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# 3rd party dependencies
import cv2
import matplotlib.pyplot as plt
# project dependencies
from deepface.modules import streaming
from deepface import DeepFace
img_path = "dataset/img1.jpg"
img = cv2.imread(img_path)
overlay_img_path = "dataset/img6.jpg"
face_objs = DeepFace.extract_faces(overlay_img_path)
overlay_img = face_objs[0]["face"][:, :, ::-1] * 255
overlay_img = cv2.resize(overlay_img, (112, 112))
raw_img = img.copy()
demographies = DeepFace.analyze(img_path=img_path, actions=("age", "gender", "emotion"))
demography = demographies[0]
x = demography["region"]["x"]
y = demography["region"]["y"]
w = demography["region"]["w"]
h = demography["region"]["h"]
img = streaming.highlight_facial_areas(img=img, faces_coordinates=[(x, y, w, h)])
img = streaming.overlay_emotion(
img=img,
emotion_probas=demography["emotion"],
x=x,
y=y,
w=w,
h=h,
)
img = streaming.overlay_age_gender(
img=img,
apparent_age=demography["age"],
gender=demography["dominant_gender"][0:1],
x=x,
y=y,
w=w,
h=h,
)
img = streaming.overlay_identified_face(
img=img,
target_img=overlay_img,
label="angelina",
x=x,
y=y,
w=w,
h=h,
)
plt.imshow(img[:, :, ::-1])
plt.show()
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