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from typing import List
import numpy as np
from retinaface import RetinaFace as rf
from deepface.models.Detector import Detector, FacialAreaRegion
# pylint: disable=too-few-public-methods
class RetinaFaceClient(Detector):
def __init__(self):
self.model = rf.build_model()
def detect_faces(self, img: np.ndarray) -> List[FacialAreaRegion]:
"""
Detect and align face with retinaface
Args:
img (np.ndarray): pre-loaded image as numpy array
Returns:
results (List[FacialAreaRegion]): A list of FacialAreaRegion objects
"""
resp = []
obj = rf.detect_faces(img, model=self.model, threshold=0.9)
if not isinstance(obj, dict):
return resp
for face_idx in obj.keys():
identity = obj[face_idx]
detection = identity["facial_area"]
y = detection[1]
h = detection[3] - y
x = detection[0]
w = detection[2] - x
# retinaface sets left and right eyes with respect to the person
left_eye = identity["landmarks"]["left_eye"]
right_eye = identity["landmarks"]["right_eye"]
# eyes are list of float, need to cast them tuple of int
left_eye = tuple(int(i) for i in left_eye)
right_eye = tuple(int(i) for i in right_eye)
confidence = identity["score"]
facial_area = FacialAreaRegion(
x=x,
y=y,
w=w,
h=h,
left_eye=left_eye,
right_eye=right_eye,
confidence=confidence,
)
resp.append(facial_area)
return resp
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