryStr, None, 'all')
for r in result:
if r['id'] is not None:
db_classes[r['id']] = r
if r['lcgid'] is not None:
if not r['lcgid'] in db_groups:
db_groups[r['lcgid']] = {**r, **{'num_children': 0}}
elif not 'lcgid' in db_groups[r['lcgid']]:
db_groups[r['lcgid']] = {**db_groups[r['lcgid']], **r}
if r['labelclassgroup'] is not None:
if not r['labelclassgroup'] in db_groups:
db_groups[r['labelclassgroup']] = {'num_children': 1}
else:
db_groups[r['labelclassgroup']]['num_children'] += 1
# parse provided class definitions list
unique_keystrokes = set()
classes_update = []
classgroups_update = []
def _parse_item(item, parent=None):
# get or create ID for item
try:
itemID = uuid.UUID(item['id'])
except:
itemID = uuid.uuid1()
while itemID in classes_update or itemID in classgroups_update:
itemID = uuid.uuid1()
entry = {
'id': itemID,
'name': item['name'],
'color': (None if not 'color' in item else item['color']),
'keystroke': None,
'labelclassgroup': parent
}
if 'children' in item:
# label class group
classgroups_update.append(entry)
for child in item['children']:
_parse_item(child, itemID)
else:
# label class
if 'keystroke' in item and not item[
'keystroke'] in unique_keystrokes:
entry['keystroke'] = item['keystroke']
unique_keystrokes.add(item['keystroke'])
classes_update.append(entry)
for item in classdef:
_parse_item(item, None)
# apply changes
if removeMissing:
queryArgs = []
if len(classes_update):
# remove all missing label classes
lcSpec = sql.SQL('WHERE id NOT IN %s')
queryArgs.append(tuple([(l['id'], ) for l in classes_update]))
else:
# remove all label classes
lcgSpec = sql.SQL('')
if len(classgroups_update):
# remove all missing labelclass groups
lcgSpec = sql.SQL('WHERE id NOT IN %s')
queryArgs.append(
tuple([(l['id'], ) for l in classgroups_update]))
else:
# remove all labelclass groups
lcgSpec = sql.SQL('')
queryStr = sql.SQL('''
DELETE FROM {id_lc}
{lcSpec};
DELETE FROM {id_lcg}
{lcgSpec};
''').format(id_lc=sql.Identifier(project, 'labelclass'),
id_lcg=sql.Identifier(project, 'labelclassgroup'),
lcSpec=lcSpec,
lcgSpec=lcgSpec)
self.dbConnector.execute(queryStr, tuple(queryArgs), None)
# add/update in order (groups, set their parents, label classes)
groups_new = [(
g['id'],
g['name'],
g['color'],
) for g in classgroups_update]
queryStr = sql.SQL('''
INSERT INTO {id_lcg} (id, name, color)
VALUES %s
ON CONFLICT (id) DO UPDATE SET
name = EXCLUDED.name,
color = EXCLUDED.color;
''').format( #TODO: on conflict(name)
id_lcg=sql.Identifier(project, 'labelclassgroup'))
self.dbConnector.insert(queryStr, groups_new)
# set parents
groups_parents = [
(
g['id'],
g['labelclassgroup'],
) for g in classgroups_update
if ('labelclassgroup' in g and g['labelclassgroup'] is not None)
]
queryStr = sql.SQL('''
UPDATE {id_lcg} AS lcg
SET parent = q.parent
FROM (VALUES %s) AS q(id, parent)
WHERE lcg.id = q.id;
''').format(id_lcg=sql.Identifier(project, 'labelclassgroup'))
self.dbConnector.insert(queryStr, groups_parents)
# insert/update label classes
lcdata = [(
l['id'],
l['name'],
l['color'],
l['keystroke'],
l['labelclassgroup'],
) for l in classes_update]
queryStr = sql.SQL('''
INSERT INTO {id_lc} (id, name, color, keystroke, labelclassgroup)
VALUES %s
ON CONFLICT (id) DO UPDATE
SET name = EXCLUDED.name,
color = EXCLUDED.color,
keystroke = EXCLUDED.keystroke,
labelclassgroup = EXCLUDED.labelclassgroup;
''').format( #TODO: on conflict(name)
id_lc=sql.Identifier(project, 'labelclass'))
self.dbConnector.insert(queryStr, lcdata)
return True
def getProjectNameAvailable(self, projectName):
'''
Returns True if the provided project (long) name is available.
'''
if not isinstance(projectName, str):
return False
projectName = projectName.strip().lower()
if not len(projectName):
return False
# check if name matches prohibited AIDE keywords (we do not replace long names)
if projectName in self.PROHIBITED_STRICT or any(
[p in projectName for p in self.PROHIBITED_STRICT]):
return False
if projectName in self.PROHIBITED_NAMES:
return False
if any(
[projectName.startswith(p)
for p in self.PROHIBITED_NAME_PREFIXES]):
return False
# check if name is already taken
result = self.dbConnector.execute(
'''SELECT 1 AS result
FROM aide_admin.project
WHERE name = %s;
''', (projectName, ), 1)
if result is None or not len(result):
return True
else:
return result[0]['result'] != 1
def getProjectShortNameAvailable(self, projectName):
'''
Returns True if the provided project shortname is available.
In essence, "available" means that a database schema with the given
name can be created (this includes Postgres schema name conventions).
Returns False otherwise.
'''
if not isinstance(projectName, str):
return False
projectName = projectName.strip().lower()
if not len(projectName):
return False
# check if name matches prohibited AIDE keywords; replace where possible
if projectName in self.PROHIBITED_STRICT or any(
[p in projectName for p in self.PROHIBITED_STRICT]):
return False
if projectName in self.PROHIBITED_NAMES or projectName in self.PROHIBITED_SHORTNAMES:
return False
if any(
[projectName.startswith(p)
for p in self.PROHIBITED_NAME_PREFIXES]):
return False
for p in self.SHORTNAME_PATTERNS_REPLACE:
projectName = projectName.replace(p, '_')
# check if provided name is valid as per Postgres conventions
matches = re.findall('(^(pg_|[0-9]).*|.*(\$|\s)+.*)', projectName)
if len(matches):
return False
# check if project shorthand already exists in database
result = self.dbConnector.execute(
'''SELECT 1 AS result
FROM information_schema.schemata
WHERE schema_name ilike %s
UNION ALL
SELECT 1 FROM aide_admin.project
WHERE shortname ilike %s;
''', (
projectName,
projectName,
), 2)
if result is None or not len(result):
return True
if len(result) == 2:
return result[0]['result'] != 1 and result[1]['result'] != 1
elif len(result) == 1:
return result[0]['result'] != 1
else:
return True
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.labelUImiddleware = DBMiddleware(config)
class ModelMarketplaceMiddleware:
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.labelUImiddleware = DBMiddleware(config)
def getModelsMarketplace(self, project):
'''
Returns a dict of model state meta data,
filtered by the project settings (model library;
annotation type, prediction type).
'''
# get project meta data (immutables, model library)
projectMeta = self.dbConnector.execute(
'''
SELECT annotationType, predictionType, ai_model_library
FROM aide_admin.project
WHERE shortname = %s;
''',
(project,),
1
)
if projectMeta is None or not len(projectMeta):
raise Exception(f'Project {project} could not be found in database.')
projectMeta = projectMeta[0]
annotationType = projectMeta['annotationtype']
predictionType = projectMeta['predictiontype']
# get matching model states
result = self.dbConnector.execute(
'''
SELECT * FROM (
SELECT id, name, description, labelclasses, model_library,
annotationType, predictionType, EXTRACT(epoch FROM timeCreated) AS time_created, alcriterion_library,
public, anonymous, selectCount,
CASE WHEN anonymous THEN NULL ELSE author END AS author,
CASE WHEN anonymous THEN NULL ELSE origin_project END AS origin_project,
CASE WHEN anonymous THEN NULL ELSE origin_uuid END AS origin_uuid
FROM aide_admin.modelMarketplace
WHERE annotationType = %s AND
predictionType = %s
AND (
public = TRUE OR
origin_project = %s
)
) AS mm
LEFT OUTER JOIN (
SELECT name AS projectName, shortname
FROM aide_admin.project
) AS pn
ON mm.origin_project = pn.shortname;
''',
(annotationType, predictionType, project),
'all'
)
if result is not None and len(result):
matchingStates = {}
for r in result:
stateID = str(r['id'])
values = {}
for key in r.keys():
if isinstance(r[key], UUID):
values[key] = str(r[key])
else:
values[key] = r[key]
matchingStates[stateID] = values
else:
matchingStates = {}
return matchingStates
def importModel(self, project, modelID):
# get model meta data
meta = self.dbConnector.execute('''
SELECT id, name, description, labelclasses, model_library,
annotationType, predictionType, timeCreated, alcriterion_library,
public, anonymous, selectCount,
CASE WHEN anonymous THEN NULL ELSE author END AS author,
CASE WHEN anonymous THEN NULL ELSE origin_project END AS origin_project,
CASE WHEN anonymous THEN NULL ELSE origin_uuid END AS origin_uuid
FROM aide_admin.modelMarketplace
WHERE id = %s;
''', (UUID(modelID),), 1)
# check if model is suitable for current project
#TODO
return 0
def shareModel(self, project, username, modelID, modelName, modelDescription,
public, anonymous):
#TODO: export as Celery task
modelID = UUID(modelID)
# check if model hasn't already been shared
isShared = self.dbConnector.execute('''
SELECT author
FROM aide_admin.modelMarketplace
WHERE origin_project = %s AND origin_uuid = %s;
''', (project, modelID), 'all')
if isShared is not None and len(isShared):
author = isShared[0]['author']
return {
'status': 2,
'message': f'Model state has already been shared by {author}.'
}
# get project immutables
immutables = self.labelUImiddleware.get_project_immutables(project)
# get label class info
labelclasses = json.dumps(self.labelUImiddleware.getClassDefinitions(project, False))
# check if name is unique (TODO: required?)
nameTaken = self.dbConnector.execute('''
SELECT COUNT(*) AS cnt
FROM aide_admin.modelMarketplace
WHERE name = %s;
''', (modelName,), 'all')
if nameTaken is not None and len(nameTaken) and nameTaken[0]['cnt']:
return {
'status': 3,
'message': f'A model state with name "{modelName}" already exists in the Model Marketplace.'
}
sharedModelID = self.dbConnector.execute(sql.SQL('''
INSERT INTO aide_admin.modelMarketplace
(name, description, labelclasses, author, statedict,
model_library, alCriterion_library,
annotationType, predictionType,
origin_project, origin_uuid, public, anonymous)
SELECT %s, %s, %s, %s, statedict,
model_library, alCriterion_library,
%s, %s,
%s, id, %s, %s
FROM {id_cnnstate} AS cnnS
WHERE id = %s
RETURNING id;
''').format(
id_cnnstate=sql.Identifier(project, 'cnnstate')
), (modelName, modelDescription, labelclasses, username,
immutables['annotationType'], immutables['predictionType'],
project, public, anonymous, UUID(modelID)))
return {
'status': 0,
'shared_model_id': sharedModelID
}
2019-21 Benjamin Kellenberger
'''
import os
from celery import current_app
from modules.AIWorker.app import AIWorker
from modules.Database.app import Database
from util.configDef import Config
# init AIWorker
modules = os.environ['AIDE_MODULES']
passiveMode = (os.environ['PASSIVE_MODE'] == '1' if 'PASSIVE_MODE'
in os.environ else False) or not ('aiworker' in modules.lower())
config = Config()
worker = AIWorker(config, Database(config), passiveMode)
@current_app.task(name='AIWorker.aide_internal_notify')
def aide_internal_notify(message):
return worker.aide_internal_notify(message)
@current_app.task(name='AIWorker.call_update_model', rate_limit=1)
def call_update_model(blank, numEpochs, project):
return worker.call_update_model(numEpochs, project)
@current_app.task(name='AIWorker.call_train', rate_limit=1)
def call_train(data, index, epoch, numEpochs, project, aiModelSettings):
if len(data) == 2 and data[1] is None:
class DBMiddleware():
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.project_immutables = {
} # project settings that cannot be changed (project shorthand -> {settings})
self._fetchProjectSettings()
self.sqlBuilder = SQLStringBuilder()
self.annoParser = AnnotationParser()
def _fetchProjectSettings(self):
# AI controller URI
aiControllerURI = self.config.getProperty('Server', 'aiController_uri')
if aiControllerURI is None or aiControllerURI.strip() == '':
# no AI backend configured
aiControllerURI = None
# global, project-independent settings
self.globalSettings = {
'indexURI':
self.config.getProperty('Server',
'index_uri',
type=str,
fallback='/'),
'dataServerURI':
self.config.getProperty('Server', 'dataServer_uri'),
'aiControllerURI':
aiControllerURI
}
# default styles
try:
# check if custom default styles are provided
self.defaultStyles = json.load(
open('config/default_ui_settings.json', 'r'))
except:
# resort to built-in styles
self.defaultStyles = json.load(
open(
'modules/ProjectAdministration/static/json/default_ui_settings.json',
'r'))
def _assemble_annotations(self, project, cursor, hideGoldenQuestionInfo):
response = {}
while True:
b = cursor.fetchone()
if b is None:
break
imgID = str(b['image'])
if not imgID in response:
response[imgID] = {
'fileName': b['filename'],
'predictions': {},
'annotations': {},
'last_checked': None
}
viewcount = b['viewcount']
if viewcount is not None:
response[imgID]['viewcount'] = viewcount
last_checked = b['last_checked']
if last_checked is not None:
if response[imgID]['last_checked'] is None:
response[imgID]['last_checked'] = last_checked
else:
response[imgID]['last_checked'] = max(
response[imgID]['last_checked'], last_checked)
if not hideGoldenQuestionInfo:
response[imgID]['isGoldenQuestion'] = b['isgoldenquestion']
# parse annotations and predictions
entryID = str(b['id'])
if b['ctype'] is not None:
colnames = self.sqlBuilder.getColnames(
self.project_immutables[project]['annotationType'],
self.project_immutables[project]['predictionType'],
b['ctype'])
entry = {}
for c in colnames:
value = b[c]
if isinstance(value, datetime):
value = value.timestamp()
elif isinstance(value, UUID):
value = str(value)
entry[c] = value
if b['ctype'] == 'annotation':
response[imgID]['annotations'][entryID] = entry
elif b['ctype'] == 'prediction':
response[imgID]['predictions'][entryID] = entry
return response
def _set_images_requested(self, project, imageIDs):
'''
Sets column "last_requested" of relation "image"
to the current date. This is done during image
querying to signal that an image has been requested,
but not (yet) viewed.
'''
# prepare insertion values
now = datetime.now(tz=pytz.utc)
vals = []
for key in imageIDs:
vals.append(key)
if len(vals):
queryStr = sql.SQL('''
UPDATE {id_img}
SET last_requested = %s
WHERE id IN %s;
''').format(id_img=sql.Identifier(project, 'image'))
self.dbConnector.execute(queryStr, (
now,
tuple(vals),
), None)
def _get_sample_metadata(self, metaType):
'''
Returns a dummy annotation or prediction for the sample
image in the "exampleData" folder, depending on the "metaType"
specified (i.e., labels, points, boundingBoxes, or segmentationMasks).
'''
if metaType == 'labels':
return {
'id': '00000000-0000-0000-0000-000000000000',
'label': '00000000-0000-0000-0000-000000000000',
'confidence': 1.0,
'priority': 1.0,
'viewcount': None
}
elif metaType == 'points' or metaType == 'boundingBoxes':
return {
'id': '00000000-0000-0000-0000-000000000000',
'label': '00000000-0000-0000-0000-000000000000',
'x': 0.542959427207637,
'y': 0.5322069489713102,
'width': 0.6133651551312653,
'height': 0.7407598263401316,
'confidence': 1.0,
'priority': 1.0,
'viewcount': None
}
elif metaType == 'segmentationMasks':
# read segmentation mask from disk
segmask = Image.open(
'modules/LabelUI/static/exampleData/sample_segmentationMask.tif'
)
segmask, width, height = helpers.imageToBase64(segmask)
return {
'id': '00000000-0000-0000-0000-000000000000',
'width': width,
'height': height,
'segmentationmask': segmask,
'confidence': 1.0,
'priority': 1.0,
'viewcount': None
}
else:
return {}
def get_project_immutables(self, project):
if project not in self.project_immutables:
queryStr = 'SELECT annotationType, predictionType, demoMode FROM aide_admin.project WHERE shortname = %s;'
result = self.dbConnector.execute(queryStr, (project, ), 1)
if result and len(result):
self.project_immutables[project] = {
'annotationType': result[0]['annotationtype'],
'predictionType': result[0]['predictiontype'],
'demoMode': helpers.checkDemoMode(project,
self.dbConnector)
}
else:
return None
return self.project_immutables[project]
def get_dynamic_project_settings(self, project):
queryStr = 'SELECT ui_settings FROM aide_admin.project WHERE shortname = %s;'
result = self.dbConnector.execute(queryStr, (project, ), 1)
result = json.loads(result[0]['ui_settings'])
# complete styles with defaults where necessary (may be required for project that got upgraded from v1)
result = helpers.check_args(result, self.defaultStyles)
return result
def getProjectSettings(self, project):
'''
Queries the database for general project-specific metadata, such as:
- Classes: names, indices, default colors
- Annotation type: one of {class labels, positions, bboxes}
'''
# publicly available info from DB
projSettings = self.getProjectInfo(project)
# label classes
projSettings['classes'] = self.getClassDefinitions(project)
# static and dynamic project settings and properties from configuration file
projSettings = {
**projSettings,
**self.get_project_immutables(project),
**self.get_dynamic_project_settings(project),
**self.globalSettings
}
# append project shorthand to AIController URI
if 'aiControllerURI' in projSettings and projSettings[
'aiControllerURI'] is not None and len(
projSettings['aiControllerURI']):
projSettings['aiControllerURI'] = os.path.join(
projSettings['aiControllerURI'], project) + '/'
return projSettings
def getProjectInfo(self, project):
'''
Returns safe, shareable information about the project
(i.e., users don't need to be part of the project to see these data).
'''
queryStr = '''
SELECT shortname, name, description, demoMode,
interface_enabled, archived, ai_model_enabled,
ai_model_library, ai_alcriterion_library,
segmentation_ignore_unlabeled
FROM aide_admin.project
WHERE shortname = %s
'''
result = self.dbConnector.execute(queryStr, (project, ), 1)[0]
# provide flag if AI model is available
aiModelAvailable = all([
result['ai_model_enabled'], result['ai_model_library'] is not None
and len(result['ai_model_library']),
result['ai_alcriterion_library'] is not None
and len(result['ai_alcriterion_library'])
])
return {
'projectShortname':
result['shortname'],
'projectName':
result['name'],
'projectDescription':
result['description'],
'demoMode':
result['demomode'],
'interface_enabled':
result['interface_enabled'] and not result['archived'],
'ai_model_available':
aiModelAvailable,
'segmentation_ignore_unlabeled':
result['segmentation_ignore_unlabeled']
}
def getClassDefinitions(self, project, showHidden=False):
'''
Returns a dictionary with entries for all classes in the project.
'''
# query data
if showHidden:
hiddenSpec = ''
else:
hiddenSpec = 'WHERE hidden IS false'
queryStr = sql.SQL('''
SELECT 'group' AS type, id, NULL as idx, name, color, parent, NULL AS keystroke, NULL AS hidden FROM {}
UNION ALL
SELECT 'class' AS type, id, idx, name, color, labelclassgroup, keystroke, hidden FROM {}
{};
''').format(sql.Identifier(project, 'labelclassgroup'),
sql.Identifier(project, 'labelclass'),
sql.SQL(hiddenSpec))
classData = self.dbConnector.execute(queryStr, None, 'all')
# assemble entries first
allEntries = {}
numClasses = 0
for cl in classData:
id = str(cl['id'])
entry = {
'id': id,
'name': cl['name'],
'color': cl['color'],
'parent':
str(cl['parent']) if cl['parent'] is not None else None,
'hidden': cl['hidden']
}
if cl['type'] == 'group':
entry['entries'] = {}
else:
entry['index'] = cl['idx']
entry['keystroke'] = cl['keystroke']
numClasses += 1
allEntries[id] = entry
# transform into tree
def _find_parent(tree, parentID):
if parentID is None:
return None
elif 'id' in tree and tree['id'] == parentID:
return tree
elif 'entries' in tree:
for ek in tree['entries'].keys():
rv = _find_parent(tree['entries'][ek], parentID)
if rv is not None:
return rv
return None
else:
return None
allEntries = {'entries': allEntries}
for key in list(allEntries['entries'].keys()):
entry = allEntries['entries'][key]
parentID = entry['parent']
del entry['parent']
if parentID is None:
# entry or group with no parent: append to root directly
allEntries['entries'][key] = entry
else:
# move item
parent = _find_parent(allEntries, parentID)
parent['entries'][key] = entry
del allEntries['entries'][key]
allEntries['numClasses'] = numClasses
return allEntries
def getBatch_fixed(self,
project,
username,
data,
hideGoldenQuestionInfo=True):
'''
Returns entries from the database based on the list of data entry identifiers specified.
'''
if not len(data):
return {'entries': {}}
# query
projImmutables = self.get_project_immutables(project)
queryStr = self.sqlBuilder.getFixedImagesQueryString(
project, projImmutables['annotationType'],
projImmutables['predictionType'], projImmutables['demoMode'])
# parse results
queryVals = (
tuple(UUID(d) for d in data),
username,
username,
)
if projImmutables['demoMode']:
queryVals = (tuple(UUID(d) for d in data), )
with self.dbConnector.execute_cursor(queryStr, queryVals) as cursor:
try:
response = self._assemble_annotations(project, cursor,
hideGoldenQuestionInfo)
# self.dbConnector.conn.commit()
except Exception as e:
print(e)
# self.dbConnector.conn.rollback()
finally:
pass
# cursor.close()
# mark images as requested
self._set_images_requested(project, response)
return {'entries': response}
def getBatch_auto(self,
project,
username,
order='unlabeled',
subset='default',
limit=None,
hideGoldenQuestionInfo=True):
'''
TODO: description
'''
# query
projImmutables = self.get_project_immutables(project)
queryStr = self.sqlBuilder.getNextBatchQueryString(
project, projImmutables['annotationType'],
projImmutables['predictionType'], order, subset,
projImmutables['demoMode'])
# limit (TODO: make 128 a hyperparameter)
if limit is None:
limit = 128
else:
limit = min(int(limit), 128)
# parse results
queryVals = (
username,
username,
limit,
username,
)
if projImmutables[
'demoMode']: #TODO: demoMode can now change dynamically
queryVals = (limit, )
with self.dbConnector.execute_cursor(queryStr, queryVals) as cursor:
response = self._assemble_annotations(project, cursor,
hideGoldenQuestionInfo)
# mark images as requested
self._set_images_requested(project, response)
return {'entries': response}
def getBatch_timeRange(self,
project,
minTimestamp,
maxTimestamp,
userList,
skipEmptyImages=False,
limit=None,
goldenQuestionsOnly=False,
hideGoldenQuestionInfo=True):
'''
Returns images that have been annotated within the given time range and/or
by the given user(s). All arguments are optional.
Useful for reviewing existing annotations.
'''
# query string
projImmutables = self.get_project_immutables(project)
queryStr = self.sqlBuilder.getDateQueryString(
project, projImmutables['annotationType'], minTimestamp,
maxTimestamp, userList, skipEmptyImages, goldenQuestionsOnly)
# check validity and provide arguments
queryVals = []
if userList is not None:
queryVals.append(tuple(userList))
if minTimestamp is not None:
queryVals.append(minTimestamp)
if maxTimestamp is not None:
queryVals.append(maxTimestamp)
if skipEmptyImages and userList is not None:
queryVals.append(tuple(userList))
# limit (TODO: make 128 a hyperparameter)
if limit is None:
limit = 128
else:
limit = min(int(limit), 128)
queryVals.append(limit)
if userList is not None:
queryVals.append(tuple(userList))
# query and parse results
with self.dbConnector.execute_cursor(queryStr,
tuple(queryVals)) as cursor:
try:
response = self._assemble_annotations(project, cursor,
hideGoldenQuestionInfo)
# self.dbConnector.conn.commit()
except Exception as e:
print(e)
# self.dbConnector.conn.rollback()
finally:
pass
# cursor.close()
# # mark images as requested
# self._set_images_requested(project, response)
return {'entries': response}
def get_timeRange(self,
project,
userList,
skipEmptyImages=False,
goldenQuestionsOnly=False):
'''
Returns two timestamps denoting the temporal limits within which
images have been viewed by the users provided in the userList.
Arguments:
- userList: string (single user name) or list of strings (multiple).
Can also be None; in this case all annotations will be
checked.
- skipEmptyImages: if True, only images that contain at least one
annotation will be considered.
- goldenQuestionsOnly: if True, only images flagged as golden questions
will be shown.
'''
# query string
queryStr = self.sqlBuilder.getTimeRangeQueryString(
project, userList, skipEmptyImages, goldenQuestionsOnly)
arguments = (None if userList is None else tuple(userList))
result = self.dbConnector.execute(queryStr, (arguments, ), numReturn=1)
if result is not None and len(result):
return {
'minTimestamp': result[0]['mintimestamp'],
'maxTimestamp': result[0]['maxtimestamp'],
}
else:
return {'error': 'no annotations made'}
def get_sampleData(self, project):
'''
Returns a sample image from the project, with annotations
(from one of the admins) and predictions.
If no image, no annotations, and/or no predictions are
available, a built-in default is returned instead.
'''
projImmutables = self.get_project_immutables(project)
queryStr = self.sqlBuilder.getSampleDataQueryString(
project, projImmutables['annotationType'],
projImmutables['predictionType'])
# query and parse results
response = None
with self.dbConnector.execute_cursor(queryStr, None) as cursor:
try:
response = self._assemble_annotations(project, cursor, True)
except:
pass
if response is None or not len(response):
# no valid data found for project; fall back to sample data
response = {
'00000000-0000-0000-0000-000000000000': {
'fileName':
'/static/interface/exampleData/sample_image.jpg',
'viewcount': 1,
'annotations': {
'00000000-0000-0000-0000-000000000000':
self._get_sample_metadata(
projImmutables['annotationType'])
},
'predictions': {
'00000000-0000-0000-0000-000000000000':
self._get_sample_metadata(
projImmutables['predictionType'])
},
'last_checked': None,
'isGoldenQuestion': True
}
}
return response
def submitAnnotations(self, project, username, submissions):
'''
Sends user-provided annotations to the database.
'''
projImmutables = self.get_project_immutables(project)
if projImmutables['demoMode']:
return 1
# assemble values
colnames = getattr(QueryStrings_annotation,
projImmutables['annotationType']).value
values_insert = []
values_update = []
meta = (None if not 'meta' in submissions else json.dumps(
submissions['meta']))
# for deletion: remove all annotations whose image ID matches but whose annotation ID is not among the submitted ones
ids = []
viewcountValues = []
for imageKey in submissions['entries']:
entry = submissions['entries'][imageKey]
try:
lastChecked = entry['timeCreated']
lastTimeRequired = entry['timeRequired']
if lastTimeRequired is None: lastTimeRequired = 0
except:
lastChecked = datetime.now(tz=pytz.utc)
lastTimeRequired = 0
try:
numInteractions = int(entry['numInteractions'])
except:
numInteractions = 0
if 'annotations' in entry and len(entry['annotations']):
for annotation in entry['annotations']:
# assemble annotation values
annotationTokens = self.annoParser.parseAnnotation(
annotation)
annoValues = []
for cname in colnames:
if cname == 'id':
if cname in annotationTokens:
# cast and only append id if the annotation is an existing one
annoValues.append(UUID(
annotationTokens[cname]))
ids.append(UUID(annotationTokens[cname]))
elif cname == 'image':
annoValues.append(UUID(imageKey))
elif cname == 'label' and annotationTokens[
cname] is not None:
annoValues.append(UUID(annotationTokens[cname]))
elif cname == 'timeCreated':
try:
annoValues.append(
dateutil.parser.parse(
annotationTokens[cname]))
except:
annoValues.append(datetime.now(tz=pytz.utc))
elif cname == 'timeRequired':
timeReq = annotationTokens[cname]
if timeReq is None: timeReq = 0
annoValues.append(timeReq)
elif cname == 'username':
annoValues.append(username)
elif cname in annotationTokens:
annoValues.append(annotationTokens[cname])
elif cname == 'unsure':
if 'unsure' in annotationTokens and annotationTokens[
'unsure'] is not None:
annoValues.append(annotationTokens[cname])
else:
annoValues.append(False)
elif cname == 'meta':
annoValues.append(meta)
else:
annoValues.append(None)
if 'id' in annotationTokens:
# existing annotation; update
values_update.append(tuple(annoValues))
else:
# new annotation
values_insert.append(tuple(annoValues))
viewcountValues.append(
(username, imageKey, 1, lastChecked, lastChecked,
lastTimeRequired, lastTimeRequired, numInteractions, meta))
# delete all annotations that are not in submitted batch
imageKeys = list(UUID(k) for k in submissions['entries'])
if len(imageKeys):
if len(ids):
queryStr = sql.SQL('''
DELETE FROM {id_anno} WHERE username = %s AND id IN (
SELECT idQuery.id FROM (
SELECT * FROM {id_anno} WHERE id NOT IN %s
) AS idQuery
JOIN (
SELECT * FROM {id_anno} WHERE image IN %s
) AS imageQuery ON idQuery.id = imageQuery.id);
''').format(id_anno=sql.Identifier(project, 'annotation'))
self.dbConnector.execute(queryStr, (
username,
tuple(ids),
tuple(imageKeys),
))
else:
# no annotations submitted; delete all annotations submitted before
queryStr = sql.SQL('''
DELETE FROM {id_anno} WHERE username = %s AND image IN %s;
''').format(id_anno=sql.Identifier(project, 'annotation'))
self.dbConnector.execute(queryStr, (
username,
tuple(imageKeys),
))
# insert new annotations
if len(values_insert):
queryStr = sql.SQL('''
INSERT INTO {id_anno} ({cols})
VALUES %s ;
''').format(
id_anno=sql.Identifier(project, 'annotation'),
cols=sql.SQL(', ').join([sql.SQL(c) for c in colnames[1:]
]) # skip 'id' column
)
self.dbConnector.insert(queryStr, values_insert)
# update existing annotations
if len(values_update):
updateCols = []
for col in colnames:
if col == 'label':
updateCols.append(sql.SQL('label = UUID(e.label)'))
elif col == 'timeRequired':
# we sum the required times together
updateCols.append(
sql.SQL(
'timeRequired = COALESCE(a.timeRequired,0) + COALESCE(e.timeRequired,0)'
))
else:
updateCols.append(
sql.SQL('{col} = e.{col}').format(col=sql.SQL(col)))
queryStr = sql.SQL('''
UPDATE {id_anno} AS a
SET {updateCols}
FROM (VALUES %s) AS e({colnames})
WHERE e.id = a.id
''').format(id_anno=sql.Identifier(project, 'annotation'),
updateCols=sql.SQL(', ').join(updateCols),
colnames=sql.SQL(', ').join(
[sql.SQL(c) for c in colnames]))
self.dbConnector.insert(queryStr, values_update)
# viewcount table
queryStr = sql.SQL('''
INSERT INTO {id_iu} (username, image, viewcount, first_checked, last_checked, last_time_required, total_time_required, num_interactions, meta)
VALUES %s
ON CONFLICT (username, image) DO UPDATE SET viewcount = image_user.viewcount + 1,
last_checked = EXCLUDED.last_checked,
last_time_required = EXCLUDED.last_time_required,
total_time_required = EXCLUDED.total_time_required + image_user.total_time_required,
num_interactions = EXCLUDED.num_interactions + image_user.num_interactions,
meta = EXCLUDED.meta;
''').format(id_iu=sql.Identifier(project, 'image_user'))
self.dbConnector.insert(queryStr, viewcountValues)
return 0
def setGoldenQuestions(self, project, submissions):
'''
Receives an iterable of tuples (uuid, bool) and updates the
property "isGoldenQuestion" of the images accordingly.
'''
projImmutables = self.get_project_immutables(project)
if projImmutables['demoMode']:
return 1
queryStr = sql.SQL('''
UPDATE {id_img} AS img SET isGoldenQuestion = c.isGoldenQuestion
FROM (VALUES %s)
AS c (id, isGoldenQuestion)
WHERE c.id = img.id;
''').format(id_img=sql.Identifier(project, 'image'))
self.dbConnector.insert(queryStr, submissions)
return 0
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
class ModelMarketplaceMiddleware:
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.labelUImiddleware = DBMiddleware(config)
self._init_available_ai_models()
def _init_available_ai_models(self):
'''
Checks the locally installed model implementations
and retains a list of those that support sharing
(i.e., the addition of new label classes).
'''
self.availableModels = set()
for key in PREDICTION_MODELS:
if 'canAddLabelclasses' in PREDICTION_MODELS[key] and \
PREDICTION_MODELS[key]['canAddLabelclasses'] is True:
self.availableModels.add(key)
def getModelsMarketplace(self, project, username):
'''
Returns a dict of model state meta data,
filtered by the project settings (model library;
annotation type, prediction type).
'''
# get project meta data (immutables, model library)
projectMeta = self.dbConnector.execute(
'''
SELECT annotationType, predictionType, ai_model_library
FROM aide_admin.project
WHERE shortname = %s;
''', (project, ), 1)
if projectMeta is None or not len(projectMeta):
raise Exception(
f'Project {project} could not be found in database.')
projectMeta = projectMeta[0]
annotationType = projectMeta['annotationtype']
predictionType = projectMeta['predictiontype']
# get matching model states
result = self.dbConnector.execute(
'''
SELECT id, name, description, labelclasses, model_library,
annotationType, predictionType, EXTRACT(epoch FROM timeCreated) AS time_created, alcriterion_library,
public, anonymous, selectCount,
is_owner, shared, tags,
CASE WHEN NOT is_owner AND anonymous THEN NULL ELSE author END AS author,
CASE WHEN NOT is_owner AND anonymous THEN NULL ELSE origin_project END AS origin_project,
CASE WHEN NOT is_owner AND anonymous THEN NULL ELSE origin_uuid END AS origin_uuid
FROM (
SELECT *,
CASE WHEN author = %s AND origin_project = %s THEN TRUE ELSE FALSE END AS is_owner
FROM aide_admin.modelMarketplace
WHERE annotationType = %s AND
predictionType = %s
AND (
(public = TRUE AND shared = TRUE) OR
origin_project = %s
)
) AS mm
LEFT OUTER JOIN (
SELECT name AS projectName, shortname
FROM aide_admin.project
) AS pn
ON mm.origin_project = pn.shortname;
''', (username, project, annotationType, predictionType, project),
'all')
if result is not None and len(result):
matchingStates = {}
for r in result:
stateID = str(r['id'])
values = {}
for key in r.keys():
if isinstance(r[key], UUID):
values[key] = str(r[key])
else:
values[key] = r[key]
matchingStates[stateID] = values
else:
matchingStates = {}
return matchingStates
def importModel(self, project, username, modelID):
if not isinstance(modelID, UUID):
modelID = UUID(modelID)
# get model meta data
meta = self.dbConnector.execute(
'''
SELECT id, name, description, labelclasses, model_library,
annotationType, predictionType, timeCreated, alcriterion_library,
public, anonymous, selectCount,
CASE WHEN anonymous THEN NULL ELSE author END AS author,
CASE WHEN anonymous THEN NULL ELSE origin_project END AS origin_project,
CASE WHEN anonymous THEN NULL ELSE origin_uuid END AS origin_uuid
FROM aide_admin.modelMarketplace
WHERE id = %s;
''', (modelID, ), 1)
if meta is None or not len(meta):
return {
'status':
2,
'message':
f'Model state with id "{str(modelID)}" could not be found in the model marketplace.'
}
meta = meta[0]
# check if model type is registered with AIDE
modelLib = meta['model_library']
if modelLib not in self.availableModels:
return {
'status':
3,
'message':
f'Model type with identifier "{modelLib}" does not support sharing across project, or else is not registered with this installation of AIDE.'
}
# check if model hasn't already been imported to current project
modelExists = self.dbConnector.execute(
sql.SQL('''
SELECT id
FROM {id_cnnstate}
WHERE marketplace_origin_id = %s;
''').format(id_cnnstate=sql.Identifier(project, 'cnnstate')),
(modelID), 1)
if modelExists is not None and len(modelExists):
# model already exists in project; update timestamp to make it current (TODO: find a better solution)
self.dbConnector.execute(
sql.SQL('''
UPDATE {id_cnnstate}
SET timeCreated = NOW()
WHERE marketplace_origin_id = %s;
''').format(id_cnnstate=sql.Identifier(project, 'cnnstate')),
(modelID))
return {
'status':
0,
'message':
'Model had already been imported to project and was elevated to be the most current.'
}
# check if model is suitable for current project
immutables = self.labelUImiddleware.get_project_immutables(project)
errors = ''
if immutables['annotationType'] != meta['annotationtype']:
meta_at = meta['annotationtype']
proj_at = immutables['annotationType']
errors = f'Annotation type of model ({meta_at}) is not compatible with project\'s annotation type ({proj_at}).'
if immutables['predictionType'] != meta['predictiontype']:
meta_pt = meta['predictiontype']
proj_pt = immutables['predictionType']
errors += f'\nPrediction type of model ({meta_pt}) is not compatible with project\'s prediction type ({proj_pt}).'
if len(errors):
return {'status': 4, 'message': errors}
# set project's selected model
self.dbConnector.execute(
'''
UPDATE aide_admin.project
SET ai_model_library = %s
WHERE shortname = %s;
''', (meta['model_library'], project))
# finally, increase selection counter and import model state
#TODO: - retain existing alCriterion library
insertedModelID = self.dbConnector.execute(
sql.SQL('''
UPDATE aide_admin.modelMarketplace
SET selectCount = selectCount + 1
WHERE id = %s;
INSERT INTO {id_cnnstate} (marketplace_origin_id, stateDict, timeCreated, partial, model_library, alCriterion_library)
SELECT id, stateDict, timeCreated, FALSE, model_library, alCriterion_library
FROM aide_admin.modelMarketplace
WHERE id = %s
RETURNING id;
''').format(id_cnnstate=sql.Identifier(project, 'cnnstate')),
(modelID, modelID), 1)
return {'status': 0, 'id': str(insertedModelID)}
def shareModel(self, project, username, modelID, modelName,
modelDescription, tags, public, anonymous):
#TODO: export as Celery task
if not isinstance(modelID, UUID):
modelID = UUID(modelID)
if tags is None:
tags = ''
elif isinstance(tags, list) or isinstance(tags, tuple):
tags = ';;'.join(tags)
# check if model class supports sharing
isShareable = self.dbConnector.execute(
'''
SELECT ai_model_library
FROM aide_admin.project
WHERE shortname = %s;
''', (project, ), 1)
if isShareable is None or not len(isShareable):
return {
'status': 1,
'message': f'Project {project} could not be found in database.'
}
modelLib = isShareable[0]['ai_model_library']
if modelLib not in self.availableModels:
return {
'status':
2,
'message':
f'The model with id "{modelLib}" does not support sharing, or else is not installed in this instance of AIDE.'
}
# check if model hasn't already been shared
isShared = self.dbConnector.execute(
'''
SELECT id, author, shared
FROM aide_admin.modelMarketplace
WHERE origin_project = %s AND origin_uuid = %s;
''', (project, modelID), 'all')
if isShared is not None and len(isShared):
if not isShared[0]['shared']:
# model had been shared in the past but then hidden; unhide
self.dbConnector.execute(
'''
UPDATE aide_admin.modelMarketplace
SET shared = True
WHERE origin_project = %s AND origin_uuid = %s;
''', (project, modelID))
# update shared model meta data
self.dbConnector.execute(
'''
UPDATE aide_admin.modelMarketplace
SET name = %s,
description = %s,
public = %s,
anonymous = %s,
tags = %s
WHERE id = %s AND author = %s;
''', (modelName, modelDescription, public, anonymous, tags,
isShared[0]['id'], username), None)
return {'status': 0}
# check if model hasn't been imported from the marketplace
isImported = self.dbConnector.execute(
sql.SQL('''
SELECT marketplace_origin_id
FROM {id_cnnstate}
WHERE id = %s;
''').format(id_cnnstate=sql.Identifier(project, 'cnnstate')),
(modelID, ), 1)
if isImported is not None and len(isImported):
marketplaceID = isImported[0]['marketplace_origin_id']
if marketplaceID is not None:
return {
'status':
4,
'message':
f'The selected model is already shared through the marketplace (id "{str(marketplaceID)}").'
}
# get project immutables
immutables = self.labelUImiddleware.get_project_immutables(project)
# get label class info
labelclasses = json.dumps(
self.labelUImiddleware.getClassDefinitions(project, False))
# check if name is unique (TODO: required?)
nameTaken = self.dbConnector.execute(
'''
SELECT COUNT(*) AS cnt
FROM aide_admin.modelMarketplace
WHERE name = %s;
''', (modelName, ), 'all')
if nameTaken is not None and len(nameTaken) and nameTaken[0]['cnt']:
return {
'status':
5,
'message':
f'A model state with name "{modelName}" already exists in the Model Marketplace.'
}
# share model state
sharedModelID = self.dbConnector.execute(
sql.SQL('''
INSERT INTO aide_admin.modelMarketplace
(name, description, tags, labelclasses, author, statedict,
model_library, alCriterion_library,
annotationType, predictionType,
origin_project, origin_uuid, public, anonymous)
SELECT %s, %s, %s, %s, %s, statedict,
model_library, alCriterion_library,
%s, %s,
%s, id, %s, %s
FROM {id_cnnstate} AS cnnS
WHERE id = %s
RETURNING id;
''').format(id_cnnstate=sql.Identifier(project, 'cnnstate')),
(modelName, modelDescription, tags, labelclasses, username,
immutables['annotationType'], immutables['predictionType'],
project, public, anonymous, modelID))
return {'status': 0, 'shared_model_id': str(sharedModelID)}
def reshareModel(self, project, username, modelID):
'''
Unlike "shareModel", this checks for a model that had already been
shared in the past, but then hidden from the marketplace, and simply
turns the "shared" attribute back on, if the model could be found.
'''
# get origin UUID of model and delegate to "shareModel" function
modelID = self.dbConnector.execute(
'''
SELECT origin_uuid FROM aide_admin.modelMarketplace
WHERE origin_project = %s
AND author = %s
AND id = %s;
''', (project, username, UUID(modelID)), 1)
if modelID is None or not len(modelID):
return {
'status':
2,
'message':
f'Model with ID "{str(modelID)}" could not be found on the Model Marketplace.'
}
modelID = modelID[0]['origin_uuid']
return self.shareModel(project, username, modelID, None, None, None,
None, None)
def unshareModel(self, project, username, modelID):
'''
Sets the "shared" flag to False for a given model state,
if the provided username is the owner of it.
'''
if not isinstance(modelID, UUID):
modelID = UUID(modelID)
# check if user is authorized
isAuthorized = self.dbConnector.execute(
'''
SELECT shared FROM aide_admin.modelMarketplace
WHERE author = %s AND id = %s;
''', (username, modelID), 1)
if isAuthorized is None or not len(isAuthorized):
# model does not exist or else user has no modification rights
return {
'status':
2,
'message':
f'Model with id "{str(modelID)}"" does not exist or else user {username} does not have modification rights to it.'
}
# unshare
self.dbConnector.execute(
'''
UPDATE aide_admin.modelMarketplace
SET shared = FALSE
WHERE author = %s AND id = %s;
''', (username, modelID))
return {'status': 0}
class ProjectStatisticsMiddleware:
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
def getProjectStatistics(self, project):
'''
Returns statistics, such as number of images (seen),
number of annotations, etc., on a global and per-user,
but class-agnostic basis.
'''
queryStr = sql.SQL('''
SELECT NULL AS username, COUNT(*) AS num_img, NULL::bigint AS num_anno FROM {id_img}
UNION ALL
SELECT NULL AS username, COUNT(DISTINCT(image)) AS num_img, NULL AS num_anno FROM {id_iu}
UNION ALL
SELECT NULL AS username, COUNT(DISTINCT(gq.id)) AS num_img, NULL AS num_anno FROM (
SELECT id FROM {id_img} WHERE isGoldenQuestion = TRUE
) AS gq
UNION ALL
SELECT NULL AS username, NULL AS num_img, COUNT(DISTINCT(image)) AS num_anno FROM {id_anno}
UNION ALL
SELECT NULL AS username, NULL AS num_img, COUNT(*) AS num_anno FROM {id_anno}
UNION ALL
SELECT username, iu_cnt AS num_img, anno_cnt AS num_anno FROM (
SELECT u.username, iu_cnt, anno_cnt
FROM (
SELECT DISTINCT(username) FROM (
SELECT username FROM {id_auth}
WHERE project = %s
UNION ALL
SELECT username FROM {id_iu}
UNION ALL
SELECT username FROM {id_anno}
) AS uQuery
) AS u
LEFT OUTER JOIN (
SELECT username, COUNT(*) AS iu_cnt
FROM {id_iu}
GROUP BY username
) AS iu
ON u.username = iu.username
LEFT OUTER JOIN (
SELECT username, COUNT(*) AS anno_cnt
FROM {id_anno}
GROUP BY username
) AS anno
ON u.username = anno.username
ORDER BY u.username
) AS q;
''').format(id_img=sql.Identifier(project, 'image'),
id_iu=sql.Identifier(project, 'image_user'),
id_anno=sql.Identifier(project, 'annotation'),
id_auth=sql.Identifier('aide_admin', 'authentication'))
result = self.dbConnector.execute(queryStr, (project, ), 'all')
response = {
'num_images': result[0]['num_img'],
'num_viewed': result[1]['num_img'],
'num_goldenQuestions': result[2]['num_img'],
'num_annotated': result[3]['num_anno'],
'num_annotations': result[4]['num_anno']
}
if len(result) > 5:
response['user_stats'] = {}
for i in range(5, len(result)):
uStats = {
'num_viewed': result[i]['num_img'],
'num_annotations': result[i]['num_anno']
}
response['user_stats'][result[i]['username']] = uStats
return response
def getLabelclassStatistics(self, project):
'''
Returns annotation statistics on a per-label class
basis.
TODO: does not work for segmentationMasks (no label fields)
'''
queryStr = sql.SQL('''
SELECT lc.name, COALESCE(num_anno, 0) AS num_anno, COALESCE(num_pred, 0) AS num_pred
FROM {id_lc} AS lc
FULL OUTER JOIN (
SELECT label, COUNT(*) AS num_anno
FROM {id_anno} AS anno
GROUP BY label
) AS annoCnt
ON lc.id = annoCnt.label
FULL OUTER JOIN (
SELECT label, COUNT(*) AS num_pred
FROM {id_pred} AS pred
GROUP BY label
) AS predCnt
ON lc.id = predCnt.label
''').format(id_lc=sql.Identifier(project, 'labelclass'),
id_anno=sql.Identifier(project, 'annotation'),
id_pred=sql.Identifier(project, 'prediction'))
result = self.dbConnector.execute(queryStr, None, 'all')
response = {}
if result is not None and len(result):
for i in range(len(result)):
nextResult = result[i]
response[nextResult['name']] = {
'num_anno': nextResult['num_anno'],
'num_pred': nextResult['num_pred']
}
return response
@staticmethod
def _calc_geometric_stats(tp, fp, fn):
tp, fp, fn = float(tp), float(fp), float(fn)
try:
precision = tp / (tp + fp)
except:
precision = 0.0
try:
recall = tp / (tp + fn)
except:
recall = 0.0
try:
f1 = 2 * precision * recall / (precision + recall)
except:
f1 = 0.0
return precision, recall, f1
def getPerformanceStatistics(self,
project,
entities_eval,
entity_target,
entityType='user',
threshold=0.5,
goldenQuestionsOnly=True):
'''
Compares the accuracy of a list of users or model states with a target
user.
The following measures of accuracy are reported, depending on the
annotation type:
- image labels: overall accuracy
- points:
RMSE (distance to closest point with the same label; in pixels)
overall accuracy (labels)
- bounding boxes:
IoU (max. with any target bounding box, regardless of label)
overall accuracy (labels)
- segmentation masks:
TODO
Value 'threshold' determines the geometric requirement for an annotation to be
counted as correct (or incorrect) as follows:
- points: maximum euclidean distance in pixels to closest target
- bounding boxes: minimum IoU with best matching target
If 'goldenQuestionsOnly' is True, only images with flag 'isGoldenQuestion' = True
will be considered for evaluation.
'''
entityType = entityType.lower()
# get annotation type for project
annoType = self.dbConnector.execute(
'''SELECT annotationType
FROM aide_admin.project WHERE shortname = %s;''', (project, ), 1)
annoType = annoType[0]['annotationtype']
# for segmentation masks: get label classes and their ordinals #TODO: implement per-class statistics for all types
labelClasses = {}
lcDef = self.dbConnector.execute(
sql.SQL('''
SELECT id, idx, color FROM {id_lc};
''').format(id_lc=sql.Identifier(project, 'labelclass')), None, 'all')
if lcDef is not None:
for l in lcDef:
labelClasses[str(l['id'])] = (l['idx'], l['color'])
else:
# no label classes defined
return {}
# compose args list and complete query
queryArgs = [entity_target, tuple(entities_eval)]
if annoType == 'points' or annoType == 'boundingBoxes':
queryArgs.append(threshold)
if annoType == 'points':
queryArgs.append(threshold)
if goldenQuestionsOnly:
sql_goldenQuestion = sql.SQL('''JOIN (
SELECT id
FROM {id_img}
WHERE isGoldenQuestion = true
) AS qi
ON qi.id = q2.image''').format(
id_img=sql.Identifier(project, 'image'))
else:
sql_goldenQuestion = sql.SQL('')
# result tokens
tokens = {}
tokens_normalize = []
if annoType == 'labels':
tokens = {
'num_matches': 0,
'correct': 0,
'incorrect': 0,
'overall_accuracy': 0.0
}
tokens_normalize = ['overall_accuracy']
elif annoType == 'points':
tokens = {
'num_pred': 0,
'num_target': 0,
'tp': 0,
'fp': 0,
'fn': 0,
'avg_dist': 0.0
}
tokens_normalize = ['avg_dist']
elif annoType == 'boundingBoxes':
tokens = {
'num_pred': 0,
'num_target': 0,
'tp': 0,
'fp': 0,
'fn': 0,
'avg_iou': 0.0
}
tokens_normalize = ['avg_iou']
elif annoType == 'segmentationMasks':
tokens = {
'num_matches': 0,
'overall_accuracy': 0.0,
'per_class': {}
}
for clID in labelClasses.keys():
tokens['per_class'][clID] = {
'num_matches': 0,
'prec': 0.0,
'rec': 0.0,
'f1': 0.0
}
tokens_normalize = []
if entityType == 'user':
queryStr = getattr(StatisticalFormulas_user, annoType).value
queryStr = sql.SQL(queryStr).format(
id_anno=sql.Identifier(project, 'annotation'),
id_iu=sql.Identifier(project, 'image_user'),
sql_goldenQuestion=sql_goldenQuestion)
else:
queryStr = getattr(StatisticalFormulas_model, annoType).value
queryStr = sql.SQL(queryStr).format(
id_anno=sql.Identifier(project, 'annotation'),
id_iu=sql.Identifier(project, 'image_user'),
id_pred=sql.Identifier(project, 'prediction'),
sql_goldenQuestion=sql_goldenQuestion)
#TODO: update points query (according to bboxes); re-write stats parsing below
# get stats
response = {}
with self.dbConnector.execute_cursor(queryStr,
tuple(queryArgs)) as cursor:
while True:
b = cursor.fetchone()
if b is None:
break
if entityType == 'user':
entity = b['username']
else:
entity = str(b['cnnstate'])
if not entity in response:
response[entity] = tokens.copy()
if annoType in ('points', 'boundingBoxes'):
response[entity]['num_matches'] = 1
if b['num_target'] > 0:
response[entity]['num_matches'] += 1
if annoType == 'segmentationMasks':
# decode segmentation masks
try:
mask_target = np.array(
base64ToImage(b['q1segmask'], b['q1width'],
b['q1height']))
mask_source = np.array(
base64ToImage(b['q2segmask'], b['q2width'],
b['q2height']))
if mask_target.shape == mask_source.shape and np.any(
mask_target) and np.any(mask_source):
# calculate OA
intersection = (mask_target > 0) * (mask_source >
0)
if np.any(intersection):
oa = np.mean(mask_target[intersection] ==
mask_source[intersection])
response[entity]['overall_accuracy'] += oa
response[entity]['num_matches'] += 1
# calculate per-class precision and recall values
for clID in labelClasses.keys():
idx = labelClasses[clID][0]
tp = np.sum((mask_target == idx) *
(mask_source == idx))
fp = np.sum((mask_target != idx) *
(mask_source == idx))
fn = np.sum((mask_target == idx) *
(mask_source != idx))
if (tp + fp + fn) > 0:
prec, rec, f1 = self._calc_geometric_stats(
tp, fp, fn)
response[entity]['per_class'][clID][
'num_matches'] += 1
response[entity]['per_class'][clID][
'prec'] += prec
response[entity]['per_class'][clID][
'rec'] += rec
response[entity]['per_class'][clID][
'f1'] += f1
except Exception as e:
print(
f'TODO: error in segmentation mask statistics calculation ("{str(e)}").'
)
else:
for key in tokens.keys():
if key == 'correct' or key == 'incorrect':
# classification
correct = b['label_correct']
# ignore None
if correct is True:
response[entity]['correct'] += 1
response[entity]['num_matches'] += 1
elif correct is False:
response[entity]['incorrect'] += 1
response[entity]['num_matches'] += 1
elif key in b and b[key] is not None:
response[entity][key] += b[key]
for entity in response.keys():
for t in tokens_normalize:
if t in response[entity]:
if t == 'overall_accuracy':
response[entity][t] = float(response[entity]['correct']) / \
float(response[entity]['correct'] + response[entity]['incorrect'])
elif annoType in ('points', 'boundingBoxes'):
response[entity][t] /= response[entity]['num_matches']
if annoType == 'points' or annoType == 'boundingBoxes':
prec, rec, f1 = self._calc_geometric_stats(
response[entity]['tp'], response[entity]['fp'],
response[entity]['fn'])
response[entity]['prec'] = prec
response[entity]['rec'] = rec
response[entity]['f1'] = f1
elif annoType == 'segmentationMasks':
# normalize OA
response[entity]['overall_accuracy'] /= response[entity][
'num_matches']
# normalize all label class values as well
for lcID in labelClasses.keys():
numMatches = response[entity]['per_class'][lcID][
'num_matches']
if numMatches > 0:
response[entity]['per_class'][lcID][
'prec'] /= numMatches
response[entity]['per_class'][lcID][
'rec'] /= numMatches
response[entity]['per_class'][lcID]['f1'] /= numMatches
return {'label_classes': labelClasses, 'per_entity': response}
def getUserAnnotationSpeeds(self,
project,
users,
goldenQuestionsOnly=False):
'''
Returns, for each username in "users" list,
the mean, median and lower and upper quartile
(25% and 75%) of the time required in a given project.
'''
# prepare output
response = {}
for u in users:
response[u] = {
'avg': float('nan'),
'median': float('nan'),
'perc_25': float('nan'),
'perc_75': float('nan')
}
if goldenQuestionsOnly:
gqStr = sql.SQL('''
JOIN {id_img} AS img
ON anno.image = img.id
WHERE img.isGoldenQuestion = true
''').format(id_img=sql.Identifier(project, 'image'))
else:
gqStr = sql.SQL('')
queryStr = sql.SQL('''
SELECT username, avg(timeRequired) AS avg,
percentile_cont(0.50) WITHIN GROUP (ORDER BY timeRequired ASC) AS median,
percentile_cont(0.25) WITHIN GROUP (ORDER BY timeRequired ASC) AS perc_25,
percentile_cont(0.75) WITHIN GROUP (ORDER BY timeRequired ASC) AS perc_75
FROM (
SELECT username, timeRequired
FROM {id_anno} AS anno
{gqStr}
) AS q
WHERE username IN %s
GROUP BY username
''').format(id_anno=sql.Identifier(project, 'annotation'), gqStr=gqStr)
result = self.dbConnector.execute(queryStr, (tuple(users), ), 'all')
if result is not None:
for r in result:
user = r['username']
response[user] = {
'avg': float(r['avg']),
'median': float(r['median']),
'perc_25': float(r['perc_25']),
'perc_75': float(r['perc_75']),
}
return response
def getUserFinished(self, project, username):
'''
Returns True if the user has viewed all images in the project,
and False otherwise.
We deliberately do not reveal more information to the general
user, in order to e.g. sustain the golden question limitation
system.
'''
queryStr = sql.SQL('''
SELECT COUNT(*) AS cnt FROM {id_iu}
WHERE viewcount > 0 AND username = %s
UNION ALL
SELECT COUNT(*) AS cnt FROM {id_img};
''').format(id_img=sql.Identifier(project, 'image'),
id_iu=sql.Identifier(project, 'image_user'))
result = self.dbConnector.execute(queryStr, (username, ), 2)
return result[0]['cnt'] >= result[1]['cnt']
def getTimeActivity(self,
project,
type='images',
numDaysMax=31,
perUser=False):
'''
Returns a histogram of the number of images viewed (if type = 'images')
or annotations made (if type = 'annotations') over the last numDaysMax.
If perUser is True, statistics are returned on a user basis.
'''
if type == 'images':
id_table = sql.Identifier(project, 'image_user')
time_field = sql.SQL('last_checked')
else:
id_table = sql.Identifier(project, 'annotation')
time_field = sql.SQL('timeCreated')
if perUser:
userSpec = sql.SQL(', username')
else:
userSpec = sql.SQL('')
queryStr = sql.SQL('''
SELECT to_char({time_field}, 'YYYY-Mon-dd') AS month_day, MIN({time_field}) AS date_of_day, COUNT(*) AS cnt {user_spec}
FROM {id_table}
WHERE {time_field} IS NOT NULL
GROUP BY month_day {user_spec}
ORDER BY date_of_day ASC
LIMIT %s
''').format(time_field=time_field,
id_table=id_table,
user_spec=userSpec)
result = self.dbConnector.execute(queryStr, (numDaysMax, ), 'all')
#TODO: homogenize series and add missing days
if perUser:
response = {}
else:
response = {'counts': [], 'timestamps': [], 'labels': []}
for row in result:
if perUser:
if row['username'] not in response:
response[row['username']] = {
'counts': [],
'timestamps': [],
'labels': []
}
response[row['username']]['counts'].append(row['cnt'])
response[row['username']]['timestamps'].append(
row['date_of_day'].timestamp())
response[row['username']]['labels'].append(row['month_day'])
else:
response['counts'].append(row['cnt'])
response['timestamps'].append(row['date_of_day'].timestamp())
response['labels'].append(row['month_day'])
return response
class AIWorker():
def __init__(self, config, passiveMode=False):
self.config = config
self.dbConnector = Database(config)
self.passiveMode = passiveMode
self._init_fileserver()
def _init_fileserver(self):
'''
The AIWorker has a special routine to detect whether the instance it is running on
also hosts the file server. If it does, data are loaded directly from disk to avoid
going through the loopback network.
'''
self.fileServer = fileserver.FileServer(self.config)
def _init_model_instance(self, project, modelLibrary, modelSettings):
# try to parse model settings
if modelSettings is not None and len(modelSettings):
try:
modelSettings = json.loads(modelSettings)
except Exception as err:
print(
'WARNING: could not read model options. Error message: {message}.'
.format(message=str(err)))
modelSettings = None
else:
modelSettings = None
# import class object
modelClass = get_class_executable(modelLibrary)
# verify functions and arguments
requiredFunctions = {
'__init__':
['project', 'config', 'dbConnector', 'fileServer', 'options'],
'train': ['stateDict', 'data', 'updateStateFun'],
'average_model_states': ['stateDicts', 'updateStateFun'],
'inference': ['stateDict', 'data', 'updateStateFun']
}
functionNames = [
func for func in dir(modelClass)
if callable(getattr(modelClass, func))
]
for key in requiredFunctions:
if not key in functionNames:
raise Exception(
'Class {} is missing required function {}.'.format(
modelLibrary, key))
# check function arguments bidirectionally
funArgs = inspect.getargspec(getattr(modelClass, key))
for arg in requiredFunctions[key]:
if not arg in funArgs.args:
raise Exception(
'Method {} of class {} is missing required argument {}.'
.format(modelLibrary, key, arg))
for arg in funArgs.args:
if arg != 'self' and not arg in requiredFunctions[key]:
raise Exception(
'Unsupported argument {} of method {} in class {}.'.
format(arg, key, modelLibrary))
# create AI model instance
return modelClass(
project=project,
config=self.config,
dbConnector=self.dbConnector,
fileServer=self.fileServer.get_secure_instance(project),
options=modelSettings)
def _init_alCriterion_instance(self, project, alLibrary, alSettings):
'''
Creates the Active Learning (AL) criterion provider instance.
'''
# try to parse settings
if alSettings is not None and len(alSettings):
try:
alSettings = json.loads(alSettings)
except Exception as err:
print(
'WARNING: could not read AL criterion options. Error message: {message}.'
.format(message=str(err)))
alSettings = None
else:
alSettings = None
# import class object
modelClass = get_class_executable(alLibrary)
# verify functions and arguments
requiredFunctions = {
'__init__':
['project', 'config', 'dbConnector', 'fileServer', 'options'],
'rank': ['data', 'updateStateFun']
}
functionNames = [
func for func in dir(modelClass)
if callable(getattr(modelClass, func))
]
for key in requiredFunctions:
if not key in functionNames:
raise Exception(
'Class {} is missing required function {}.'.format(
alLibrary, key))
# check function arguments bidirectionally
funArgs = inspect.getargspec(getattr(modelClass, key))
for arg in requiredFunctions[key]:
if not arg in funArgs.args:
raise Exception(
'Method {} of class {} is missing required argument {}.'
.format(alLibrary, key, arg))
for arg in funArgs.args:
if arg != 'self' and not arg in requiredFunctions[key]:
raise Exception(
'Unsupported argument {} of method {} in class {}.'.
format(arg, key, alLibrary))
# create AI model instance
return modelClass(
project=project,
config=self.config,
dbConnector=self.dbConnector,
fileServer=self.fileServer.get_secure_instance(project),
options=alSettings)
def _get_model_instance(self, project):
'''
Returns the class instance of the model specified in the given
project.
TODO: cache models?
'''
# get model settings for project
queryStr = '''
SELECT ai_model_library, ai_model_settings FROM aide_admin.project
WHERE shortname = %s;
'''
result = self.dbConnector.execute(queryStr, (project, ), 1)
modelLibrary = result[0]['ai_model_library']
modelSettings = result[0]['ai_model_settings']
# create new model instance
modelInstance = self._init_model_instance(project, modelLibrary,
modelSettings)
return modelInstance
def _get_alCriterion_instance(self, project):
'''
Returns the class instance of the Active Learning model
specified in the project.
TODO: cache models?
'''
# get model settings for project
queryStr = '''
SELECT ai_alCriterion_library, ai_alCriterion_settings FROM aide_admin.project
WHERE shortname = %s;
'''
result = self.dbConnector.execute(queryStr, (project, ), 1)
modelLibrary = result[0]['ai_alcriterion_library']
modelSettings = result[0]['ai_alcriterion_settings']
# create new model instance
modelInstance = self._init_alCriterion_instance(
project, modelLibrary, modelSettings)
return modelInstance
def aide_internal_notify(self, message):
'''
Used for AIDE administrative communication between AIController
and AIWorker(s), e.g. for setting up queues.
'''
if self.passiveMode:
return
# not required (yet)
def call_train(self, data, epoch, numEpochs, project, subset):
# get project-specific model
modelInstance = self._get_model_instance(project)
return functional._call_train(project, data, epoch, numEpochs, subset,
getattr(modelInstance, 'train'),
self.dbConnector, self.fileServer)
def call_average_model_states(self, epoch, numEpochs, project):
# get project-specific model
modelInstance = self._get_model_instance(project)
return functional._call_average_model_states(
project, epoch, numEpochs,
getattr(modelInstance, 'average_model_states'), self.dbConnector,
self.fileServer)
def call_inference(self, imageIDs, epoch, numEpochs, project):
# get project-specific model and AL criterion
modelInstance = self._get_model_instance(project)
alCriterionInstance = self._get_alCriterion_instance(project)
return functional._call_inference(
project, imageIDs, epoch, numEpochs,
getattr(modelInstance, 'inference'),
getattr(alCriterionInstance, 'rank'), self.dbConnector,
self.fileServer,
self.config.getProperty('AIWorker',
'inference_batch_size_limit',
type=int,
fallback=-1))
def verify_model_state(self, project, modelLibrary, stateDict,
modelOptions):
'''
Launches a dummy training-averaging-inference chain
on a received model state and returns True if the chain
could be executed without any errors (else False). Does
not store anything in the database.
Inputs:
- project: str, project shortname (used to retrieve
sample data)
- modelLibrary: str, identifier of the AI model
- stateDict: bytes object, AI model state
- modelOptions: str, model settings to be tested
(optional)
Returns a dict with the following entries:
- valid: bool, True if the provided state dict and
(optionally) model options are valid (i.e.,
can be used to perform training, averaging,
and inference), or False otherwise.
- messages: str, text describing the error(s) encounte-
red if there are any.
'''
#TODO
raise NotImplementedError('Not yet implemented.')
class DBMiddleware():
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self._fetchProjectSettings()
self.sqlBuilder = SQLStringBuilder(config)
self.annoParser = AnnotationParser(config)
def _fetchProjectSettings(self):
# AI controller URI
aiControllerURI = self.config.getProperty('Server', 'aiController_uri')
if aiControllerURI is None or aiControllerURI.strip() == '':
# no AI backend configured
aiControllerURI = None
# LabelUI drawing styles
with open(
self.config.getProperty(
'LabelUI',
'styles_file',
type=str,
fallback='modules/LabelUI/static/json/styles.json'),
'r') as f:
styles = json.load(f)
# Image backdrops for index screen
with open(
self.config.getProperty(
'Project',
'backdrops_file',
type=str,
fallback='modules/LabelUI/static/json/backdrops.json'),
'r') as f:
backdrops = json.load(f)
# Welcome message for UI tutorial
with open(
self.config.getProperty(
'Project',
'welcome_message_file',
type=str,
fallback=
'modules/LabelUI/static/templates/welcome_message.html'),
'r') as f:
welcomeMessage = f.readlines()
self.projectSettings = {
'projectName':
self.config.getProperty('Project', 'projectName'),
'projectDescription':
self.config.getProperty('Project', 'projectDescription'),
'indexURI':
self.config.getProperty('Server',
'index_uri',
type=str,
fallback='/'),
'dataServerURI':
self.config.getProperty('Server', 'dataServer_uri'),
'aiControllerURI':
aiControllerURI,
'dataType':
self.config.getProperty('Project', 'dataType', fallback='images'),
'classes':
self.getClassDefinitions(),
'enableEmptyClass':
self.config.getProperty('Project',
'enableEmptyClass',
fallback='no'),
'annotationType':
self.config.getProperty('Project', 'annotationType'),
'predictionType':
self.config.getProperty('Project', 'predictionType'),
'showPredictions':
self.config.getProperty('LabelUI',
'showPredictions',
fallback='yes'),
'showPredictions_minConf':
self.config.getProperty('LabelUI',
'showPredictions_minConf',
type=float,
fallback=0.5),
'carryOverPredictions':
self.config.getProperty('LabelUI',
'carryOverPredictions',
fallback='no'),
'carryOverRule':
self.config.getProperty('LabelUI',
'carryOverRule',
fallback='maxConfidence'),
'carryOverPredictions_minConf':
self.config.getProperty('LabelUI',
'carryOverPredictions_minConf',
type=float,
fallback=0.75),
'defaultBoxSize_w':
self.config.getProperty('LabelUI',
'defaultBoxSize_w',
type=int,
fallback=10),
'defaultBoxSize_h':
self.config.getProperty('LabelUI',
'defaultBoxSize_h',
type=int,
fallback=10),
'minBoxSize_w':
self.config.getProperty('Project',
'box_minWidth',
type=int,
fallback=1),
'minBoxSize_h':
self.config.getProperty('Project',
'box_minHeight',
type=int,
fallback=1),
'numImagesPerBatch':
self.config.getProperty('LabelUI',
'numImagesPerBatch',
type=int,
fallback=1),
'minImageWidth':
self.config.getProperty('LabelUI',
'minImageWidth',
type=int,
fallback=300),
'numImageColumns_max':
self.config.getProperty('LabelUI',
'numImageColumns_max',
type=int,
fallback=1),
'defaultImage_w':
self.config.getProperty('LabelUI',
'defaultImage_w',
type=int,
fallback=800),
'defaultImage_h':
self.config.getProperty('LabelUI',
'defaultImage_h',
type=int,
fallback=600),
'styles':
styles['styles'],
'backdrops':
backdrops,
'welcomeMessage':
welcomeMessage,
'demoMode':
self.config.getProperty('Project',
'demoMode',
type=bool,
fallback=False)
}
def _assemble_annotations(self, cursor):
response = {}
while True:
b = cursor.fetchone()
if b is None:
break
imgID = str(b['image'])
if not imgID in response:
response[imgID] = {
'fileName': b['filename'],
'predictions': {},
'annotations': {},
'last_checked': None
}
viewcount = b['viewcount']
if viewcount is not None:
response[imgID]['viewcount'] = viewcount
last_checked = b['last_checked']
if last_checked is not None:
if response[imgID]['last_checked'] is None:
response[imgID]['last_checked'] = last_checked
else:
response[imgID]['last_checked'] = max(
response[imgID]['last_checked'], last_checked)
# parse annotations and predictions
entryID = str(b['id'])
if b['ctype'] is not None:
colnames = self.sqlBuilder.getColnames(b['ctype'])
entry = {}
for c in colnames:
value = b[c]
if isinstance(value, datetime):
value = value.timestamp()
elif isinstance(value, UUID):
value = str(value)
entry[c] = value
if b['ctype'] == 'annotation':
response[imgID]['annotations'][entryID] = entry
elif b['ctype'] == 'prediction':
response[imgID]['predictions'][entryID] = entry
return response
def getProjectSettings(self):
'''
Queries the database for general project-specific metadata, such as:
- Classes: names, indices, default colors
- Annotation type: one of {class labels, positions, bboxes}
'''
return self.projectSettings
def getProjectInfo(self):
'''
Returns safe, shareable information about the project.
'''
return {
'projectName':
self.projectSettings['projectName'],
'projectDescription':
self.projectSettings['projectDescription'],
'demoMode':
self.config.getProperty('Project',
'demoMode',
type=bool,
fallback=False),
'backdrops':
self.projectSettings['backdrops']['images']
}
def getClassDefinitions(self):
'''
Returns a dictionary with entries for all classes in the project.
'''
classdef = {
'entries': {
'default': {} # default group for ungrouped label classes
}
}
schema = self.config.getProperty('Database', 'schema')
# query data
sql = '''
SELECT 'group' AS type, id, NULL as idx, name, color, parent, NULL AS keystroke FROM {schema}.labelclassgroup
UNION ALL
SELECT 'class' AS type, id, idx, name, color, labelclassgroup, keystroke FROM {schema}.labelclass;
'''.format(schema=schema)
classData = self.dbConnector.execute(sql, None, 'all')
# assemble entries first
allEntries = {}
numClasses = 0
for cl in classData:
id = str(cl['id'])
entry = {
'id': id,
'name': cl['name'],
'color': cl['color'],
'parent':
str(cl['parent']) if cl['parent'] is not None else None,
}
if cl['type'] == 'group':
entry['entries'] = {}
else:
entry['index'] = cl['idx']
entry['keystroke'] = cl['keystroke']
numClasses += 1
allEntries[id] = entry
# transform into tree
def _find_parent(tree, parentID):
if parentID is None:
return tree['entries']['default']
elif 'id' in tree and tree['id'] == parentID:
return tree
elif 'entries' in tree:
for ek in tree['entries'].keys():
rv = _find_parent(tree['entries'][ek], parentID)
if rv is not None:
return rv
return None
else:
return None
allEntries['default'] = {'name': '(other)', 'entries': {}}
allEntries = {'entries': allEntries}
for key in list(allEntries['entries'].keys()):
if key == 'default':
continue
if key in allEntries['entries']:
entry = allEntries['entries'][key]
parentID = entry['parent']
del entry['parent']
if 'entries' in entry and parentID is None:
# group, but no parent: append to root directly
allEntries['entries'][key] = entry
else:
# move item
parent = _find_parent(allEntries, parentID)
parent['entries'][key] = entry
del allEntries['entries'][key]
classdef = allEntries
classdef['numClasses'] = numClasses
return classdef
def getBatch_fixed(self, username, data):
'''
Returns entries from the database based on the list of data entry identifiers specified.
'''
# query
sql = self.sqlBuilder.getFixedImagesQueryString(
self.projectSettings['demoMode'])
# parse results
queryVals = (
tuple(UUID(d) for d in data),
username,
username,
)
if self.projectSettings['demoMode']:
queryVals = (tuple(UUID(d) for d in data), )
with self.dbConnector.execute_cursor(sql, queryVals) as cursor:
try:
response = self._assemble_annotations(cursor)
# self.dbConnector.conn.commit()
except Exception as e:
print(e)
# self.dbConnector.conn.rollback()
finally:
pass
# cursor.close()
return {'entries': response}
def getBatch_auto(self,
username,
order='unlabeled',
subset='default',
limit=None):
'''
TODO: description
'''
# query
sql = self.sqlBuilder.getNextBatchQueryString(
order, subset, self.projectSettings['demoMode'])
# limit (TODO: make 128 a hyperparameter)
if limit is None:
limit = 128
else:
limit = min(int(limit), 128)
# parse results
queryVals = (
username,
limit,
username,
)
if self.projectSettings['demoMode']:
queryVals = (limit, )
with self.dbConnector.execute_cursor(sql, queryVals) as cursor:
response = self._assemble_annotations(cursor)
return {'entries': response}
def getBatch_timeRange(self,
minTimestamp,
maxTimestamp,
userList,
skipEmptyImages=False,
limit=None):
'''
Returns images that have been annotated within the given time range and/or
by the given user(s). All arguments are optional.
Useful for reviewing existing annotations.
'''
# query string
sql = self.sqlBuilder.getDateQueryString(minTimestamp, maxTimestamp,
userList, skipEmptyImages)
# check validity and provide arguments
queryVals = []
if userList is not None:
queryVals.append(tuple(userList))
if minTimestamp is not None:
queryVals.append(minTimestamp)
if maxTimestamp is not None:
queryVals.append(maxTimestamp)
if skipEmptyImages and userList is not None:
queryVals.append(tuple(userList))
# limit (TODO: make 128 a hyperparameter)
if limit is None:
limit = 128
else:
limit = min(int(limit), 128)
queryVals.append(limit)
if userList is not None:
queryVals.append(tuple(userList))
# query and parse results
with self.dbConnector.execute_cursor(sql, tuple(queryVals)) as cursor:
try:
response = self._assemble_annotations(cursor)
# self.dbConnector.conn.commit()
except Exception as e:
print(e)
# self.dbConnector.conn.rollback()
finally:
pass
# cursor.close()
return {'entries': response}
def get_timeRange(self, userList, skipEmptyImages=False):
'''
Returns two timestamps denoting the temporal limits within which
images have been viewed by the users provided in the userList.
Arguments:
- userList: string (single user name) or list of strings (multiple).
Can also be None; in this case all annotations will be
checked.
- skipEmptyImages: if True, only images that contain at least one
annotation will be considered.
'''
# query string
sql = self.sqlBuilder.getTimeRangeQueryString(userList,
skipEmptyImages)
arguments = (None if userList is None else tuple(userList))
result = self.dbConnector.execute(sql, (arguments, ), numReturn=1)
if result is not None and len(result):
return {
'minTimestamp': result[0]['mintimestamp'],
'maxTimestamp': result[0]['maxtimestamp'],
}
else:
return {'error': 'no annotations made'}
def submitAnnotations(self, username, submissions):
'''
Sends user-provided annotations to the database.
'''
if self.projectSettings['demoMode']:
return 0
# assemble values
colnames = getattr(QueryStrings_annotation,
self.projectSettings['annotationType']).value
values_insert = []
values_update = []
meta = (None if not 'meta' in submissions else json.dumps(
submissions['meta']))
# for deletion: remove all annotations whose image ID matches but whose annotation ID is not among the submitted ones
ids = []
viewcountValues = []
for imageKey in submissions['entries']:
entry = submissions['entries'][imageKey]
try:
lastChecked = entry['timeCreated']
lastTimeRequired = entry['timeRequired']
if lastTimeRequired is None: lastTimeRequired = 0
except:
lastChecked = datetime.now(tz=pytz.utc)
lastTimeRequired = 0
if 'annotations' in entry and len(entry['annotations']):
for annotation in entry['annotations']:
# assemble annotation values
annotationTokens = self.annoParser.parseAnnotation(
annotation)
annoValues = []
for cname in colnames:
if cname == 'id':
if cname in annotationTokens:
# cast and only append id if the annotation is an existing one
annoValues.append(UUID(
annotationTokens[cname]))
ids.append(UUID(annotationTokens[cname]))
elif cname == 'image':
annoValues.append(UUID(imageKey))
elif cname == 'label' and annotationTokens[
cname] is not None:
annoValues.append(UUID(annotationTokens[cname]))
elif cname == 'timeCreated':
try:
annoValues.append(
dateutil.parser.parse(
annotationTokens[cname]))
except:
annoValues.append(datetime.now(tz=pytz.utc))
elif cname == 'timeRequired':
timeReq = annotationTokens[cname]
if timeReq is None: timeReq = 0
annoValues.append(timeReq)
elif cname == 'username':
annoValues.append(username)
elif cname in annotationTokens:
annoValues.append(annotationTokens[cname])
elif cname == 'unsure':
if 'unsure' in annotationTokens and annotationTokens[
'unsure'] is not None:
annoValues.append(annotationTokens[cname])
else:
annoValues.append(False)
elif cname == 'meta':
annoValues.append(meta)
else:
annoValues.append(None)
if 'id' in annotationTokens:
# existing annotation; update
values_update.append(tuple(annoValues))
else:
# new annotation
values_insert.append(tuple(annoValues))
viewcountValues.append(
(username, imageKey, 1, lastChecked, lastTimeRequired, meta))
schema = self.config.getProperty('Database', 'schema')
# delete all annotations that are not in submitted batch
imageKeys = list(UUID(k) for k in submissions['entries'])
if len(imageKeys):
if len(ids):
sql = '''
DELETE FROM {schema}.annotation WHERE username = %s AND id IN (
SELECT idQuery.id FROM (
SELECT * FROM {schema}.annotation WHERE id NOT IN %s
) AS idQuery
JOIN (
SELECT * FROM {schema}.annotation WHERE image IN %s
) AS imageQuery ON idQuery.id = imageQuery.id);
'''.format(schema=schema)
self.dbConnector.execute(sql, (
username,
tuple(ids),
tuple(imageKeys),
))
else:
# no annotations submitted; delete all annotations submitted before
sql = '''
DELETE FROM {schema}.annotation WHERE username = %s AND image IN %s;
'''.format(schema=schema)
self.dbConnector.execute(sql, (
username,
tuple(imageKeys),
))
# insert new annotations
if len(values_insert):
sql = '''
INSERT INTO {}.annotation ({})
VALUES %s ;
'''.format(
schema,
', '.join(colnames[1:]) # skip 'id' column
)
self.dbConnector.insert(sql, values_insert)
# update existing annotations
if len(values_update):
updateCols = ''
for col in colnames:
if col == 'label':
updateCols += '{col} = UUID(e.{col}),'.format(col=col)
elif col == 'timeRequired':
# we sum the required times together
updateCols += '{col} = COALESCE(a.{col},0) + COALESCE(e.{col},0),'.format(
col=col)
else:
updateCols += '{col} = e.{col},'.format(col=col)
sql = '''
UPDATE {schema}.annotation AS a
SET {updateCols}
FROM (VALUES %s) AS e({colnames})
WHERE e.id = a.id;
'''.format(schema=schema,
updateCols=updateCols.strip(','),
colnames=', '.join(colnames))
self.dbConnector.insert(sql, values_update)
# viewcount table
sql = '''
INSERT INTO {}.image_user (username, image, viewcount, last_checked, last_time_required, meta)
VALUES %s
ON CONFLICT (username, image) DO UPDATE SET viewcount = image_user.viewcount + 1, last_checked = EXCLUDED.last_checked, last_time_required = EXCLUDED.last_time_required, meta = EXCLUDED.meta;
'''.format(schema)
self.dbConnector.insert(sql, viewcountValues)
return 0
def __init__(self, config, celery_app):
self.config = config
self.dbConn = Database(config)
self.sqlBuilder = SQLStringBuilder(config)
self.celery_app = celery_app
class AIMiddleware():
def __init__(self, config):
self.config = config
self.dbConn = Database(config)
self.sqlBuilder = SQLStringBuilder(config)
self.training = False # will be set to True once start_training is called (and False as soon as everything about the training process has finished)
self.celery_app = current_app
self.celery_app.set_current()
self.celery_app.set_default()
self.watchdog = None # note: watchdog only created if users poll status (i.e., if there's activity)
#TODO
self.messageProcessor = MessageProcessor(self.celery_app)
self.messageProcessor.start()
def _init_watchdog(self):
'''
Launches a thread that periodically polls the database for new
annotations. Once the required number of new annotations is reached,
this thread will initiate the training process through the middleware.
The thread will be terminated and destroyed; a new thread will only be
re-created once the training process has finished.
'''
if self.training:
return
numImages_autoTrain = self.config.getProperty('AIController',
'numImages_autoTrain',
type=int,
fallback=-1)
if numImages_autoTrain == -1:
return
self.watchdog = Watchdog(self.config, self.dbConn, self)
self.watchdog.start()
def _get_num_available_workers(self):
#TODO: message + queue if no worker available
#TODO: limit to n tasks per worker
i = self.celery_app.control.inspect()
if i is not None:
stats = i.stats()
if stats is not None:
return len(i.stats())
return 1 #TODO
def _training_completed(self, trainingJob):
'''
To be called after a training process has been completed.
If there is more than one worker, the 'average_model_states'
instruction of the AI model is called and again awaited for.
After successful training, the 'training' flag will be set
to False to allow another round of model training.
'''
# re-enable training if no other training job is ongoing
self.training = self.messageProcessor.task_ongoing('train')
def _get_training_job_signature(self,
minTimestamp='lastState',
minNumAnnoPerImage=0,
maxNumImages=None,
maxNumWorkers=-1):
'''
Assembles (but does not submit) a training job based on the provided parameters.
'''
# check if training is still in progress
if self.messageProcessor.task_ongoing('train'):
raise Exception('Training process already running.')
self.training = True
try:
# sanity checks
if not (isinstance(minTimestamp, datetime)
or minTimestamp == 'lastState' or minTimestamp == -1
or minTimestamp is None):
raise ValueError(
'{} is not a recognized property for variable "minTimestamp"'
.format(str(minTimestamp)))
if maxNumWorkers != 1:
# only query the number of available workers if more than one is specified to save time
num_workers = min(maxNumWorkers,
self._get_num_available_workers())
else:
num_workers = maxNumWorkers
# query image IDs
sql = self.sqlBuilder.getLatestQueryString(
minNumAnnoPerImage=minNumAnnoPerImage, limit=maxNumImages)
if isinstance(minTimestamp, datetime):
imageIDs = self.dbConn.execute(sql, (minTimestamp, ), 'all')
else:
imageIDs = self.dbConn.execute(sql, None, 'all')
imageIDs = [i['image'] for i in imageIDs]
if maxNumWorkers > 1:
# distribute across workers (TODO: also specify subset size for multiple jobs; randomly draw if needed)
images_subset = array_split(
imageIDs, max(1,
len(imageIDs) // num_workers))
processes = []
for subset in images_subset:
processes.append(
celery_interface.call_train.si(subset, True))
process = group(processes)
else:
# call one worker directly
# process = celery_interface.call_train.delay(data) #TODO: route to specific worker? http://docs.celeryproject.org/en/latest/userguide/routing.html#manual-routing
process = celery_interface.call_train.si(imageIDs, False)
return process, num_workers
except:
self.training = self.messageProcessor.task_ongoing('train')
return None
def _get_inference_job_signature(self, imageIDs, maxNumWorkers=-1):
'''
Assembles (but does not submit) an inference job based on the provided parameters.
'''
# setup
if maxNumWorkers != 1:
# only query the number of available workers if more than one is specified to save time
num_available = self._get_num_available_workers()
if maxNumWorkers == -1:
maxNumWorkers = num_available #TODO: more than one process per worker?
else:
maxNumWorkers = min(maxNumWorkers, num_available)
# distribute across workers
images_subset = array_split(imageIDs,
max(1,
len(imageIDs) // maxNumWorkers))
jobs = []
for subset in images_subset:
job = celery_interface.call_inference.si(imageIDs=subset)
jobs.append(job)
jobGroup = group(jobs)
return jobGroup
def start_training(self,
minTimestamp='lastState',
minNumAnnoPerImage=0,
maxNumImages=None,
maxNumWorkers=-1):
'''
Initiates a training round for the model, based on the set of data (images, annotations)
as specified in the parameters. Distributes data to the set of registered AIWorker instan-
ces, which then call the 'train' function of the AI model given in the configuration. Upon
training completion, the model states as returned by the function, and eventually the
AIWorker instances are collected, and the AIController calls the 'average_states' function
of the AI model to get one single, most recent state. This is finally inserted to the data-
base.
Note that this function only loads the annotation data from the database, but not the images.
Retrieving images is part of the AI model's 'train' function. TODO: feature vectors?
Input parameters:
- minTimestamp: Defines the earliest point in time of the annotations to be considered for
model training. May take one of the following values:
- 'lastState' (default): Limits the annotations to those made after the time-
stamp of the latest model state. If no model state is
found, all annotations are considered.
- None, -1, or 'all': Includes all annotations.
- (a datetime object): Includes annotations made after a custom timestamp.
- minNumAnnoPerImage: Minimum number of annotations per image to be considered for training.
This may be useful for e.g. detection tasks with a lot of false alarms
in order to limit the "forgetting factor" of the model subject to training.
- maxNumImages: Maximum number of images to train on at a time.
- maxNumWorkers: Specify the maximum number of workers to distribute training to. If set to 1,
the model is trained on just one worker (no model state averaging appended).
If set to a number, that number of workers (up to the maximum number of connected)
is consulted for training the model. Upon completion, all model state dictionaries
are averaged by one random worker.
If set to -1, all connected workers are considered. //TODO: load balancing?
Returns:
- A dict with a status message. May take one of the following:
- TODO: status ok, fail, no annotations, etc. Make threaded so that it immediately returns something.
'''
process, numWorkers = self._get_training_job_signature(
minTimestamp=minTimestamp,
minNumAnnoPerImage=minNumAnnoPerImage,
maxNumImages=maxNumImages,
maxNumWorkers=maxNumWorkers)
# submit job
task_id = self.messageProcessor.task_id()
if numWorkers > 1:
# also append average model states job
job = process.apply_async(
task_id=task_id,
ignore_result=False,
result_extended=True,
headers={
'type': 'train',
'submitted': str(current_time())
},
link=celery_interface.call_average_model_states.s())
else:
job = process.apply_async(task_id=task_id,
ignore_result=False,
result_extended=True,
headers={
'type': 'train',
'submitted': str(current_time())
})
# start listener
self.messageProcessor.register_job(job, 'train',
self._training_completed)
return 'ok'
def _do_inference(self, process):
# send job
task_id = self.messageProcessor.task_id()
result = process.apply_async(task_id=task_id,
ignore_result=False,
result_extended=True,
headers={
'type': 'inference',
'submitted': str(current_time())
})
# start listener
self.messageProcessor.register_job(result, 'inference', None)
return
def start_inference(self,
forceUnlabeled=True,
maxNumImages=-1,
maxNumWorkers=-1):
'''
Performs inference (prediction) on a set of data (images) as specified in the parameters. Distributes
data to the set of registered AIWorker instances, which then call the 'inference' function of the AI
model given in the configuration. Upon completion, each AIWorker then automatically inserts the latest
predictions into the database and reports back to the AIController (this instance) that its job has
finished.
Note that this function only loads the annotation data from the database, but not the images.
Retrieving images is part of the AI model's 'train' function.
The AI model, depending on its configuration, may or may not choose to load the images, but just work
with the feature vectors as provided through the database directly. This is particularly useful for mo-
dels that are supposed to have e.g. a frozen feature extractor, but fine-tune the last prediction branch
at each inference time to accelerate the process.
Input parameters:
- forceUnlabeled: If True, only images that have not been labeled (i.e., with a viewcount of 0) will be
predicted on (default).
- maxNumImages: Manually override the project settings' maximum number of images to do inference on.
If set to -1 (default), the value from the project settings will be chosen.
- maxNumWorkers: Manually set the maximum number of AIWorker instances to perform inference at the same
time. If set to -1 (default), the data will be divided across all registered workers.
'''
# setup
if maxNumImages is None or maxNumImages == -1:
maxNumImages = self.config.getProperty('AIController',
'maxNumImages_inference',
type=int)
# load the IDs of the images that are being subjected to inference
sql = self.sqlBuilder.getInferenceQueryString(forceUnlabeled,
maxNumImages)
imageIDs = self.dbConn.execute(sql, None, 'all')
imageIDs = [i['image'] for i in imageIDs]
process = self._get_inference_job_signature(imageIDs, maxNumWorkers)
self._do_inference(process)
return 'ok'
def inference_fixed(self, imageIDs, maxNumWorkers=-1):
'''
Performs inference (prediction) on a fixed set of data (images), as provided by the parameter 'imageIDs'.
Distributes data to the set of registered AIWorker instances, which then call the 'inference' function of
the AI model given in the configuration. Upon completion, each AIWorker then automatically inserts the
latest predictions into the database and reports back to the AIController (this instance) that its job has
finished.
Note that this function only loads the annotation data from the database, but not the images.
Retrieving images is part of the AI model's 'train' function.
The AI model, depending on its configuration, may or may not choose to load the images, but just work
with the feature vectors as provided through the database directly. This is particularly useful for mo-
dels that are supposed to have e.g. a frozen feature extractor, but fine-tune the last prediction branch
at each inference time to accelerate the process.
Input parameters:
- imageIDs: An array containing the UUIDs (or equivalent strings) of the images that need to be inferred on.
- maxNumWorkers: Manually set the maximum number of AIWorker instances to perform inference at the same
time. If set to -1 (default), the data will be divided across all registered workers.
'''
process = self._get_inference_job_signature(imageIDs, maxNumWorkers)
self._do_inference(process)
return 'ok'
def start_train_and_inference(self,
minTimestamp='lastState',
minNumAnnoPerImage=0,
maxNumImages_train=None,
maxNumWorkers_train=1,
forceUnlabeled_inference=True,
maxNumImages_inference=None,
maxNumWorkers_inference=1):
'''
Submits a model training job, followed by inference.
This is the default behavior for the automated model update, since the newly trained model should directly
be used to infer new, potentially useful labels.
'''
# get training job signature
process, numWorkers_train = self._get_training_job_signature(
minTimestamp=minTimestamp,
minNumAnnoPerImage=minNumAnnoPerImage,
maxNumImages=maxNumImages_train,
maxNumWorkers=maxNumWorkers_train)
# submit job
task_id = self.messageProcessor.task_id()
if numWorkers_train > 1:
# also append average model states job
job = process.apply_async(
task_id=task_id,
ignore_result=False,
result_extended=True,
headers={
'type': 'train',
'submitted': str(current_time())
},
link=celery_interface.call_average_model_states.s())
else:
job = process.apply_async(task_id=task_id,
ignore_result=False,
result_extended=True,
headers={
'type': 'train',
'submitted': str(current_time())
})
# start listener thread
def chain_inference(*args):
self.training = self.messageProcessor.task_ongoing('train')
return self.start_inference(forceUnlabeled_inference,
maxNumImages_inference,
maxNumWorkers_inference)
#TODO: chaining doesn't work properly this way...
self.messageProcessor.register_job(job, 'train', chain_inference)
return 'ok'
def check_status(self, project, tasks, workers):
'''
Queries the Celery worker results depending on the parameters specified.
Returns their status accordingly if they exist.
'''
status = {}
# project status
if project:
if self.training:
status['project'] = {}
else:
# notify watchdog that users are active
if self.watchdog is None or self.watchdog.stopped():
self._init_watchdog()
if self.watchdog is not None:
self.watchdog.nudge()
status['project'] = {
'num_annotated': self.watchdog.lastCount,
'num_next_training': self.watchdog.annoThreshold
}
else:
status['project'] = {}
# running tasks status
if tasks:
status['tasks'] = self.messageProcessor.poll_status()
# get worker status (this is very expensive, as each worker needs to be pinged)
if workers:
status['workers'] = self.messageProcessor.poll_worker_status()
return status
def main():
# parse arguments
parser = argparse.ArgumentParser(description='AIDE local model tester')
parser.add_argument('--project',
type=str,
required=True,
help='Project shortname to draw sample data from.')
parser.add_argument(
'--mode',
type=str,
required=True,
help=
'Evaluation mode (function to call). One of {"train", "inference"}.')
parser.add_argument(
'--modelLibrary',
type=str,
required=False,
help=
'Optional AI model library override. Provide a dot-separated Python import path here.'
)
parser.add_argument(
'--modelSettings',
type=str,
required=False,
help=
'Optional AI model settings override (absolute or relative path to settings file, or else "none" to not use any predefined settings).'
)
args = parser.parse_args()
#TODO: continue
assert args.mode.lower() in (
'train', 'inference'), f'"{args.mode}" is not a known evaluation mode.'
mode = args.mode.lower()
# initialize required modules
config = Config()
dbConnector = Database(config)
fileServer = FileServer(config).get_secure_instance(args.project)
aiw = AIWorker(config, dbConnector, True)
aicw = AIControllerWorker(config, None)
# check if AIDE file server is reachable
admin = AdminMiddleware(config, dbConnector)
connDetails = admin.getServiceDetails(True, False)
fsVersion = connDetails['FileServer']['aide_version']
if not isinstance(fsVersion, str):
# no file server running
raise Exception(
'ERROR: AIDE file server is not running, but required for running models. Make sure to launch it prior to running this script.'
)
elif fsVersion != AIDE_VERSION:
print(
f'WARNING: the AIDE version of File Server instance ({fsVersion}) differs from this one ({AIDE_VERSION}).'
)
# get model trainer instance and settings
queryStr = '''
SELECT ai_model_library, ai_model_settings FROM aide_admin.project
WHERE shortname = %s;
'''
result = dbConnector.execute(queryStr, (args.project, ), 1)
if result is None or not len(result):
raise Exception(
f'Project "{args.project}" could not be found in this installation of AIDE.'
)
modelLibrary = result[0]['ai_model_library']
modelSettings = result[0]['ai_model_settings']
customSettingsSpecified = False
if hasattr(args, 'modelSettings') and isinstance(
args.modelSettings, str) and len(args.modelSettings):
# settings override specified
if args.modelSettings.lower() == 'none':
modelSettings = None
customSettingsSpecified = True
elif not os.path.isfile(args.modelSettings):
print(
f'WARNING: model settings override provided, but file cannot be found ("{args.modelSettings}"). Falling back to project default ("{modelSettings}").'
)
else:
modelSettings = args.modelSettings
customSettingsSpecified = True
if hasattr(args, 'modelLibrary') and isinstance(
args.modelLibrary, str) and len(args.modelLibrary):
# library override specified; try to import it
try:
modelClass = helpers.get_class_executable(args.modelLibrary)
if modelClass is None:
raise
modelLibrary = args.modelLibrary
# re-check if current model settings are compatible; warn and set to None if not
if modelLibrary != result[0][
'ai_model_library'] and not customSettingsSpecified:
# project model settings are not compatible with provided model
print(
'WARNING: custom model library specified differs from the one currently set in project. Model settings will be set to None.'
)
modelSettings = None
except Exception as e:
print(
f'WARNING: model library override provided ("{args.modelLibrary}"), but could not be imported. Falling back to project default ("{modelLibrary}").'
)
# initialize instance
print(f'Using model library "{modelLibrary}".')
modelTrainer = aiw._init_model_instance(args.project, modelLibrary,
modelSettings)
stateDict = None #TODO: load latest unless override is specified?
# get data
data = aicw.get_training_images(project=args.project, maxNumImages=512)
data = __load_metadata(args.project, dbConnector, data[0],
(mode == 'train'))
# helper functions
def updateStateFun(state, message, done=None, total=None):
print(message, end='')
if done is not None and total is not None:
print(f': {done}/{total}')
else:
print('')
# launch task
if mode == 'train':
result = modelTrainer.train(stateDict, data, updateStateFun)
if result is None:
raise Exception(
'Training function must return an object (i.e., trained model state) to be stored in the database.'
)
elif mode == 'inference':
result = modelTrainer.inference(stateDict, data, updateStateFun)
class UserMiddleware():
TOKEN_NUM_BYTES = 64
SALT_NUM_ROUNDS = 12
def __init__(self, config):
self.config = config
self.dbConnector = Database(config)
self.usersLoggedIn = {} # username -> {timestamp, sessionToken}
def _current_time(self):
return current_time()
def _create_token(self):
return secrets.token_urlsafe(self.TOKEN_NUM_BYTES)
def _compare_tokens(self, tokenA, tokenB):
if tokenA is None or tokenB is None:
return False
return secrets.compare_digest(tokenA, tokenB)
def _check_password(self, providedPass, hashedTargetPass):
return bcrypt.checkpw(providedPass, hashedTargetPass)
def _create_hash(self, password):
hash = bcrypt.hashpw(password, bcrypt.gensalt(self.SALT_NUM_ROUNDS))
return hash
def _get_user_data(self, username):
result = self.dbConnector.execute(
'SELECT last_login, session_token, secret_token FROM aide_admin.user WHERE name = %s;',
(username, ),
numReturn=1)
if not len(result):
return None
result = result[0]
return result
def _extend_session_database(self, username, sessionToken):
'''
Updates the last login timestamp of the user to the current
time and commits the changes to the database.
Runs in a thread to be non-blocking.
'''
def _extend_session():
now = self._current_time()
self.dbConnector.execute(
'''UPDATE aide_admin.user SET last_login = %s,
session_token = %s
WHERE name = %s
''', (
now,
sessionToken,
username,
),
numReturn=None)
# also update local cache
self.usersLoggedIn[username]['timestamp'] = now
eT = Thread(target=_extend_session)
eT.start()
def _init_or_extend_session(self, username, sessionToken=None):
'''
Establishes a "session" for the user (i.e., sets 'time_login'
to now).
Also creates a new sessionToken if None provided.
'''
now = self._current_time()
if sessionToken is None:
sessionToken = self._create_token()
# new session created; add to database
self.dbConnector.execute(
'''UPDATE aide_admin.user SET last_login = %s, session_token = %s
WHERE name = %s
''', (
now,
sessionToken,
username,
),
numReturn=None)
# store locally
self.usersLoggedIn[username] = {
'timestamp': now,
'sessionToken': sessionToken
}
# update local cache as well
if not username in self.usersLoggedIn:
self.usersLoggedIn[username] = {
'timestamp': now,
'sessionToken': sessionToken
}
else:
self.usersLoggedIn[username]['timestamp'] = now
self.usersLoggedIn[username]['sessionToken'] = sessionToken
# also tell DB about updated tokens
self._extend_session_database(username, sessionToken)
expires = now + timedelta(
0, self.config.getProperty('UserHandler', 'time_login', type=int))
return sessionToken, now, expires
def _invalidate_session(self, username):
if username in self.usersLoggedIn:
del self.usersLoggedIn[username]
self.dbConnector.execute(
'UPDATE aide_admin.user SET session_token = NULL WHERE name = %s',
(username, ),
numReturn=None)
#TODO: feedback that everything is ok?
def _check_account_exists(self, username, email):
response = {'username': True, 'email': True}
if username is None or not len(username): username = ''
if email is None or not len(email): email = ''
result = self.dbConnector.execute(
'SELECT COUNT(name) AS c FROM aide_admin.user WHERE name = %s UNION ALL SELECT COUNT(name) AS c FROM aide_admin.user WHERE email = %s',
(
username,
email,
),
numReturn=2)
response['username'] = (result[0]['c'] > 0)
response['email'] = (result[1]['c'] > 0)
return response
def _check_logged_in(self, username, sessionToken):
now = self._current_time()
time_login = self.config.getProperty('UserHandler',
'time_login',
type=int)
if not username in self.usersLoggedIn:
# check database
result = self._get_user_data(username)
if result is None:
# account does not exist
return False
# check for session token
if not self._compare_tokens(result['session_token'], sessionToken):
# invalid session token provided
return False
# check for timestamp
time_diff = (now - result['last_login']).total_seconds()
if time_diff <= time_login:
# user still logged in
if not username in self.usersLoggedIn:
self.usersLoggedIn[username] = {
'timestamp': now,
'sessionToken': sessionToken
}
else:
self.usersLoggedIn[username]['timestamp'] = now
# extend user session (commit to DB) if needed
if time_diff >= 0.75 * time_login:
self._extend_session_database(username, sessionToken)
return True
else:
# session time-out
return False
# generic error
return False
else:
# check locally
if not self._compare_tokens(
self.usersLoggedIn[username]['sessionToken'],
sessionToken):
# invalid session token provided; check database if token has updated
# (can happen if user logs in again from another machine)
result = self._get_user_data(username)
if not self._compare_tokens(result['session_token'],
sessionToken):
return False
else:
# update local cache
self.usersLoggedIn[username]['sessionToken'] = result[
'session_token']
self.usersLoggedIn[username]['timestamp'] = now
if (now - self.usersLoggedIn[username]['timestamp']
).total_seconds() <= time_login:
# user still logged in
return True
else:
# local cache session time-out; check if database holds more recent timestamp
result = self._get_user_data(username)
if (now - result['last_login']).total_seconds() <= time_login:
# user still logged in; update
self._init_or_extend_session(username, sessionToken)
else:
# session time-out
return False
# generic error
return False
# generic error
return False
def _check_authorized(self, project, username, admin, return_all=False):
'''
Verifies whether a user has access rights to a project.
If "return_all" is set to True, a dict with the following bools
is returned:
- enrolled: if the user is member of the project
- isAdmin: if the user is a project administrator
- isPublic: if the project is publicly visible (*)
- demoMode: if the project runs in demo mode (*)
(* note that these are here for convenience, but do not count
as authorization tokens)
If "return_all" is False, only a single bool is returned, with
criteria as follows:
- if "admin" is set to True, the user must be a project admini-
strator
- else, the user must be enrolled, admitted, and not blocked for
the current date and time
In this case, options like the demo mode and public flag are not
relevant for the decision.
'''
now = current_time()
response = {'enrolled': False, 'isAdmin': False, 'isPublic': False}
queryStr = sql.SQL('''
SELECT * FROM aide_admin.authentication AS auth
JOIN (SELECT shortname, demoMode, isPublic FROM aide_admin.project) AS proj
ON auth.project = proj.shortname
WHERE project = %s AND username = %s;
''')
try:
result = self.dbConnector.execute(queryStr, (
project,
username,
), 1)
if len(result):
response['isAdmin'] = result[0]['isadmin']
response['isPublic'] = result[0]['ispublic']
admitted_until = True
blocked_until = False
if result[0]['admitted_until'] is not None:
admitted_until = (result[0]['admitted_until'] >= now)
if result[0]['blocked_until'] is not None:
blocked_until = (result[0]['blocked_until'] >= now)
response['enrolled'] = (admitted_until and not blocked_until)
except:
# no results to fetch: user is not authenticated
pass
# check if super user
superUser = self._check_user_privileges(username, superuser=True)
if superUser:
response['enrolled'] = True
response['isAdmin'] = True
if return_all:
return response
else:
if admin:
return response['isAdmin']
else:
return response['enrolled']
# if admin:
# queryStr = sql.SQL('''SELECT COUNT(*) AS cnt FROM aide_admin.authentication
# WHERE project = %s AND username = %s AND isAdmin = %s''')
# queryVals = (project,username,admin,)
# else:
# queryStr = sql.SQL('''SELECT COUNT(*) AS cnt FROM aide_admin.authentication
# WHERE project = %s AND username = %s
# AND (
# (admitted_until IS NULL OR admitted_until >= now())
# AND
# (blocked_until IS NULL OR blocked_until < now())
# )''')
# queryVals = (project,username,)
# result = self.dbConnector.execute(queryStr, queryVals, 1)
# return result[0]['cnt'] == 1
def checkDemoMode(self, project):
return checkDemoMode(project, self.dbConnector)
def decryptSessionToken(self, username, request):
try:
userdata = self._get_user_data(username)
return request.get_cookie('session_token',
secret=userdata['secret_token'])
except:
return None
def encryptSessionToken(self, username, response):
userdata = self._get_user_data(username)
response.set_cookie('session_token',
userdata['session_token'],
httponly=True,
path='/',
secret=userdata['secret_token'])
def _check_user_privileges(self,
username,
superuser=False,
canCreateProjects=False,
return_all=False):
response = {'superuser': False, 'can_create_projects': False}
result = self.dbConnector.execute(
'''SELECT isSuperUser, canCreateProjects
FROM aide_admin.user WHERE name = %s;''', (username, ), 1)
if len(result):
response['superuser'] = result[0]['issuperuser']
response['can_create_projects'] = result[0]['cancreateprojects']
if return_all:
return response
else:
if superuser and not result[0]['issuperuser']:
return False
if canCreateProjects and not (result[0]['cancreateprojects']
or result[0]['issuperuser']):
return False
return True
def isAuthenticated(self,
username,
sessionToken,
project=None,
admin=False,
superuser=False,
canCreateProjects=False,
extend_session=False,
return_all=False):
'''
Checks if the user is authenticated to access a service.
Returns False if one or more of the following conditions holds:
- user is not logged in
- 'project' (shortname) is provided, project is configured to be private and user is not in the
authenticated users list
- 'admin' is True, 'project' (shortname) is provided and user is not an admin of the project
- 'superuser' is True and user is not a super user
- 'canCreateProjects' is True and user is not authenticated to create (or remove) projects
If 'extend_session' is True, the user's session will automatically be prolonged by the max login time
specified in the configuration file.
If 'return_all' is True, all individual flags (instead of just a single bool) is returned.
'''
demoMode = checkDemoMode(project, self.dbConnector)
if return_all:
returnVals = {}
returnVals['logged_in'] = self._check_logged_in(
username, sessionToken)
if not returnVals['logged_in']:
username = None
if project is not None:
returnVals['project'] = self._check_authorized(project,
username,
admin,
return_all=True)
returnVals['project']['demoMode'] = demoMode
returnVals['privileges'] = self._check_user_privileges(
username, superuser, canCreateProjects, return_all=True)
if returnVals['logged_in'] and extend_session:
self._init_or_extend_session(username, sessionToken)
return returnVals
else:
# return True if project is in demo mode
if demoMode is not None and demoMode:
return True
if not self._check_logged_in(username, sessionToken):
return False
if project is not None and not self._check_authorized(
project, username, admin):
return False
if not self._check_user_privileges(username, superuser,
canCreateProjects):
return False
if extend_session:
self._init_or_extend_session(username, sessionToken)
return True
def getAuthentication(self, username, project=None):
'''
Returns general authentication properties of the user, regardless of whether
they are logged in or not.
If a project shortname is specified, this will also return the user access
properties for the given project.
'''
response = {}
if project is None:
result = self.dbConnector.execute(
'''SELECT * FROM aide_admin.user AS u
WHERE name = %s;
''', (username, ), 1)
response['canCreateProjects'] = result[0]['cancreateprojects']
response['isSuperUser'] = result[0]['issuperuser']
else:
result = self.dbConnector.execute(
'''SELECT * FROM aide_admin.user AS u
JOIN aide_admin.authentication AS a
ON u.name = a.username
WHERE name = %s
AND project = %s;
''', (
username,
project,
), 1)
response['canCreateProjects'] = result[0]['cancreateprojects']
response['isSuperUser'] = result[0]['issuperuser']
response['isAdmin'] = result[0]['isadmin']
response['admittedUntil'] = result[0]['admitted_until']
response['blockedUntil'] = result[0]['blocked_until']
return response
def getLoginData(self, username, sessionToken):
'''
Performs a lookup on the login timestamp dict.
If the username cannot be found (also not in the database),
they are not logged in (False returned).
If the difference between the current time and the recorded
login timestamp exceeds a pre-defined threshold, the user is
removed from the dict and False is returned.
Otherwise returns True if and only if 'sessionToken' matches
the entry in the database.
'''
if self._check_logged_in(username, sessionToken):
# still logged in; extend session
sessionToken, now, expires = self._init_or_extend_session(
username, sessionToken)
return sessionToken, now, expires
else:
# not logged in or error
raise Exception('Not logged in.')
def getUserPermissions(self, project, username):
'''
Returns the user-to-project relation (e.g., if user is admin).
'''
response = {
'demoMode': False,
'isAdmin': False,
'admittedUntil': None,
'blockedUntil': None
}
try:
# demo mode
response['demoMode'] = checkDemoMode(project, self.dbConnector)
# rest
queryStr = sql.SQL(
'SELECT * FROM {id_auth} WHERE project = %s AND username = %s'
).format(id_auth=sql.Identifier('aide_admin', 'authentication'))
result = self.dbConnector.execute(queryStr, (
project,
username,
), 1)
if len(result):
response['isAdmin'] = result[0]['isadmin']
response['admittedUntil'] = result[0]['admitted_until']
response['blockedUntil'] = result[0]['blocked_until']
finally:
return response
def login(self, username, password, sessionToken):
# check if logged in
if self._check_logged_in(username, sessionToken):
# still logged in; extend session
sessionToken, now, expires = self._init_or_extend_session(
username, sessionToken)
return sessionToken, now, expires
# get user info
userData = self.dbConnector.execute(
'SELECT hash FROM aide_admin.user WHERE name = %s;', (username, ),
numReturn=1)
if len(userData) == 0:
# account does not exist
raise InvalidRequestException()
userData = userData[0]
# verify provided password
if self._check_password(password.encode('utf8'),
bytes(userData['hash'])):
# correct
sessionToken, timestamp, expires = self._init_or_extend_session(
username, None)
return sessionToken, timestamp, expires
else:
# incorrect
self._invalidate_session(username)
raise InvalidPasswordException()
def logout(self, username, sessionToken):
# check if logged in first
if self._check_logged_in(username, sessionToken):
self._invalidate_session(username)
def accountExists(self, username, email):
return self._check_account_exists(username, email)
def createAccount(self, username, password, email):
accExstChck = self._check_account_exists(username, email)
if accExstChck['username'] or accExstChck['email']:
raise AccountExistsException(username)
else:
hash = self._create_hash(password.encode('utf8'))
queryStr = '''
INSERT INTO aide_admin.user (name, email, hash)
VALUES (%s, %s, %s);
'''
self.dbConnector.execute(queryStr, (
username,
email,
hash,
),
numReturn=None)
sessionToken, timestamp, expires = self._init_or_extend_session(
username)
return sessionToken, timestamp, expires
def getUserNames(self, project=None):
if not project:
queryStr = 'SELECT name FROM aide_admin.user'
queryVals = None
else:
queryStr = 'SELECT username AS name FROM aide_admin.authentication WHERE project = %s'
queryVals = (project, )
result = self.dbConnector.execute(queryStr, queryVals, 'all')
response = [r['name'] for r in result]
return response
def setPassword(self, username, password):
hashVal = self._create_hash(password.encode('utf8'))
queryStr = '''
UPDATE aide_admin.user
SET hash = %s
WHERE name = %s;
SELECT hash
FROM aide_admin.user
WHERE name = %s;
'''
result = self.dbConnector.execute(queryStr,
(hashVal, username, username), 1)
if len(result):
return {'success': True}
else:
return {
'success': False,
'message': f'User with name "{username}" does not exist.'
}
