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import logging
import cv2 as cv
import numpy as np
import dlib
from typing import Optional
logging.basicConfig(level=logging.INFO)
class FaceGrabber:
def __init__(self):
self.cascades = [
"haarcascade_frontalface_default.xml",
"haarcascade_frontalface_alt.xml",
"haarcascade_frontalface_alt2.xml",
"haarcascade_frontalface_alt_tree.xml"
]
self.detector = dlib.get_frontal_face_detector() # load face detector
self.predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks_GTX.dat") # load face predictor
self.mmod = dlib.cnn_face_detection_model_v1("mmod_human_face_detector.dat") # load face detector
self.paddingBy = 0.1 # padding by 10%
def grab_faces(self, img: np.ndarray, bGray: bool = False) -> Optional[np.ndarray]:
if bGray:
img = cv.cvtColor(img, cv.COLOR_BGR2GRAY) # convert to grayscale
detected = None
if detected is None:
faces = self.detector(img) # detect faces
if len(faces) > 0:
detected = faces[0]
detected = (detected.left(), detected.top(), detected.width(), detected.height())
logging.info("Face detected by dlib")
if detected is None:
faces = self.mmod(img)
if len(faces) > 0:
detected = faces[0]
detected = (detected.rect.left(), detected.rect.top(), detected.rect.width(), detected.rect.height())
logging.info("Face detected by mmod")
if detected is None:
for cascade in self.cascades:
cascadeClassifier = cv.CascadeClassifier(cv.data.haarcascades + cascade)
faces = cascadeClassifier.detectMultiScale(img, scaleFactor=1.5, minNeighbors=5) # detect faces
if len(faces) > 0:
detected = faces[0]
logging.info(f"Face detected by {cascade}")
break
if detected is not None: # if face detected
x, y, w, h = detected # grab first face
padW = int(self.paddingBy * w) # get padding width
padH = int(self.paddingBy * h) # get padding height
imgH, imgW, _ = img.shape # get image dims
x = max(0, x - padW)
y = max(0, y - padH)
w = min(imgW - x, w + 2 * padW)
h = min(imgH - y, h + 2 * padH)
x = max(0, x - (w - detected[2]) // 2) # center the face horizontally
y = max(0, y - (h - detected[3]) // 2) # center the face vertically
face = img[y:y+h, x:x+w] # crop face
return face
return None |