def get_models():
model_path = 'face_sdk/models'
# face detection model setting.
scene = 'non-mask'
model_category = 'face_detection'
model_name = model_conf[scene][model_category]
logger.info('Start to load the face detection model...')
try:
faceDetModelLoader = FaceDetModelLoader(model_path, model_category,
model_name)
model, cfg = faceDetModelLoader.load_model()
faceDetModelHandler = FaceDetModelHandler(model, 'cuda:0', cfg)
except Exception as e:
logger.error('Falied to load face detection Model.')
logger.error(e)
sys.exit(-1)
else:
logger.info('Success!')
# face landmark model setting.
model_category = 'face_alignment'
model_name = model_conf[scene][model_category]
logger.info('Start to load the face landmark model...')
try:
faceAlignModelLoader = FaceAlignModelLoader(model_path, model_category,
model_name)
model, cfg = faceAlignModelLoader.load_model()
faceAlignModelHandler = FaceAlignModelHandler(model, 'cuda:0', cfg)
except Exception as e:
logger.error('Failed to load face landmark model.')
logger.error(e)
sys.exit(-1)
else:
logger.info('Success!')
# face recognition model setting.
model_category = 'face_recognition'
model_name = model_conf[scene][model_category]
logger.info('Start to load the face recognition model...')
try:
faceRecModelLoader = FaceRecModelLoader(model_path, model_category,
model_name)
model, cfg = faceRecModelLoader.load_model()
faceRecModelHandler = FaceRecModelHandler(model, 'cuda:0', cfg)
except Exception as e:
logger.error('Failed to load face recognition model.')
logger.error(e)
sys.exit(-1)
else:
logger.info('Success!')
face_cropper = FaceRecImageCropper()
return faceDetModelHandler, faceAlignModelHandler, faceRecModelHandler, face_cropper
sys.exit(-1)
else:
logger.info(
'Successfully parsed the model configuration file model_meta.json!'
)
try:
model, cfg = faceAlignModelLoader.load_model()
except Exception as e:
logger.error('Model loading failed!')
logger.error(e)
sys.exit(-1)
else:
logger.info('Successfully loaded the face landmark model!')
faceAlignModelHandler = FaceAlignModelHandler(model, 'cuda:0', cfg)
# read image
image_path = 'api_usage/test_images/test1.jpg'
image_det_txt_path = 'api_usage/test_images/test1_detect_res.txt'
image = cv2.imread(image_path, cv2.IMREAD_COLOR)
with open(image_det_txt_path, 'r') as f:
lines = f.readlines()
try:
for i, line in enumerate(lines):
line = line.strip().split()
det = np.asarray(list(map(int, line[0:4])), dtype=np.int32)
landmarks = faceAlignModelHandler.inference_on_image(image, det)
save_path_img = 'api_usage/temp/test1_' + 'landmark_res' + str(
i) + '.jpg'