def create_apps(book_id):
"""
Celery queued task that creates tt_apps and tt1 tasks
:arg book_id: Internet archive book id
:returns: book indicating if the applications were created
:rtype: bool
"""
try:
imgs = meb_util.get_tt_images(book_id)
bookInfo = meb_util.get_archive_book_data(book_id)
app_tt_select = Apptt_select(short_name=book_id + "_tt1", title=bookInfo['title'], book_info=bookInfo)
app_tt_meta = Apptt_meta(short_name=book_id + "_tt2", title=bookInfo['title'])
app_tt_struct = Apptt_struct(short_name=book_id + "_tt3", title=bookInfo['title'])
app_tt_transcribe = Apptt_transcribe(short_name=book_id + "_tt4", title=bookInfo['title'])
app_tt_select.add_app_infos(bookInfo)
app_tt_meta.add_app_infos(bookInfo)
app_tt_struct.add_app_infos(bookInfo)
app_tt_transcribe.add_app_infos(bookInfo)
if len(app_tt_select.get_tasks()) == 0:
for img in imgs:
task = app_tt_select.add_task(img)
workflow_transaction_info = dict(task_id_1=task.id, task_id_2=None, task_id_3=None, task_id_4=None)
data_mngr.record_workflow_transaction(workflow_transaction_info)
return True
except Exception as e:
return False
def add_next_task(self):
# Get the list of task_runs
task_runs = self.get_task_runs()
task_run = task_runs[-1] # Get only the last answer
answer = task_run.info
answer_info_json = json.loads(answer)
if (answer != "0"): # page don't have table
# record the page tables and its metadata on mbdb
self.__record_page_table_and_metadata(answer_info_json)
if (self.__checkIfNextTaskWasCreated()):
logger.warn(Meb_exception_tt2(6, self.task.id))
raise Meb_exception_tt2(6, self.task.id)
tt3_app_short_name = self.app_short_name[:-1] + "3"
tt3_app = ttapps.Apptt_struct(short_name=tt3_app_short_name)
bookId = self.get_book_id()
imgId = self.task.info["page"]
rotate = answer_info_json[0]["text"]["girar"]
try:
self.__downloadArchiveImages(bookId, imgId)
self.__runLinesRecognition(bookId, imgId, rotate)
# file with the lines recognized
arch = open(
"%s/books/%s/metadados/saida/image%s_model%s.txt" % (
app.config['CV_MODULES'], bookId, imgId, "1"))
# get the lines recognitions
tables_coords = self.__splitFile(arch)
t3_tasks = []
for tableId in range(len(tables_coords)):
self.__runAreaSelection(bookId, imgId, tableId, rotate)
image_pieces = self.__getAreaSelection(bookId, imgId, tableId)
table_subject_code = answer_info_json[tableId]['text']['assunto']
next_task_priority = priority_task_manager.get_priority(table_subject_code)
if (len(image_pieces) > 0):
for image_piece in image_pieces:
info = dict(hasZoom=True, zoom=image_piece,
coords=tables_coords[tableId],
table_id=tableId,
page=imgId, img_url=self.__url_table(
bookId, imgId, tableId))
t3_tasks.append(tt3_app.add_task(info, priority=next_task_priority)) # add task to tt3_backend
else:
info = dict(hasZoom=False,
coords=tables_coords[tableId],
table_id=tableId,
page=imgId, img_url=self.__url_table(
bookId, imgId, tableId))
t3_tasks.append(tt3_app.add_task(info, priority=next_task_priority))
workflow_transaction = data_manager.get_workflow_transaction_by_task_id_2(self.task.id)
workflow_transaction_info = dict(task_id_1=workflow_transaction.task_id_1, task_id_2=workflow_transaction.task_id_2, task_id_3=workflow_transaction.task_id_3, task_id_4=workflow_transaction.task_id_4)
for i in range(0, len(t3_tasks)):
workflow_transaction_info['task_id_3'] = t3_tasks[i].id
if i == 0:
data_manager.update_workflow_transaction_t3(workflow_transaction_info)
else:
data_manager.record_workflow_transaction(workflow_transaction_info)
return True
except Meb_exception_tt2 as e:
raise e
return False
def add_workflow_transaction(info_workflow_transaction):
data_mngr.record_workflow_transaction(info_workflow_transaction)
