def handleObject(self):
from photonix.classifiers.object import ObjectModel, run_on_photo
print('Loading object classification model')
model = ObjectModel()
threaded_queue_processor = ThreadedQueueProcessor(
model, 'classify.object', run_on_photo, num_workers, batch_size)
threaded_queue_processor.run(loop=False)
def handleLocaltion(self):
from photonix.classifiers.location import LocationModel, run_on_photo
print('Loading object location model')
model = LocationModel()
threaded_queue_processor = ThreadedQueueProcessor(
model, 'classify.location', run_on_photo, num_workers, batch_size)
threaded_queue_processor.run(loop=False)
def test_classifier_batch(photo_fixture_snow):
photo = PhotoFactory()
PhotoFileFactory(photo=photo)
for i in range(4):
TaskFactory(subject_id=photo.id)
start = time()
threaded_queue_processor = ThreadedQueueProcessor(model, 'classify.style', run_on_photo, 1, 64)
threaded_queue_processor.run(loop=False)
assert time() - start > 0
assert time() - start < 100
assert photo.photo_tags.count() == 1
assert photo.photo_tags.all()[0].tag.name == 'serene'
assert photo.photo_tags.all()[0].confidence > 0.9
def run_processors(self):
num_workers = 4
batch_size = 64
threaded_queue_processor = ThreadedQueueProcessor(
model, 'classify.style', run_on_photo, num_workers, batch_size)
threaded_queue_processor.run()