def test_load_image_exception(self):
# Cloud not read exception
with self.assertRaises(ValueError):
image = facecrop.load_image(image_path='./sample/99999.jpeg')
# Image dimension exceeded limit exception
with self.assertRaises(ValueError):
image = facecrop.load_image(image_path='./sample/IMG_0102.JPG')
def test_get_largest_face(self):
# Should return largest cropped face (numpy.ndarray)
image = facecrop.load_image(image_path='./sample/2.jpg')
lg_face, bound = facecrop.get_largest_face(
image=image, faces=facecrop.detect_face(image))
self.assertIsInstance(lg_face, numpy.ndarray)
# Compare if it is the same largest face
mssim = compare_image(lg_face, cv2.imread('./tests/asset/2.jpg'))
self.assertGreaterEqual(mssim, .9)
def test_detect_face_exception(self):
# No face detected exception
with self.assertRaises(ValueError):
faces = facecrop.detect_face(image=facecrop.load_image(
image_path='./sample/blank.jpg'))
def test_detect_face(self):
# Should return faces (dlib.rectangles)
faces = facecrop.detect_face(image=facecrop.load_image(
image_path='./sample/0.jpg'))
self.assertIsInstance(faces, dlib.rectangles)
def test_load_image(self):
# Should return image (numpy.ndarray)
image = facecrop.load_image(image_path='./sample/0.jpg')
self.assertIsInstance(image, numpy.ndarray)