def test_wrong_n_of_action(self, random_lf):
lfs = LandmarkFaces(random_lf, random_lf, random_lf)
a = Multiple([Smile(), Smile()])
with pytest.raises(ValueError):
a.perform(lfs)
def test_simple(self, random_lf, scale):
a = Smile(scale)
new_lf, df = a.perform(random_lf)
if scale == 0:
assert np.allclose(df.delta_x, np.zeros_like(df.delta_x))
assert np.allclose(df.delta_y, np.zeros_like(df.delta_y))
else:
assert not np.allclose(df.delta_x, np.zeros_like(df.delta_x))
assert not np.allclose(df.delta_y, np.zeros_like(df.delta_y))
def smile(img):
img_path = img
img = cv2.imread(img_path)
img8 = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
lf = LandmarkFace.estimate(img8)
from pychubby.actions import Smile
a = Smile(scale=0.2)
new_lf, df = a.perform(lf)
ani = create_animation(df, img)
plt.imsave('output_image.gif', ani)
plt.show()
def test_lf_to_lfs_casting(self, random_lf):
a = Multiple(Smile())
new_lfs, df = a.perform(random_lf)
assert isinstance(new_lfs, LandmarkFaces)
assert isinstance(df, DisplacementField)
def test_wrong_constructor(self):
with pytest.raises(TypeError):
Multiple([Smile(), 'WRONG'])
with pytest.raises(TypeError):
Multiple('WRONG')
def test_overall(self, random_lf):
steps = [Smile(), Chubbify()]
a = Pipeline(steps)
new_lf, df = a.perform(random_lf)
assert df.is_valid
class TestMultiple:
"""Collection of tests focused on the ``Multiple`` action."""
@pytest.mark.parametrize('per_face_action',
[Smile(), [Smile(), Smile()]],
ids=['single', 'many'])
def test_overall(self, random_lf, per_face_action):
lf_1 = random_lf
lf_2 = LandmarkFace(random_lf.points + np.random.random((68, 2)),
random_lf.img)
lfs = LandmarkFaces(lf_1, lf_2)
a = Multiple(per_face_action)
new_lfs, df = a.perform(lfs)
assert isinstance(new_lfs, LandmarkFaces)
assert isinstance(df, DisplacementField)
assert len(lfs) == len(new_lfs)
def test_wrong_n_of_action(self, random_lf):
lfs = LandmarkFaces(random_lf, random_lf, random_lf)
a = Multiple([Smile(), Smile()])
with pytest.raises(ValueError):
a.perform(lfs)
def test_wrong_constructor(self):
with pytest.raises(TypeError):
Multiple([Smile(), 'WRONG'])
with pytest.raises(TypeError):
Multiple('WRONG')
def test_lf_to_lfs_casting(self, random_lf):
a = Multiple(Smile())
new_lfs, df = a.perform(random_lf)
assert isinstance(new_lfs, LandmarkFaces)
assert isinstance(df, DisplacementField)
def photo():
img = request.args.get('photob62')
imgdata = base64.b64decode(img)
img = cv2.imread(io.BytesIO(base64.b64decode(imgdata)))
img = cv2.imread(img)
img8 = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
lf = LandmarkFace.estimate(img8)
from pychubby.actions import Smile, OpenEyes, Multiple, RaiseEyebrow, StretchNostrils, AbsoluteMove
smile = Smile(scale=0.2)
new_lf, df = smile.perform(lf) # lf defined above
# new_lf.plot(show_landmarks=False)
plt.imsave('output_image.png', new_lf.img)
import base64
encoded = base64.b64encode(open("output_image.png", "rb").read())
return encoded
cv2.putText(image, "Face #{}".format(i + 1), (x - 10, y - 10),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
# loop over the (x, y)-coordinates for the facial landmarks
# and draw them on the image
for (x, y) in shape:
cv2.circle(image, (x, y), 2, (0, 0, 255, 255), -1)
cv2.circle(blank_image, (x, y), 2, (0, 0, 255, 0), -1)
cv2.imshow('Video', blank_image)
cv2.imshow('video1', image)
# img = frame
print(frame.shape)
try:
lf = LandmarkFace.estimate(img)
a_per_face = Pipeline([Smile()])
a_all = Multiple(a_per_face)
new_lf, _ = a_all.perform(lf)
new_img = new_lf
#new_lf.plot(figsize=(5, 5), show_numbers=False)
except:
pass
# data = np.fromstring(new_lf, dtype=np.uint8, sep='')
# cv2.imshow('video', data)
cam.send(blank_image)
cam.sleep_until_next_frame()
if cv2.waitKey(1) & 0xFF == ord('q'):
break