外参扰动 car_noise2cam = car2cam @ car_noise2car - 惯性聚合

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博客园 - 无左无右

mmdetection3d-1.0.0rc0 安裝左乘和右乘，行向量和列向量 grep -rl "math\.tan" /media/data_1/everyday/2025_down --include="*.py" - 无左无右已知相机到车的rt 4x4矩阵，求pitch和yaw角度 torch.where(condition, x, y) 是一个三元运算符：如果条件为真，取 x 的值；如果条件为假，保持 y（即原本的 weights）不变。 for decoder_idx, (cls, reg) in enumerate(zip(cls_scores, reg_preds)): log_str += ', '.join(log_items) 左乘与右乘 GridMask--随机用“网格状”的遮挡去盖住图片的一部分，迫使模型学习更鲁棒的特征。 obtain_sensor2top函数， sensor → ego_s → global → ego_lidar → lidar assert osp.exists(self.table_root), 'Database version not found: {}'.format(self.table_root) Deformable-DETR 网页绘图，无需注册 value = value.masked_fill(input_padding_mask[..., None], float(0)) DETR 点云绕不同的轴旋转可视化，roll，pitch，yaw 相机坐标系转车辆坐标系以及相反， RT矩阵，旋转变换P_cam = rot_car2cam * P_car + trans_car2cam； P_cam = rot * (P_car - trans) 连续200帧的ego的RT矩阵R_prevel2wld，shape是[200,4,4]，目标的rt矩阵的R_curpt2curvels的shape是[87, 200, 4, 4]， 87是目标数量，把t11时刻的目标对齐到t0， numpy实现 vscode launch.json debug 带caffe库的工程代码标注工具--抹除目标 ubuntu1804安装 mmdet3d 0.17.1 报错与解决 np.stack(a,axis=x)， x=0,1,2 BEVDet-net部分 TP, FP, precision, recall bevdepth- 数据处理部分 ubuntu 硬盘挂载，重启后硬盘掉了 create_frustum 分析（frustum = torch.stack((x_coords, y_coords, d_coords, paddings), -1)） sweep_lidar_depth = sweep_lidar_depth.reshape(batch_size * num_cams, *sweep_lidar_depth.shape[2:]) torch.where(condition, x, y) 自动驾驶，单目3D中的alpha角度

外参扰动 car_noise2cam = car2cam @ car_noise2car

无左无右 · 2025-06-26 · via 博客园 - 无左无右

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