How did model.txt come about

[kay2019-art]

    def solve(self, points):
        """Solve pose with all the 68 image points
        Args:
            points (np.ndarray): points on image.

        Returns:
            Tuple: (rotation_vector, translation_vector) as pose.
        """

        if self.r_vec is None:
            (_, rotation_vector, translation_vector) = cv2.solvePnP(
                self.model_points_68, points, self.camera_matrix, self.dist_coeefs)
            self.r_vec = rotation_vector
            self.t_vec = translation_vector

        (_, rotation_vector, translation_vector) = cv2.solvePnP(
            self.model_points_68,
            points,
            self.camera_matrix,
            self.dist_coeefs,
            rvec=self.r_vec,
            tvec=self.t_vec,
            useExtrinsicGuess=True)

        return (rotation_vector, translation_vector)

model_points_68 is obtained by importing model.txt, and points are obtained by detecting key points. May I ask how this model.txt is obtained

[yinguobing]

head-pose-estimation/README.md

Line 98 in e0c3770

The 3D face model is from OpenFace, you can find the original file [here](https://github.com/TadasBaltrusaitis/OpenFace/blob/master/lib/local/LandmarkDetector/model/pdms/In-the-wild_aligned_PDM_68.txt).