# get image to process
image = queue.pop_from_queue()
if not image:
time.sleep(0.25)
continue
logger.info('recieved image=%s', image)
image_content = get_image_content(image)
logger.info('getting tags for image=%s', image)
tags = tagging.get_tags(image_binary=image_content)
if config.get('translation', 'enabled') == 'true':
logger.info('translating tags for image=%s', image)
translated_tags = translater.translate_tags(target=config.get(
'translation', 'target'),
tags=tags)
# Prepare ElasticSearch Document
doc['image_type'] = os.path.splitext(image)[1]
doc['image_fname'] = os.path.basename(image)
doc['image_path'] = image
doc['uploaded_at'] = datetime.datetime.fromtimestamp(
int(os.path.getmtime(image))).strftime('%Y-%m-%d %H:%M:%S')
doc['timestamp'] = int(time.time())
doc['en_lables'] = tags
if translated_tags:
target_lang = config.get('translation', 'target')
doc['%s_lables' % target_lang] = translated_tags
logger.info('pusing all details to elasticsearch for image=%s', image)
if not es_engine.push_to_es(doc=doc):
queue.add_to_queue(queue_name='failed_queue', image=image)
new_linked_list.remove_from_list("Ron")
new_linked_list.print_list()
new_linked_list.find_element("Anna")
print("\n---------------------- Queue -------------------------------")
name = "Mary"
phone = "1-890-562"
person = NodeQ(name, phone)
queue = Queue()
queue.add_to_queue(person)
queue.print_queue()
persons = ("John", "1-675-657"), ("Ron", "1-908-089"), ("Anna", "1-987-987")
queue = [NodeQ(name, phone) for name, phone in persons]
new_queue = Queue()
for person in queue:
new_queue.add_to_queue(person)
new_queue.print_queue()
print("Queue size is {}".format(new_queue.get_size()))
