def update_family_model(family_id, people):
# Updating family model
clear_directory(settings.FACE_RECOG_TRAIN_TEMP_DIR)
# Getting Face Models for family
face_model = FaceModel.objects.filter(family_id=family_id).first()
if not face_model:
# No face model, create new one
process_family(family_id)
else:
X = pickle.loads(face_model.fit_data_faces)
y = pickle.loads(face_model.fit_data_person_ids)
files = []
for person in people:
if person.large_thumbnail:
file = download_file(settings.FACE_RECOG_TRAIN_TEMP_DIR,
person.large_thumbnail)
files.append(file)
process_file(file, X, y, person.id)
if len(files) > 0:
face_model.update_knn_classifier(X, y)
def update_family_model(family_id, people):
# Getting Face Models for family
face_model = FaceModel.objects.filter(family_id=family_id).first()
if face_model is None:
# No face model, create new one
process_family(family_id)
else:
X = pickle.loads(face_model.fit_data_faces)
y = pickle.loads(face_model.fit_data_person_ids)
index_removed = False
# Removing people from face models
for person in people:
person_id = person['person_id']
while person_id in y:
index = y.index(person_id)
y.pop(index)
X.pop(index)
index_removed = True
if index_removed:
face_model.update_knn_classifier(X, y)
def update_family_model(family_id, tags):
clear_directory(settings.FACE_RECOG_TRAIN_TEMP_DIR)
# Getting Face Models for family
face_model = FaceModel.objects.filter(family_id=family_id).first()
if not face_model:
# No face model, create new one
process_family(family_id)
else:
X = pickle.loads(face_model.fit_data_faces)
y = pickle.loads(face_model.fit_data_person_ids)
files = []
for tag in tags:
if tag.image.large_thumbnail:
file = get_file_for_tag(tag, tag.image,
settings.FACE_RECOG_TRAIN_TEMP_DIR)
files.append(file)
process_file(file, X, y, tag.person_id)
if len(files) > 0:
face_model.update_knn_classifier(X, y)
def handle(self, *args, **options):
print('===Rebuilding Facial Models===')
for family in Family.objects.all():
print('')
print('Building: {0}'.format(family.description))
process_family(family.id)
def test_process_family(self):
path = settings.MEDIA_ROOT + 'profile_photos/large_test_image1.jpg'
shutil.copy2(self.test_image, path)
self.person.set_profile_image_crop_rotate_resize(
path, 1, 1, 1200, 1700, 0, True)
self.person.save()
process_family(self.family.id)
self.person.remove_local_images()
self.person.remove_remote_images()
face_model = FaceModel.objects.get(family_id=self.family.id)
self.assertTrue(self.person.id in face_model.fit_data_person_ids)
self.assertIsNotNone(face_model.trained_knn_model)
def setUp(self):
'''
Need to create a family and a gallery
'''
self.family = Family()
self.family.save()
self.gallery = Gallery.objects.create(title="test_gallery",
family_id=self.family.id)
clear_directory(settings.FACE_RECOG_TRAIN_TEST_DIR)
self.test_image = os.path.join(
settings.BASE_DIR, 'facial_recognition/tests/test_image_woman.jpg')
self.test_image_destination = ''.join([
settings.MEDIA_ROOT, 'galleries/',
str(self.family.id), '/',
str(self.gallery.id), '/test_image.jpg'
])
self.test_image_s3_key = ''.join([
'galleries/',
str(self.family.id), '/',
str(self.gallery.id), '/test_image.jpg'
])
directory = ''.join([
settings.MEDIA_ROOT, 'galleries/',
str(self.family.id), '/',
str(self.gallery.id)
])
if not os.path.exists(directory):
os.makedirs(directory)
#Copy test image to media area
shutil.copy2(self.test_image, self.test_image_destination)
self.image = Image(gallery=self.gallery,
family=self.family,
original_image=''.join([
'galleries/',
str(self.family.id), '/',
str(self.gallery.id), '/test_image.jpg'
]))
self.image.save()
self.image.upload_files_to_s3()
self.person = Person(name='Wallace',
gender='M',
email='*****@*****.**',
family_id=self.family.id,
language='en')
self.person.save()
self.tag = Tag.objects.create(image_id=self.image.id,
x1=0.279,
y1=0.188,
x2=0.536,
y2=0.381,
person_id=self.person.id,
face_detected=True)
# Upload new image
self.test_image2 = os.path.join(
settings.BASE_DIR,
'facial_recognition/tests/test_image_woman_and_baby.jpg')
self.test_image2_image_destination = ''.join([
settings.MEDIA_ROOT, 'galleries/',
str(self.family.id), '/',
str(self.gallery.id), '/test_image_woman_and_baby.jpg'
])
# Copy to test area
shutil.copy2(self.test_image2, self.test_image2_image_destination)
self.image2 = Image(gallery=self.gallery,
family=self.family,
original_image=''.join([
'galleries/',
str(self.family.id), '/',
str(self.gallery.id),
'/test_image_woman_and_baby.jpg'
]))
self.image2.save()
self.image2.upload_files_to_s3()
self.person2 = Person(name='Gromit',
gender='M',
email='*****@*****.**',
family_id=self.family.id,
language='en')
self.person2.save()
self.tag2 = Tag.objects.create(image_id=self.image2.id,
x1=0.312,
y1=0.239,
x2=0.732,
y2=0.811,
person_id=self.person2.id,
face_detected=True)
# Create a trained model
process_family(self.family.id)