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_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)
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:
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)
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)
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)
