def test_remove_face(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
self.test_add_face()
training_set_path = os.path.join(
fm._data_dir_path, c.TRAINING_SET_DIR)
aligned_faces_path = os.path.join(
training_set_path, c.ALIGNED_FACES_DIR)
label = 3812
subject_path = os.path.join(aligned_faces_path, str(label))
im_name = ''
for im in os.listdir(subject_path):
im_name = im
ok = fm.remove_face(label, im_name)
self.assertTrue(ok)
def test_disable_faces(self):
self.test_add_face()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
labels = fm.get_labels()
print('labels', labels)
rel_im_tuples = []
for label in labels:
images = fm.get_images_for_label(label)
print('images', images)
for image in images:
rel_im_tuple = (label, image)
rel_im_tuples.append(rel_im_tuple)
fm.disable_faces(rel_im_tuples)
# Assert that file with enabled models does not exist
db_file_name = os.path.join(fm._data_dir_path, c.ENABLED_FACE_MODELS_FILE)
self.assertFalse(os.path.exists(db_file_name))
def test_prediction(self):
base_path = '..' + os.sep + 'test_files' + os.sep + 'face_models'
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
self.test_add_face()
fm.load_models()
im_path = os.path.join(base_path, '0000000_aligned.png')
face = cv2.imread(im_path, cv2.IMREAD_GRAYSCALE)
(label, conf) = fm.recognize_face(face)
print 'Predicted label = %s (confidence=%.2f)' % (label, conf)
self.assertEquals(label, 3812)
im_path = os.path.join(base_path, '0000002_aligned.png')
face = cv2.imread(im_path, cv2.IMREAD_GRAYSCALE)
(tag, conf) = fm.recognize_face(face)
print 'Predicted tag = %s (confidence=%.2f)' % (tag, conf)
self.assertEquals(tag, 3815)
def test_enable_faces(self):
self.test_disable_faces()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
label = 3812
rel_im_tuples = []
images = fm.get_images_for_label(label)
for image in images:
rel_im_tuple = (label, image)
rel_im_tuples.append(rel_im_tuple)
fm.enable_faces(rel_im_tuples)
# Get labels from all models
labels = fm._models.getMat("labels")
self.assertEqual(len(labels), 6)
# Get labels from enabled models
labels = fm._en_models.getMat("labels")
self.assertEqual(len(labels), 2)
def test_create_models_from_aligned_faces(self):
self.test_create_models_from_whole_images()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
labels = [2000, 2001, 2002, 2003]
fm.create_models_from_aligned_faces(labels)
# Check that directory with aligned faces exists
# and that sub directories have the right name
aligned_faces_path = os.path.join(
fm._data_dir_path, c.TRAINING_SET_DIR, c.ALIGNED_FACES_DIR)
sub_dir_counter = 0
if os.path.exists(aligned_faces_path):
for sub_dir in os.listdir(aligned_faces_path):
self.assertEqual(sub_dir, str(labels[sub_dir_counter]))
sub_dir_counter += 1
def test_recognize_model_internal_models(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(
os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
self.test_add_face()
fm = FaceModels(params)
fm.load_enabled_models()
model_id = 0
im_list = [os.path.join(base_path, '0000000_aligned.png'),
os.path.join(base_path, '0000005_aligned.png')]
model_path_0 = fm.create_model_from_image_list(im_list, model_id)
query_model = cv2.createLBPHFaceRecognizer()
query_model.load(model_path_0)
rec_results = fm.recognize_model(query_model)
print('rec_results', rec_results)
rec_result = rec_results[0]
self.assertEqual(rec_result[c.ASSIGNED_TAG_KEY], 3812)
def test_add_face_from_whole_image(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
label = 0
tag = 'Mameli_Giacomo'
im_path = os.path.join(base_path, '0000000.png')
fm.add_face(label, tag, im_path)
def test_add_blacklist_item(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
item = 'Al_telefono'
fm = FaceModels(params)
fm.add_blacklist_item(item)
blacklist = fm.get_blacklist()
self.assertIn(item, blacklist)
def test_get_tag(self):
self.test_add_face()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.load_models()
tag = fm.get_tag(3812)
self.assertEqual(tag, 'Mameli_Giacomo')
def test_create_models_from_whole_images_and_labels(self):
orig_images_dir_path = os.path.join(
'..', 'test_files', 'face_models', 'Whole images')
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
labels = [1000, 1001, 1002, 1003]
fm.create_models_from_whole_images(orig_images_dir_path, labels)
# Check that all files exist
db_file_name = os.path.join(fm._data_dir_path, c.FACE_MODELS_FILE)
self.assertTrue(os.path.exists(db_file_name))
tag_label_associations_file = os.path.join(
fm._data_dir_path, c.TAG_LABEL_ASSOCIATIONS_FILE)
self.assertTrue(os.path.exists(tag_label_associations_file))
faces_file = os.path.join(fm._data_dir_path, c.FACES_FILE)
self.assertTrue(os.path.exists(faces_file))
aligned_faces_path = os.path.join(
fm._data_dir_path, c.TRAINING_SET_DIR, c.ALIGNED_FACES_DIR)
# Check that directory with aligned faces exists
# and has the right number of sub directories
# and that each sub directory has the right name
sub_dir_counter = 0
if os.path.exists(aligned_faces_path):
for sub_dir in os.listdir(aligned_faces_path):
self.assertEqual(sub_dir, str(labels[sub_dir_counter]))
sub_dir_counter += 1
self.assertEqual(sub_dir_counter, 4)
def test_create_models_from_image_list(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
model_id = 0
im_list = [os.path.join(base_path, '0000000_aligned.png'),
os.path.join(base_path, '0000005_aligned.png')]
model_path_0 = fm.create_model_from_image_list(im_list, model_id)
model_id = 1
im_list = [os.path.join(base_path, '0000001_aligned.png')]
model_path_1 = fm.create_model_from_image_list(im_list, model_id)
model_id = 2
im_list = [os.path.join(base_path, '0000002_aligned.png')]
model_path_2 = fm.create_model_from_image_list(im_list, model_id)
model_id = 3
im_list = [os.path.join(base_path, '0000003_aligned.png'),
os.path.join(base_path, '0000004_aligned.png')]
model_path_3 = fm.create_model_from_image_list(im_list, model_id)
self.assertTrue(os.path.exists(model_path_0))
self.assertTrue(os.path.exists(model_path_1))
self.assertTrue(os.path.exists(model_path_2))
self.assertTrue(os.path.exists(model_path_3))
def test_remove_label_not_removed(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
self.test_add_face()
label = -1
ok = fm.remove_label(label)
self.assertFalse(ok)
def test_cluster(self):
self.test_add_face()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
base_path = os.path.join('..', 'test_files', 'face_models')
label = 3816
tag = 'Mameli_Giacomo-2'
image_path = os.path.join(base_path, '0000000.png')
aligned_image_path = os.path.join(base_path, '0000000_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (303, 131, 352, 134)
bbox = (260, 76, 137, 137)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3817
tag = 'Fadda_Paolo-2'
image_path = os.path.join(base_path, '0000001.png')
aligned_image_path = os.path.join(base_path, '0000001_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (323, 150, 376, 145)
bbox = (267, 87, 166, 166)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
# Get clusters
fm.cluster_models()
clusters = fm.get_clusters()
# Check correctness of clusters
self.assertEqual(len(clusters), 4)
self.assertIn(3816, clusters[0])
def test_delete_model(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
self.test_create_models_from_image_list()
model_id = 0
model_path = os.path.join(
fm._data_dir_path, c.FACE_MODELS_DIR, str(model_id))
fm.delete_model(model_id)
self.assertFalse(os.path.exists(model_path))
def test_change_tag_to_label(self):
self.test_add_face()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
label = 3812
new_tag = 'Giacomo_Mameli'
fm.change_tag_to_label(label, new_tag)
tag = fm.get_tag(label)
self.assertEqual(tag, 'Giacomo_Mameli')
def test_change_label_to_face(self):
self.test_add_face()
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
old_label = 3812
images = fm.get_images_for_label(old_label)
im_name = images[0]
new_label = 3813
fm.change_label_to_face(im_name, old_label, new_label)
images_new_label = fm.get_images_for_label(new_label)
self.assertIn(im_name, images_new_label)
def test_recognize_model_external_models(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(
os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
model_path_0 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '0')
model_path_1 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '1')
model_path_2 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '2')
model_path_3 = os.path.join(face_rec_data, c.FACE_MODELS_DIR, '3')
model_0 = {c.MODEL_ID_KEY: 0,
c.MODEL_FILE_KEY: model_path_0,
c.TAG_KEY: 'Mameli_Giacomo'}
model_1 = {c.MODEL_ID_KEY: 1,
c.MODEL_FILE_KEY: model_path_1,
c.TAG_KEY: 'Fadda_Paolo'}
model_2 = {c.MODEL_ID_KEY: 2,
c.MODEL_FILE_KEY: model_path_2,
c.TAG_KEY: 'Giannotta_Michele'}
model_3 = {c.MODEL_ID_KEY: 3,
c.MODEL_FILE_KEY: model_path_3,
c.TAG_KEY: 'Leoni_Mario'}
fm = FaceModels(params, [model_0, model_1, model_2, model_3])
fm.delete_models()
self.test_create_models_from_image_list()
fm.load_models()
model_id = 0
im_list = [os.path.join(base_path, '0000000_aligned.png'),
os.path.join(base_path, '0000005_aligned.png')]
model_path_0 = fm.create_model_from_image_list(im_list, model_id)
query_model = cv2.createLBPHFaceRecognizer()
query_model.load(model_path_0)
rec_results = fm.recognize_model(query_model)
rec_result = rec_results[0]
self.assertEqual(rec_result[c.ASSIGNED_TAG_KEY], 0)
def test_get_tags(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_MODELS_MIN_DIFF_KEY: -1,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
self.test_add_face()
fm.load_models()
tags = fm.get_tags()
self.assertEquals(len(tags), 4)
def test_add_face(self):
base_path = os.path.join('..', 'test_files', 'face_models')
face_rec_data = os.path.abspath(os.path.join(base_path, 'face_rec_data'))
params = {c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: face_rec_data}
fm = FaceModels(params)
fm.delete_models()
label = 3812
tag = 'Mameli_Giacomo'
image_path = os.path.join(base_path, '0000000.png')
aligned_image_path = os.path.join(base_path, '0000000_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (303, 131, 352, 134)
bbox = (260, 76, 137, 137)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3813
tag = 'Fadda_Paolo'
image_path = os.path.join(base_path, '0000001.png')
aligned_image_path = os.path.join(base_path, '0000001_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (323, 150, 376, 145)
bbox = (267, 87, 166, 166)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3815
tag = 'Giannotta_Michele'
image_path = os.path.join(base_path, '0000002.png')
aligned_image_path = os.path.join(base_path, '0000002_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (337, 190, 393, 183)
bbox = (282, 121, 161, 161)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3814
tag = 'Leoni_Mario'
image_path = os.path.join(base_path, '0000003.png')
aligned_image_path = os.path.join(base_path, '0000003_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (355, 148, 407, 152)
bbox = (300, 89, 156, 156)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3814
tag = 'Leoni_Mario'
image_path = os.path.join(base_path, '0000004.png')
aligned_image_path = os.path.join(base_path, '0000004_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (138, 150, 158, 151)
bbox = (119, 128, 60, 60)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
label = 3812
tag = 'Mameli_Giacomo'
image_path = os.path.join(base_path, '0000005.png')
aligned_image_path = os.path.join(base_path, '0000005_aligned.png')
aligned_face = cv2.imread(aligned_image_path, cv2.IMREAD_GRAYSCALE)
eye_pos = (318, 128, 361, 126)
bbox = (272, 86, 126, 126)
fm.add_face(label, tag, image_path, aligned_face, eye_pos, bbox)
c.OFFSET_PCT_X_KEY: 0.30,
c.OFFSET_PCT_Y_KEY: 0.42,
c.SCALE_FACTOR_KEY: 1.1,
c.MAX_EYE_ANGLE_KEY: 0.125,
c.MIN_EYE_DISTANCE_KEY: 0.25,
c.USE_EYES_POSITION_KEY: True,
c.USE_NOSE_POS_IN_DETECTION_KEY: False,
c.ALIGNED_FACES_PATH_KEY: align_path,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: 'face_rec_data',
c.LBP_GRID_X_KEY: 4,
c.LBP_GRID_Y_KEY: 5,
c.LBP_NEIGHBORS_KEY: 8,
c.LBP_RADIUS_KEY: 1
}
fm = FaceModels(params)
# Delete possible already existing models
fm.delete_models()
# Add face from first image to face models
label = 0
tag = ''
fm.add_face(label, tag, image_path_1)
# Detect face in second image
result = detect_faces_in_image(
image_path_2, align_path, params, show_results=False)
# Recognize aligned face detected in second image
if result and c.FACES_KEY in result:
def main(argv):
# Set path of images to be analyzed
image_path_1 = argv[1]
print "image_path_1 ", image_path_1
image_path_2 = argv[2]
print "image_path_2 ", image_path_2
# Set path of directory where aligned faces will be saved
align_path = '/tmp'
# Set parameters
params = {
c.CHECK_EYE_POSITIONS_KEY: True,
c.CLASSIFIERS_DIR_PATH_KEY: '/home/active/gitactive/ACTIVE/face_extractor/examples/haarcascades',
c.CROPPED_FACE_HEIGHT_KEY: 250,
c.CROPPED_FACE_WIDTH_KEY: 200,
c.EYE_DETECTION_CLASSIFIER_KEY: 'haarcascade_mcs_lefteye.xml',
c.FACE_DETECTION_ALGORITHM_KEY: 'HaarCascadeFrontalFaceAlt2',
c.FLAGS_KEY: 'DoCannyPruning',
c.MIN_NEIGHBORS_KEY: 5,
c.MIN_SIZE_HEIGHT_KEY: 20,
c.MIN_SIZE_WIDTH_KEY: 20,
c.OFFSET_PCT_X_KEY: 0.30,
c.OFFSET_PCT_Y_KEY: 0.42,
c.SCALE_FACTOR_KEY: 1.1,
c.MAX_EYE_ANGLE_KEY: 0.125,
c.MIN_EYE_DISTANCE_KEY: 0.25,
c.USE_EYES_POSITION_KEY: True,
c.USE_NOSE_POS_IN_DETECTION_KEY: False,
c.ALIGNED_FACES_PATH_KEY: align_path,
c.GLOBAL_FACE_REC_DATA_DIR_PATH_KEY: '/home/active/gitactive/ACTIVE/face_extractor/examples/face_rec_data2',
c.LBP_GRID_X_KEY: 4,
c.LBP_GRID_Y_KEY: 5,
c.LBP_NEIGHBORS_KEY: 8,
c.LBP_RADIUS_KEY: 1
}
fm = FaceModels(params)
# Delete possible already existing models
fm.delete_models()
# Add face from first image to face models
label = 0
tag = ''
fm.add_face(label, tag, image_path_1)
# Detect face in second image
result = detect_faces_in_image(
image_path_2, align_path, params, show_results=False)
# Recognize aligned face detected in second image
if result and c.FACES_KEY in result:
faces = result[c.FACES_KEY]
if len(faces) == 1:
# Get aligned face and calculate distance between faces
file_name = faces[0][c.ALIGNED_FACE_FILE_NAME_KEY]
file_name_complete = file_name + '_gray.png'
file_path = os.path.join(align_path, file_name_complete)
aligned_face = cv2.imread(file_path, cv2.IMREAD_GRAYSCALE)
(label, conf) = fm.recognize_face(aligned_face)
# Draw bounding box around face
img = cv2.imread(image_path_2)
(x, y, w, h) = faces[0][c.BBOX_KEY]
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 0, 255), 3, 8, 0)
# Write distance from reference image
cv2.putText(img, str(conf), (x, y + h + 30),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
print "distance ", conf
cv2.imshow('Image', img)
cv2.waitKey(0)
image_path_2 = os.path.splitext(image_path_2)[0]
image_path_2 = image_path_2 + '_comparison.png'
cv2.imwrite(image_path_2, img)
