您好，我在kitti-split1上用单卡进行训练，batch_size=4，在val的3694张图上测试：

[2021-06-17 06:25:15,960] monoflex.inference INFO: metric = R40
[2021-06-17 06:25:15,961] monoflex.inference INFO:
Car [email protected], 0.70, 0.70:
bbox AP:93.1365, 88.1290, 80.6364
bev  AP:27.4066, 19.9626, 16.8124
3d   AP:19.3602, 13.9580, 11.9678
aos  AP:93.01, 87.77, 79.92
Car [email protected], 0.50, 0.50:
bbox AP:93.1365, 88.1290, 80.6364
bev  AP:61.1731, 45.9274, 40.7388
3d   AP:55.3238, 41.9672, 35.9666
aos  AP:93.01, 87.77, 79.92
Pedestrian [email protected], 0.50, 0.50:
bbox AP:52.8775, 44.4330, 37.8220
bev  AP:6.5744, 5.0258, 4.0656
3d   AP:5.9074, 4.2190, 3.2233
aos  AP:46.37, 38.43, 32.49
Pedestrian [email protected], 0.25, 0.25:
bbox AP:52.8775, 44.4330, 37.8220
bev  AP:21.2798, 17.0815, 13.9071
3d   AP:20.5831, 16.5574, 13.3822
aos  AP:46.37, 38.43, 32.49
Cyclist [email protected], 0.50, 0.50:
bbox AP:55.2721, 36.1850, 33.6507
bev  AP:1.5678, 0.8645, 0.7968
3d   AP:1.2153, 0.3637, 0.3799
aos  AP:47.42, 30.75, 28.57
Cyclist [email protected], 0.25, 0.25:
bbox AP:55.2721, 36.1850, 33.6507
bev  AP:11.4607, 5.7936, 5.4553
3d   AP:10.6146, 5.3862, 4.8811
aos  AP:47.42, 30.75, 28.57

[2021-06-17 06:25:16,132] monoflex.trainer INFO: Total training time: 21:24:51.903272 (0.8307 s / it), best model is achieved at iteration = 91872

低于论文中Table1的val ap3d_r40,：23.64 17.51 14.83，相差4个点左右。请问是我哪里设置的不对吗？谢谢

What can I do for it? I use 4 gpus to train data with arg"--num_gpus=4",and it can train and val,but one hours later,error occured: `Traceback (most recent call last): File "tools/plain_train_net.py", line 161, in args=(args,), File "/zft/code/MonoFlex/engine/launch.py", line 54, in launch daemon=False, File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 199, in spawn return start_processes(fn, args, nprocs, join, daemon, start_method='spawn') File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 157, in start_processes while not context.join(): File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 118, in join raise Exception(msg) Exception:

-- Process 1 terminated with the following error: Traceback (most recent call last): File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/multiprocessing/spawn.py", line 19, in _wrap fn(i, *args) File "/zft/code/MonoFlex/engine/launch.py", line 89, in _distributed_worker main_func(*args) File "/zft/code/MonoFlex/tools/plain_train_net.py", line 140, in main train(cfg, model, device, distributed) File "/zft/code/MonoFlex/tools/plain_train_net.py", line 84, in train arguments, File "/zft/code/MonoFlex/engine/trainer.py", line 109, in do_train loss_dict, log_loss_dict = model(images, targets) File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 619, in forward output = self.module(*inputs[0], **kwargs[0]) File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/zft/code/MonoFlex/model/detector.py", line 34, in forward loss_dict, log_loss_dict = self.heads(features, targets) File "/root/anaconda3/envs/monoflex/lib/python3.7/site-packages/torch/nn/modules/module.py", line 727, in _call_impl result = self.forward(*input, **kwargs) File "/zft/code/MonoFlex/model/head/detector_head.py", line 21, in forward loss_dict, log_loss_dict = self.loss_evaluator(x, targets) File "/zft/code/MonoFlex/model/head/detector_loss.py", line 271, in call pred_targets, preds, reg_nums, weights = self.prepare_predictions(targets_variables, predictions) File "/zft/code/MonoFlex/model/head/detector_loss.py", line 153, in prepare_predictions target_corners_3D = self.anno_encoder.encode_box3d(target_rotys_3D, target_dimensions_3D, target_locations_3D) File "/zft/code/MonoFlex/model/anno_encoder.py", line 108, in encode_box3d ry = self.rad_to_matrix(rotys, N) File "/zft/code/MonoFlex/model/anno_encoder.py", line 60, in rad_to_matrix ry = i_temp.repeat(N, 1).view(N, -1, 3) RuntimeError: cannot reshape tensor of 0 elements into shape [0, -1, 3] because the unspecified dimension size -1 can be any value and is ambiguous`

Hello , I see you use gradient clipping in training code, I wonder if it's necessary ? and the gradient will be vanishing if without gradient clipping ?

Hello, when reading the tag data, if I change the filter conditions of the instance level, does it mean that the distance of the model I trained focus is different, and will the level filtering hyperparameter affect the evaluation process?

sys: ubuntu 20.04 GPU: GF 1080 driver: NVIDIA-SMI 515.65.01 Driver Version: 515.65.01 CUDA Version: 11.7 cuda: Cuda compilation tools, release 10.1, V10.1.243 python: 3.7.13 haa1d7c7_1 torch: torch 1.7.0+cu110 pypi_0 pypi torchaudio 0.4.0 py37 pytorch torchvision 0.8.1+cu110 pypi_0 pypi cudatoolkit cudatoolkit 10.1.243 h6bb024c_0

https://github.com/zhangyp15/MonoFlex/blob/ec6da017c325451b7d997d89e323083fa8430ada/model/anno_encoder.py#L178

why use f_u to compute the decode the depth instead of f_v here？

The obj height should correspond to the y-axis in the camera coordinate

I have run the official MonoFlex pretrained model and code on kitti test dataset , got below score:

There is a big gap between above score and MonoFlex's official score. So, how can i reproduce the score on kitti test leadboard ? How to generate predictions on kitti test dataset?