def test_face_landmarks_small_model(self):
img = api.load_image_file(os.path.join(os.path.dirname(__file__), 'test_images', 'obama.jpg'))
face_landmarks = api.face_landmarks(img, model="small")
self.assertEqual(
set(face_landmarks[0].keys()),
set(['nose_tip', 'left_eye', 'right_eye']))
self.assertEqual(face_landmarks[0]['nose_tip'], [(496, 295)])
def test_face_landmarks_small_model(self):
img = api.load_image_file(os.path.join(os.path.dirname(__file__), 'test_images', 'obama.jpg'))
face_landmarks = api.face_landmarks(img, model="small")
self.assertEqual(
set(face_landmarks[0].keys()),
set(['nose_tip', 'left_eye', 'right_eye']))
self.assertEqual(face_landmarks[0]['nose_tip'], [(496, 295)])
def test_face_landmarks(self):
img = api.load_image_file(os.path.join(os.path.dirname(__file__), 'test_images', 'obama.jpg'))
face_landmarks = api.face_landmarks(img)
self.assertEqual(
set(face_landmarks[0].keys()),
set(['chin', 'left_eyebrow', 'right_eyebrow', 'nose_bridge',
'nose_tip', 'left_eye', 'right_eye', 'top_lip',
'bottom_lip']))
self.assertEqual(
face_landmarks[0]['chin'],
[(369, 220), (372, 254), (378, 289), (384, 322), (395, 353),
(414, 382), (437, 407), (464, 424), (495, 428), (527, 420),
(552, 399), (576, 372), (594, 344), (604, 314)])
def test_face_landmarks(self):
img = api.load_image_file(os.path.join(os.path.dirname(__file__), 'test_images', 'obama.jpg'))
face_landmarks = api.face_landmarks(img)
self.assertEqual(
set(face_landmarks[0].keys()),
set(['chin', 'left_eyebrow', 'right_eyebrow', 'nose_bridge',
'nose_tip', 'left_eye', 'right_eye', 'top_lip',
'bottom_lip']))
self.assertEqual(
face_landmarks[0]['chin'],
[(369, 220), (372, 254), (378, 289), (384, 322), (395, 353),
(414, 382), (437, 407), (464, 424), (495, 428), (527, 420),
(552, 399), (576, 372), (594, 344), (604, 314), (610, 282),
(613, 250), (615, 219)])
def save_keypoints_image(image_path, input_folder, output_folder, model):
image = face_recognition.load_image_file(image_path)
locations = face_recognition.face_locations(image, model=model)
landmarks = face_recognition.face_landmarks(image,
face_locations=locations,
return_dict=False)
num_faces = landmarks.shape[0]
if num_faces == 0:
return
out_path = move_path(image_path, input_folder, output_folder)
out_path = out_path.with_suffix('')
out_path.mkdir(parents=True, exist_ok=True)
for face_idx in range(num_faces):
file_path = Path(out_path, F"{face_idx}.npy")
landmark_array = landmarks[face_idx]
np.save(file_path, landmark_array)
print(F"finished image {out_path}")
def test_face_landmarks(self):
img = api.load_image_file(os.path.join(os.path.dirname(__file__), "test_images", "obama.jpg"))
face_landmarks = api.face_landmarks(img)
assert set(face_landmarks[0].keys()) == set(['chin', 'left_eyebrow', 'right_eyebrow', 'nose_bridge', 'nose_tip', 'left_eye', 'right_eye', 'top_lip', 'bottom_lip'])
assert face_landmarks[0]['chin'] == [(369, 220), (372, 254), (378, 289), (384, 322), (395, 353), (414, 382), (437, 407), (464, 424), (495, 428), (527, 420), (552, 399), (576, 372), (594, 344), (604, 314)]
