def test_jaanet():
# AU Detection Case:
detector1 = Detector(
face_model="RetinaFace",
emotion_model=None,
landmark_model="MobileFaceNet",
au_model="jaanet",
)
bboxes = detector1.detect_faces(img01)
lands = detector1.detect_landmarks(img01, bboxes)
aus = detector1.detect_aus(img01, lands)
assert np.sum(np.isnan(aus)) == 0
assert aus.shape[-1] == 12
def test_drml():
# AU Detection Case2:
inputFname = os.path.join(get_test_data_path(), "sampler0000.jpg")
img01 = cv2.imread(inputFname)
detector1 = Detector(
face_model="RetinaFace",
emotion_model=None,
landmark_model="MobileFaceNet",
au_model="drml",
)
bboxes = detector1.detect_faces(img01)
lands = detector1.detect_landmarks(img01, bboxes)
aus = detector1.detect_aus(img01, lands)
assert np.sum(np.isnan(aus)) == 0
assert aus.shape[-1] == 12
def test_svm():
# AU Detection Case:
detector1 = Detector(
face_model="RetinaFace",
emotion_model=None,
landmark_model="MobileFaceNet",
au_model="svm",
)
detected_faces = detector1.detect_faces(img01)
landmarks = detector1.detect_landmarks(img01, detected_faces)
hogs, new_lands = detector1._batch_hog(frames=img01,
detected_faces=detected_faces,
landmarks=landmarks)
aus = detector1.detect_aus(frame=hogs, landmarks=new_lands)
assert np.sum(np.isnan(aus)) == 0
assert aus.shape[-1] == 20
def test_rf():
# AU Detection Case:
detector1 = Detector(
face_model="RetinaFace",
emotion_model=None,
landmark_model="MobileFaceNet",
au_model="RF",
)
bboxes = detector1.detect_faces(img01)
lands = detector1.detect_landmarks(img01, bboxes)
convex_hull, new_lands = detector1.extract_face(
frame=img01,
detected_faces=[bboxes[0:4]],
landmarks=lands,
size_output=112)
hogs = detector1.extract_hog(frame=convex_hull, visualize=False)
aus = detector1.detect_aus(frame=hogs, landmarks=new_lands)
assert np.sum(np.isnan(aus)) == 0
assert aus.shape[-1] == 20