| | import os |
| | import mediapipe as mp |
| |
|
| | from mediapipe.tasks import python |
| | from mediapipe.tasks.python import vision |
| | from . import face_landmark |
| |
|
| | CUR_DIR = os.path.dirname(__file__) |
| |
|
| | class LMKExtractor(): |
| | def __init__(self): |
| | |
| | self.mode = mp.tasks.vision.FaceDetectorOptions.running_mode.IMAGE |
| | base_options = python.BaseOptions(model_asset_path=os.path.join(CUR_DIR, 'mp_models','face_landmarker_v2_with_blendshapes.task')) |
| | base_options.delegate = mp.tasks.BaseOptions.Delegate.CPU |
| | options = vision.FaceLandmarkerOptions(base_options=base_options, |
| | running_mode=self.mode, |
| | output_face_blendshapes=False, |
| | output_facial_transformation_matrixes=True, |
| | num_faces=1, |
| | min_face_detection_confidence=0.5, |
| | min_face_presence_confidence=0.5, |
| | min_tracking_confidence=0.5) |
| | self.detector = face_landmark.FaceLandmarker.create_from_options(options) |
| |
|
| | det_base_options = python.BaseOptions(model_asset_path=os.path.join(CUR_DIR, 'mp_models','blaze_face_short_range.tflite')) |
| | det_options = vision.FaceDetectorOptions(base_options=det_base_options) |
| | self.det_detector = vision.FaceDetector.create_from_options(det_options) |
| | |
| | def __call__(self, img): |
| | image = mp.Image(image_format=mp.ImageFormat.SRGB, data=img) |
| | try: |
| | detection_result, _ = self.detector.detect(image) |
| | except: |
| | return None |
| | |
| | return detection_result.face_landmarks |
| | |
