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import os
import cv2
import dlib
try:
import urllib.request as request_file
except BaseException:
import urllib as request_file
from ..core import FaceDetector
from ...utils import appdata_dir
class DlibDetector(FaceDetector):
def __init__(self, device, path_to_detector=None, verbose=False):
super().__init__(device, verbose)
print('Warning: this detector is deprecated. Please use a different one, i.e.: S3FD.')
base_path = os.path.join(appdata_dir('face_alignment'), "data")
# Initialise the face detector
if 'cuda' in device:
if path_to_detector is None:
path_to_detector = os.path.join(
base_path, "mmod_human_face_detector.dat")
if not os.path.isfile(path_to_detector):
print("Downloading the face detection CNN. Please wait...")
path_to_temp_detector = os.path.join(
base_path, "mmod_human_face_detector.dat.download")
if os.path.isfile(path_to_temp_detector):
os.remove(os.path.join(path_to_temp_detector))
request_file.urlretrieve(
"https://www.adrianbulat.com/downloads/dlib/mmod_human_face_detector.dat",
os.path.join(path_to_temp_detector))
os.rename(os.path.join(path_to_temp_detector), os.path.join(path_to_detector))
self.face_detector = dlib.cnn_face_detection_model_v1(path_to_detector)
else:
self.face_detector = dlib.get_frontal_face_detector()
def detect_from_image(self, tensor_or_path):
image = self.tensor_or_path_to_ndarray(tensor_or_path, rgb=False)
detected_faces = self.face_detector(cv2.cvtColor(image, cv2.COLOR_BGR2GRAY))
if 'cuda' not in self.device:
detected_faces = [[d.left(), d.top(), d.right(), d.bottom()] for d in detected_faces]
else:
detected_faces = [[d.rect.left(), d.rect.top(), d.rect.right(), d.rect.bottom()] for d in detected_faces]
return detected_faces
@property
def reference_scale(self):
return 195
@property
def reference_x_shift(self):
return 0
@property
def reference_y_shift(self):
return 0
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