From eafae796c23183ad365dfd86f37180b30c303339 Mon Sep 17 00:00:00 2001 From: hesuicong Date: Thu, 16 Apr 2026 09:16:33 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=A0=E9=99=A4=E4=BF=9D=E7=95=99=E7=9A=84?= =?UTF-8?q?=E5=87=BD=E6=95=B0=EF=BC=8C=E7=AE=80=E5=8C=96?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- libs/MVS/mask_face_occlusion.py | 146 -------------------------------- 1 file changed, 146 deletions(-) diff --git a/libs/MVS/mask_face_occlusion.py b/libs/MVS/mask_face_occlusion.py index 09fcfeb..e830053 100755 --- a/libs/MVS/mask_face_occlusion.py +++ b/libs/MVS/mask_face_occlusion.py @@ -1928,64 +1928,6 @@ class ModelProcessor: depth = render.render_to_depth_image(z_in_view_space=True) return np.asarray(depth) - def sort_vertices(vertices_original): - return sorted( - (v for v in vertices_original), - key=lambda v: (v.co.x, v.co.y, v.co.z) - ) - - def _flag_model(self, camera_data, face_points): - """标记可见顶点""" - vertex_visible = [] - vertex_occlusion = [] - depth_images = [] - - render = o3d.visualization.rendering.OffscreenRenderer(camera_data['width'], camera_data['height']) - - material = o3d.visualization.rendering.MaterialRecord() - render.scene.add_geometry("mesh", self.mesh, material) - - # 生成深度图 - depth_image = self._gen_depth_image(camera_data, render) - - # 计算可见性 - R = self.qvec2rotmat(camera_data['qvec']).T - eye = -R @ camera_data['tvec'] - # eye = camera_data['tvec'] - # final_visible_list, final_occlusion_list, final_vertex_difference_list = self._compute_vertex_in_frustum( - final_visible_list, final_occlusion_list = self._compute_vertex_in_frustum( - camera_data['fx'], camera_data['fy'], - camera_data['cx'], camera_data['cy'], - R, eye, - camera_data['height'], camera_data['width'], - depth_image,camera_data['qvec'], camera_data['tvec'] - ) - print("_flag_model", len(final_occlusion_list), len(self.mesh.vertices), len(self.mesh.vertex_colors)) - - # 获取三角形面片数组 - triangles = np.asarray(self.mesh.triangles) - - face_visible_bitmap = np.zeros(len(triangles), dtype=bool) - - # 遍历所有面片 - for face_idx, face in enumerate(triangles): - v0, v1, v2 = face - - face_visible_bitmap[face_idx] = any([ # any all - final_visible_list[v0], - final_visible_list[v1], - final_visible_list[v2] - ]) - - shrunk_visibility = self._shrink_face_visibility(face_visible_bitmap, 6) # 6 10 - - expanded_visibility = self._expand_face_visibility(face_visible_bitmap, 30) - shrunk_visibility2 = self._shrink_face_visibility(face_visible_bitmap, 50) - expanded_edge = expanded_visibility & ~shrunk_visibility2 - delete_edge = face_visible_bitmap & ~shrunk_visibility - - return shrunk_visibility, expanded_edge, delete_edge - def _flag_contour(self, camera_data, face_points): """标记可见顶点""" vertex_visible = [] @@ -2075,94 +2017,6 @@ class ModelProcessor: face_visible_bitmap = np.ones(len(triangles), dtype=bool) # 临时填充 return face_visible_bitmap, face_edge - """ - def _mask_face_occlusion(self): - # 读取相机数据 - cameras = read_cameras_text(os.path.join(self.pose_path, "cameras.txt")) - images = read_images_text(os.path.join(self.pose_path, "images.txt")) - # cameras = read_cameras_text(os.path.join(self.pose_path, "backup_cameras.txt")) - # images = read_images_text(os.path.join(self.pose_path, "backup_images.txt")) - - face_points_sorted_path = os.path.join(self.pose_path, "face_points_sorted.txt") - print("face_points_sorted_path=", face_points_sorted_path) - #face_points = read_int_text(face_points_sorted_path) - face_points = read_indices_from_file(face_points_sorted_path) - # face_points = {} - camera_data = {} - - for img in images.values(): - if self.mask_image == img.name[:-4]: - camera = cameras[img.camera_id] - camera_data = { - "qvec": img.qvec, - "tvec": img.tvec, - "fx": camera.params[0], - "fy": camera.params[1], - "cx": camera.params[2], - "cy": camera.params[3], - "width": camera.width, - "height": camera.height, - "name": img.name[:-4] - } - - # print(face_points) - self._flag_model(camera_data, face_points) - """ - - def _mask_occlusion(self): - # 读取相机数据 - cameras = read_cameras_text(os.path.join(self.pose_path, "cameras.txt")) - images = read_images_text(os.path.join(self.pose_path, "images.txt")) - - camera_data = {} - - countour_faces_dict = {} - visible_faces_dict = {} - edge_faces_dict = {} - delete_edge_faces_dict = {} - - total_start = time.time() - - n = 0 - for img in images.values(): - camera = cameras[img.camera_id] - camera_data = { - "qvec": img.qvec, - "tvec": img.tvec, - "fx": camera.params[0], - "fy": camera.params[1], - "cx": camera.params[2], - "cy": camera.params[3], - "width": camera.width, - "height": camera.height, - "name": img.name[:-4] - } - img_name = img.name[:-4] - # if (img_name!="73_8" and img_name!="52_8" and img_name!="62_8"): - # if (img_name!="52_8" and img_name!="62_8"): - # if (img_name!="52_8"): - # continue - - start_time = time.time() - face_visibility, face_edge, face_delete_edge = self._flag_model(camera_data, None) - processing_time = time.time() - start_time - - visible_faces = np.where(face_visibility)[0].tolist() - visible_faces_dict[img.name[:-4]] = visible_faces - edge_faces_dict[img.name[:-4]] = np.where(face_edge)[0].tolist() - delete_edge_faces_dict[img.name[:-4]] = np.where(face_delete_edge)[0].tolist() - n += 1 - - print(f"图像={img_name}，耗时={processing_time:.2f}秒，可见面数={len(visible_faces)}") - - total_time = time.time() - total_start - print(f"所有图像处理完成，总耗时: {total_time:.2f}秒") - print(f"平均每张图像耗时: {total_time/len(images):.2f}秒") - - self.save_occlusion_data(visible_faces_dict, edge_faces_dict, delete_edge_faces_dict, self.asset_dir) - - return {"result1": visible_faces_dict, "result2": edge_faces_dict, "result3": delete_edge_faces_dict} - def save_occlusion_data(self, result1: Dict[str, List[int]], result2: Dict[str, List[int]], result3: Dict[str, List[int]],