Method forward

wan/models/face_model.py:339–476

(self, src_image, reset=False, pre_rect=None)

        self.trackingFaces = []

    def forward(self, src_image, reset=False, pre_rect=None):
        if self.reset or reset:
            self.trackingFaces = []

        if len(self.trackingFaces) == 0:
            if pre_rect is not None:
                detected_faces = [pre_rect]
            else:
                detected_faces, _, _ = self.face_alignment_module.face_detector.detect(
                    src_image
                )
            for face_rect in detected_faces:
                new_tracking_object = {
                    "face_rect": face_rect,
                    "rotate_angle": 0.0,
                    "pre_kpt_222": None,
                    "face_dis": np.sqrt(
                        np.square((face_rect[2] - face_rect[0]))
                        + np.square((face_rect[3] - face_rect[1]))
                    ),
                    "smoother_222": Smoother222(),
                    "prob": 0,
                }
                self.trackingFaces.append(new_tracking_object)
        else:
            detected_faces, _, _ = self.face_alignment_module.face_detector.detect(
                src_image
            )
            for face_rect in detected_faces:
                new_tracking_object = {
                    "face_rect": face_rect,
                    "rotate_angle": 0.0,
                    "pre_kpt_222": None,
                    "face_dis": np.sqrt(
                        np.square((face_rect[2] - face_rect[0]))
                        + np.square((face_rect[3] - face_rect[1]))
                    ),
                    "smoother_222": Smoother222(),
                    "prob": 0,
                }
                self.trackingFaces.append(new_tracking_object)

        delete_idx_list = []
        for face_idx, tracking_face in enumerate(self.trackingFaces):
            if tracking_face["pre_kpt_222"] is not None:
                result_dict = self.face_alignment_module.forward(
                    src_image, pre_pts=tracking_face["pre_kpt_222"], iterations=3
                )
            else:
                result_dict = self.face_alignment_module.forward(
                    src_image, face_box=tracking_face["face_rect"], iterations=3
                )

            if result_dict["prob"] < self.face_prob_th:
                if not face_idx in delete_idx_list:
                    delete_idx_list.append(face_idx)
                continue