def _received_existing_images(self, message: Message):
self.outbox_queue.put(
Message(ProcessManager.OutboxTypes.EXISTING_IMAGES, content=message.content)
)
self.to_image_crawler_queue.put(
Message(
Crawler.InboxTypes.SET_EXISTING_IMAGES,
content=[image.path for image in message.content]
)
)
self._send_images_for_analysis(message.content)
self._send_faces_for_analysis(message.content)
def _handle_message(self, message):
if message.descriptor == ImageStore.InboxTypes.GET_EXISTING_IMAGES:
images = [
Image.from_datamodel(image)
for image in self.ImageTable.get_all_images()
]
return Message(ImageStore.OutboxTypes.EXISTING_IMAGES,
content=images)
elif message.descriptor == ImageStore.InboxTypes.ADD_NEW_IMAGES:
return Message(ImageStore.OutboxTypes.ADDED_IMAGES,
content=self._add_images(message.content))
elif message.descriptor == ImageStore.InboxTypes.UPDATE_METADATA:
return Message(ImageStore.OutboxTypes.UPDATED_METADATA,
self._update_metadata(message.content))
return None
def _handle_message(self, message):
if message.descriptor == ImageAnalyzer.InboxTypes.ANALYZE_NEW_IMAGES:
images = message.content
for image in images:
# send one by one because processing is slow
self.outbox_queue.put(
Message(ImageAnalyzer.OutboxTypes.UPDATE_METADATA,
content=self.image_analysis([image])))
elif message.descriptor == ImageAnalyzer.InboxTypes.ANALYZE_FACES:
faces = message.content
for face in faces:
# send one by one because processing is slow
self.outbox_queue.put(
Message(ImageAnalyzer.OutboxTypes.FACES_IDENTIFIED,
content=self.face_analysis([face])))
def _send_images_for_analysis(self, images: List[Image]):
not_analyzed = [
image for image in images if image.faces_detected is False or image.tags_detected is False
]
if len(not_analyzed) > 0:
self.to_image_analyzer_queue.put(
Message(ImageAnalyzer.InboxTypes.ANALYZE_NEW_IMAGES, content=not_analyzed)
)
def _send_faces_for_analysis(self, images: List[Image]):
faces_for_analysis = []
for image in images:
for face in image.faces:
# id is assigned after face was written to the database
if face.recognized is False and face.id is not None:
faces_for_analysis.append(face)
if len(faces_for_analysis) > 0:
self.to_image_analyzer_queue.put(
Message(ImageAnalyzer.InboxTypes.ANALYZE_FACES, content=faces_for_analysis)
)
def find_in_dirs(self, dirs, recursive=True):
"""
Finds untracked or changed files having extension listed in __extensions__ tuple in the given directories;
Puts them into __new_images_queue__
:param dirs: folder to search in (string)
:param recursive: search recursively on the folder (boolean)
"""
for dir in dirs:
self.__find_in_dir__(dir=dir, recursive=recursive)
if len(self.__new_images_queue__) > 0:
self.outbox_queue.put(
Message(Crawler.OutboxTypes.DISCOVERED_IMAGES,
content=self.__new_images_queue__))
self.__new_images_queue__ = []
def _init_process_manager(self):
"""
Start image store main loop in a separate process.
:return:
"""
self.to_process_manager = Queue()
self.from_process_manager = Queue()
self.process_manager_proc = Process(target=start_worker,
args=(ProcessManager, self.config,
self.to_process_manager,
self.from_process_manager))
self.process_manager_proc.start()
self.to_process_manager.put(
Message(ProcessManager.InboxTypes.GET_EXISTING_IMAGES,
content=None))
def _set_new_metadata(self, message: Message):
self.to_image_store_queue.put(
Message(ImageStore.InboxTypes.UPDATE_METADATA, message.content)
)
def _request_existing_images(self, message: Message):
self.to_image_store_queue.put(
Message(ImageStore.InboxTypes.GET_EXISTING_IMAGES, content=None)
)
def _received_discovered_images(self, message: Message):
self.to_image_store_queue.put(
Message(ImageStore.InboxTypes.ADD_NEW_IMAGES, content=message.content)
)
def _received_images_added_to_image_store(self, message: Message):
self.outbox_queue.put(
Message(ProcessManager.OutboxTypes.ADDED_IMAGES, content=message.content)
)
self._send_images_for_analysis(message.content)
def _send_updates_to_app(self, message: Message):
self.outbox_queue.put(Message(
ProcessManager.OutboxTypes.UPDATED_METADATA,
message.content
))
self._send_faces_for_analysis(message.content)