删除保留的函数，简化
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hesuicong committed
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@@ -1928,64 +1928,6 @@ class ModelProcessor:
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depth = render.render_to_depth_image(z_in_view_space=True)
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return np.asarray(depth)
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def sort_vertices(vertices_original):
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return sorted(
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(v for v in vertices_original),
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key=lambda v: (v.co.x, v.co.y, v.co.z)
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)
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def _flag_model(self, camera_data, face_points):
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"""标记可见顶点"""
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vertex_visible = []
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vertex_occlusion = []
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depth_images = []
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render = o3d.visualization.rendering.OffscreenRenderer(camera_data['width'], camera_data['height'])
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material = o3d.visualization.rendering.MaterialRecord()
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render.scene.add_geometry("mesh", self.mesh, material)
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# 生成深度图
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depth_image = self._gen_depth_image(camera_data, render)
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# 计算可见性
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R = self.qvec2rotmat(camera_data['qvec']).T
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eye = -R @ camera_data['tvec']
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# eye = camera_data['tvec']
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# final_visible_list, final_occlusion_list, final_vertex_difference_list = self._compute_vertex_in_frustum(
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final_visible_list, final_occlusion_list = self._compute_vertex_in_frustum(
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camera_data['fx'], camera_data['fy'],
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camera_data['cx'], camera_data['cy'],
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R, eye,
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camera_data['height'], camera_data['width'],
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depth_image,camera_data['qvec'], camera_data['tvec']
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)
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print("_flag_model", len(final_occlusion_list), len(self.mesh.vertices), len(self.mesh.vertex_colors))
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# 获取三角形面片数组
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triangles = np.asarray(self.mesh.triangles)
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face_visible_bitmap = np.zeros(len(triangles), dtype=bool)
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# 遍历所有面片
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for face_idx, face in enumerate(triangles):
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v0, v1, v2 = face
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face_visible_bitmap[face_idx] = any([ # any all
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final_visible_list[v0],
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final_visible_list[v1],
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final_visible_list[v2]
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])
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shrunk_visibility = self._shrink_face_visibility(face_visible_bitmap, 6) # 6 10
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expanded_visibility = self._expand_face_visibility(face_visible_bitmap, 30)
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shrunk_visibility2 = self._shrink_face_visibility(face_visible_bitmap, 50)
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expanded_edge = expanded_visibility & ~shrunk_visibility2
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delete_edge = face_visible_bitmap & ~shrunk_visibility
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return shrunk_visibility, expanded_edge, delete_edge
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def _flag_contour(self, camera_data, face_points):
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"""标记可见顶点"""
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vertex_visible = []
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@@ -2075,94 +2017,6 @@ class ModelProcessor:
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face_visible_bitmap = np.ones(len(triangles), dtype=bool) # 临时填充
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return face_visible_bitmap, face_edge
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"""
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def _mask_face_occlusion(self):
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# 读取相机数据
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cameras = read_cameras_text(os.path.join(self.pose_path, "cameras.txt"))
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images = read_images_text(os.path.join(self.pose_path, "images.txt"))
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# cameras = read_cameras_text(os.path.join(self.pose_path, "backup_cameras.txt"))
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# images = read_images_text(os.path.join(self.pose_path, "backup_images.txt"))
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face_points_sorted_path = os.path.join(self.pose_path, "face_points_sorted.txt")
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print("face_points_sorted_path=", face_points_sorted_path)
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#face_points = read_int_text(face_points_sorted_path)
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face_points = read_indices_from_file(face_points_sorted_path)
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# face_points = {}
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camera_data = {}
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for img in images.values():
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if self.mask_image == img.name[:-4]:
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camera = cameras[img.camera_id]
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camera_data = {
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"qvec": img.qvec,
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"tvec": img.tvec,
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"fx": camera.params[0],
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"fy": camera.params[1],
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"cx": camera.params[2],
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"cy": camera.params[3],
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"width": camera.width,
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"height": camera.height,
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"name": img.name[:-4]
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}
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# print(face_points)
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self._flag_model(camera_data, face_points)
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"""
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def _mask_occlusion(self):
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# 读取相机数据
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cameras = read_cameras_text(os.path.join(self.pose_path, "cameras.txt"))
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images = read_images_text(os.path.join(self.pose_path, "images.txt"))
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camera_data = {}
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countour_faces_dict = {}
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visible_faces_dict = {}
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edge_faces_dict = {}
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delete_edge_faces_dict = {}
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total_start = time.time()
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n = 0
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for img in images.values():
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camera = cameras[img.camera_id]
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camera_data = {
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"qvec": img.qvec,
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"tvec": img.tvec,
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"fx": camera.params[0],
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"fy": camera.params[1],
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"cx": camera.params[2],
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"cy": camera.params[3],
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"width": camera.width,
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"height": camera.height,
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"name": img.name[:-4]
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}
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img_name = img.name[:-4]
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# if (img_name!="73_8" and img_name!="52_8" and img_name!="62_8"):
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# if (img_name!="52_8" and img_name!="62_8"):
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# if (img_name!="52_8"):
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# continue
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start_time = time.time()
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face_visibility, face_edge, face_delete_edge = self._flag_model(camera_data, None)
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processing_time = time.time() - start_time
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visible_faces = np.where(face_visibility)[0].tolist()
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visible_faces_dict[img.name[:-4]] = visible_faces
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edge_faces_dict[img.name[:-4]] = np.where(face_edge)[0].tolist()
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delete_edge_faces_dict[img.name[:-4]] = np.where(face_delete_edge)[0].tolist()
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n += 1
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print(f"图像={img_name}，耗时={processing_time:.2f}秒，可见面数={len(visible_faces)}")
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total_time = time.time() - total_start
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print(f"所有图像处理完成，总耗时: {total_time:.2f}秒")
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print(f"平均每张图像耗时: {total_time/len(images):.2f}秒")
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self.save_occlusion_data(visible_faces_dict, edge_faces_dict, delete_edge_faces_dict, self.asset_dir)
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return {"result1": visible_faces_dict, "result2": edge_faces_dict, "result3": delete_edge_faces_dict}
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def save_occlusion_data(self, result1: Dict[str, List[int]],
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result2: Dict[str, List[int]],
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result3: Dict[str, List[int]],
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