def __init__(self, device, path_to_detector=None, verbose=False):
super(SFDDetector, self).__init__(device, verbose)
base_path = os.path.join(appdata_dir("face_alignment"), "data")
// Initialise the face detector
if path_to_detector is None:
path_to_detector = os.path.join(
base_path, "s3fd_convert.pth")
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, "s3fd_convert.pth.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/python-fan/s3fd_convert.pth",
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 = s3fd()
self.face_detector.load_state_dict(torch.load(path_to_detector))
self.face_detector.to(device)
self.face_detector.eval()
After Change
// Initialise the face detector
if path_to_detector is None:
model_weights = load_url(models_urls["s3fd"])
else:
model_weights = torch.load(path_to_detector)
