# we need to convert rot to SECOND format. gt_boxes = np.concatenate([locs, dims, -rots - np.pi / 2], axis=1) assert len(gt_boxes) == len( annotations), f'{len(gt_boxes)}, {len(annotations)}' info['gt_boxes'] = gt_boxes info['gt_names'] = names info['gt_velocity']...
self.pred_boxes.sample_tokens = 914,self.gt_boxes.sample_tokens = 6019 真实值包括整个数据集,但我仅使用了part1数据集. 2. 代码修改: 文件:/home/ch511/anaconda3/envs/open-mmlab/lib/python3.7/site-packages/nuscenes/eval/common/loaders.py函数:load_gt sample_tokens_all = [s['token'] for s...
self._add_instance( ret, gt_det, k, cls_id, bbox, bbox_amodal, ann, trans_output, aug_s, calib, pre_cts, track_ids) if self.opt.debug > 0 or self.enable_meta: gt_det = self._format_gt_det(gt_det) meta = {'c': c, 's': s, 'gt_det': gt_det, 'img_id': img_...
boxes = info['gt_boxes'][mask] names = info['gt_names'][mask] objects = [] for name, box in zip(names, boxes): objects.append(Object3d(name, box)) return objects def get_split(self, split): return NuSceneSplit(self, split=split) def get_split_list(self, split): if split in...
# visualize.pyimportcopyimportosfromtypingimportList,Optional,Tupleimportcv2importmmcvimportnumpyasnpfrommatplotlibimportpyplotaspltfrommmdet3d.core.bboximportLiDARInstance3DBoxes__all__=["visualize_camera","visualize_lidar","visualize_map"]OBJECT_PALETTE={"car":(255,158,0),"truck":(255,99,71),"...
Hi, In nuSences the lidar coordinate is ( up z y front ^ ^ | / | / 0 ---> x), but the gt_bbox_3d in nuscenes_dataset not change to the LiDARInstance3DBoxes coordinate( up z x front ^ ^ | / | / left y <--- 0) 👀1 Activity ...
return_past_2d_disp_gt: bool = False, return_instance_map: bool = False)` 1. 2. 3. 4. 5. 6. 参数: data_dict: 数据信息字典 grid_size: 网格尺寸 extents: ROI范围 frame_skip: 需要过滤的帧数 reordered: 是否需要对结果重新排序,保证第一要素对应过去的记录。该选项只对返回值return_past_2d...
'instance_boxes_19804c352c0a4767b61b8d0709d1db99' = {ndarray:(50,10)} # 实例1, 含有前后50帧,每个实例box含有10个维度:中心、长宽高、四元数 'category_b61b72a5b5ad482e9bc94c203f75b8d4' = {int} 2 'instance_boxes_b61b72a5b5ad482e9bc94c203f75b8d4' = {ndarray:(50,10)} ...
在他们的官方简介里,他说他们纯手工臻选了1000个scenes,每个scene有20s的数据,包含23个object classes,3D bounding boxes为2Hz,2*20*1000=40k个关键帧。传感器为6 cameras, 1 LIDAR, 5 RADAR, GPS, IMU。lidarseg会对每个关键帧的所有lidar点标记label(32种)。 下面这个传感器布置图对于SLAM领域的大佬们,尤其是...
I'm having the following error: AssertionError: Samples in split don't match samples in predicted tracks. Can anyone please explain why this happens? What's samples in split?