def test_recognise_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face recognition on file with no faces %s" % (img_fn,))
result = recognise_face(self.stub, img_fn, bboxes)
# Should still have the right number of responses, even if they are meaningless
#print(np.array([f for f in result.identities[0].identity]))
self.assertEqual(len(result.identities), len(bboxes))
def test_align_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face alignment on file with no faces %s" %
(img_fn, ))
result = align_face(self.stub, img_fn, source_bboxes=bboxes)
# Should still have the right number of responses, even if they are meaningless
self.assertEqual(len(result), len(bboxes))
render_face_alignment_debug_image(self, img_fn, result)
def test_get_landmarks_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face detect on file with no faces %s" % (img_fn,))
result = get_face_landmarks(self.stub, img_fn, bboxes, model=self.algorithm)
# Should still have the right number of responses, even if they are meaningless
self.assertEqual(len(result.landmarked_faces), len(bboxes))
for i in range(0, len(bboxes)):
self.assertEqual(len(result.landmarked_faces[i].point), int(self.algorithm))
render_face_landmarks_debug_image(self, img_fn, result)
def test_recognise_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face recognition on file with no faces %s" %
(img_fn, ))
boxes = [BoundingBox(**b) for b in bboxes]
header = FaceRecognitionHeader(faces=boxes)
with open(img_fn, 'rb') as infile:
chunk = infile.read()
request = FaceRecognitionRequest(
header=header, image_chunk=ImageRGB(content=chunk))
result = self.stub.RecogniseFace(request)
# Should still have the right number of responses, even if they are meaningless
# print(np.array([f for f in result.identities[0].identity]))
self.assertEqual(len(result.identities), len(bboxes))
def test_align_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face alignment on file with no faces %s" %
(img_fn, ))
boxes = [BoundingBox(**b) for b in bboxes]
header = FaceAlignmentHeader(source_bboxes=boxes)
with open(img_fn, 'rb') as infile:
chunk = infile.read()
request = FaceAlignmentRequest(
header=header, image_chunk=ImageRGB(content=chunk))
result = self.stub.AlignFace(request)
images = []
for i in result.image_chunk:
images.append(bytes(i.content))
# Should still have the right number of responses, even if they are meaningless
self.assertEqual(len(images), len(bboxes))
def test_get_landmarks_no_faces(self):
for img_fn in no_faces:
# When there is no face, then this checks things don't explode when we give it a face bbox with no face
bboxes = list(pre_calculated_faces.values())[0]
logging.debug("Testing face detect on file with no faces %s" %
(img_fn, ))
boxes = [BoundingBox(**b) for b in bboxes]
header = FaceLandmarkHeader(
landmark_model=self.algorithm,
faces=FaceDetections(face_bbox=boxes))
with open(img_fn, 'rb') as infile:
chunk = infile.read()
request = FaceLandmarkRequest(
header=header, image_chunk=ImageRGB(content=chunk))
result = self.stub.GetLandmarks(request)
# Should still have the right number of responses, even if they are meaningless
self.assertEqual(len(result.landmarked_faces), len(bboxes))
for i in range(0, len(bboxes)):
self.assertEqual(len(result.landmarked_faces[i].point),
int(self.algorithm))