Rather than applying a single action at a time pychubby enables piping multiple actions together. To achieve this one can use the metaaction Pipeline.
Let us again assume that we start with an image with a single face in it.
Let's try to make the person smile but also close her eyes slightly.
import matplotlib.pyplot as plt
from pychubby.actions import OpenEyes, Pipeline, Smile
from pychubby.detect import LandmarkFace
img = plt.imread("path/to/the/image")
lf = LandmarkFace.estimate(img)
a_s = Smile(0.1)
a_e = OpenEyes(-0.03)
a = Pipeline([a_s, a_e])
new_lf, df = a.perform(lf)
new_lf.plot(show_landmarks=False)
To create an animation we can use the visualize module.
from pychubby.visualize import create_animation
ani = create_animation(df, img)