Hi.

I found that the training process will randomly crashed with RuntimeError: DataLoader worker (pid(s) 36469) exited unexpectedly, is that normal?

I use the following training command.

python tracking/train.py --script stark_s --config baseline_got10k_only --save_dir . --mode multiple --nproc_per_node 8

thanks!

When I train ‘st’ model，I found the 'net_type' is ''STARKS'',but the checkpoint_dict['net_type'] is ''LittleBoy_clean_corner'', so assert net_type == checkpoint_dict['net_type'], 'Network is not of correct type.'It's always wrong.

How can I solve this problem?Thanks！

run: python tracking/video_demo.py stark_s baseline test_video/demo.mp4

cuda10.2:

NVIDIA GeForce RTX 3060 Laptop GPU with CUDA capability sm_86 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_61 sm_70 sm_75 compute_37.
If you want to use the NVIDIA GeForce RTX 3060 Laptop GPU GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
  warnings.warn(incompatible_device_warn.format(device_name, capability, " ".join(arch_list), device_name))

cuda11.0:

WARNING: You are using tensorboardX instead sis you have a too old pytorch version.
Traceback (most recent call last):
  File "tracking/../lib/train/admin/tensorboard.py", line 4, in <module>
    from torch.utils.tensorboard import SummaryWriter
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 189, in <module>
    _load_global_deps()
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 142, in _load_global_deps
    ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL)
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/ctypes/__init__.py", line 348, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: /home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/lib/../../../../libcublas.so.11: symbol free_gemm_select version libcublasLt.so.11 not defined in file libcublasLt.so.11 with link time reference

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tracking/video_demo.py", line 9, in <module>
    from lib.test.evaluation import Tracker
  File "tracking/../lib/test/evaluation/__init__.py", line 1, in <module>
    from .data import Sequence
  File "tracking/../lib/test/evaluation/data.py", line 3, in <module>
    from lib.train.data.image_loader import imread_indexed
  File "tracking/../lib/train/__init__.py", line 1, in <module>
    from .admin.multigpu import MultiGPU
  File "tracking/../lib/train/admin/__init__.py", line 3, in <module>
    from .tensorboard import TensorboardWriter
  File "tracking/../lib/train/admin/tensorboard.py", line 7, in <module>
    from tensorboardX import SummaryWriter
ModuleNotFoundError: No module named 'tensorboardX'

but when i installed tensorboardX:

WARNING: You are using tensorboardX instead sis you have a too old pytorch version.
Traceback (most recent call last):
  File "tracking/../lib/train/admin/tensorboard.py", line 4, in <module>
    from torch.utils.tensorboard import SummaryWriter
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 189, in <module>
    _load_global_deps()
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 142, in _load_global_deps
    ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL)
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/ctypes/__init__.py", line 348, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: /home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/lib/../../../../libcublas.so.11: symbol free_gemm_select version libcublasLt.so.11 not defined in file libcublasLt.so.11 with link time reference

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "tracking/video_demo.py", line 9, in <module>
    from lib.test.evaluation import Tracker
  File "tracking/../lib/test/evaluation/__init__.py", line 1, in <module>
    from .data import Sequence
  File "tracking/../lib/test/evaluation/data.py", line 3, in <module>
    from lib.train.data.image_loader import imread_indexed
  File "tracking/../lib/train/__init__.py", line 1, in <module>
    from .admin.multigpu import MultiGPU
  File "tracking/../lib/train/admin/__init__.py", line 3, in <module>
    from .tensorboard import TensorboardWriter
  File "tracking/../lib/train/admin/tensorboard.py", line 7, in <module>
    from tensorboardX import SummaryWriter
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/tensorboardX/__init__.py", line 5, in <module>
    from .torchvis import TorchVis
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/tensorboardX/torchvis.py", line 11, in <module>
    from .writer import SummaryWriter
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/tensorboardX/writer.py", line 34, in <module>
    import torch
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 189, in <module>
    _load_global_deps()
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/__init__.py", line 142, in _load_global_deps
    ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL)
  File "/home/richard/miniconda3/envs/torch1.7/lib/python3.6/ctypes/__init__.py", line 348, in __init__
    self._handle = _dlopen(self._name, mode)
OSError: /home/richard/miniconda3/envs/torch1.7/lib/python3.6/site-packages/torch/lib/../../../../libcublas.so.11: symbol free_gemm_select version libcublasLt.so.11 not defined in file libcublasLt.so.11 with link time reference

Hi, Thanks for your wonderful work. I notice that Transformer Tracking use the model trained with all datasets(LaSOT, GOT10K, COCO, TrackingNet) to get the evaluation result on GOT-10k test set, and the result is much better than the model trained with GOT10K only.

However, when I use the STARK-S50 pre-trained model(trained on all datasets) in your model zoo to evaluate the GOT-10k test set, I find that the AO is 0.688, which only gains small improvement compared with 0.672

I am confused with this phenomenon. Have you ever tried to evaluate the model trained with all datasets on GOT-10k test set? Or can you kindly explain the reason why there is just little performance gain to use the model trained on all datasets?

Thanks for your work! I trained the model and want to evaluate it on the GOT10k-Val dataset to see its performance, but only see 'LaSOT', 'otb', 'nfs', 'uav', 'tc128ce' datasets, so how to evaluate on the GOT10k-Val? By the way, what's the difference between analysis_results and analysis_results_ITP files?

It seems that STARK doesn't mention anything about a dynamically updated template (DUT for short) during training procedure, is it a deliberate design or am I missing something?

I reckon that the DUT is actually something like a short-term memory, and it should not be treated equally as a normal template from the first frame by the transformer, so the DUT should be explicitly included in training. However, this is not how STARK has been implemented.

So I'm curious what's the intuition or reasoning behind STARK's current training protocol of dismissing the DUT?

Hi, thanks for your work. I find from your codes that "shuffle = True" when setting dataloaders. So if the input data is not sequential, how to update template every 200 frames? thanks!

hi,

I run several times about vot (python version), but still got the problem: from lib.test.vot20.stark_vot20 import run_vot_exp ModuleNotFoundError: No module named 'lib'

It seems not finding the stark project path, though I export it as: export PYTHONPATH=/home/xxxx/projects/transformer/Stark-main:$PYTHONPATH.

Expected to solve it by inspiring from any of your answers.

Thanks!

Hi! Could you please tell what is the meaning of "lmdb" in class EnvironmentSettings "self.lasot_lmdb_dir"? I guess it is the dir of val dataset of lasot?

Hi, thanks for your work! There is a parameter making me confused. I don't find the definition of params in class STARK_ST and could you please tell me? Thanks!

Thanks for sharing! I have some questions around the choice of template. From the paper you cropped 2^2 times the ground truth bounding box, rather than just the actual target bounding box resized to square image. My questions are:

1. Is the purpose here to include more surrounding information? If so what would be the optimal template size here? Also a factor of 2 would not always include the whole tracking object if aspect ratio is high.
2. By not specifying the bounding box exactly I assume the transformer has to learn some segmentation capability? For instance right now I noticed that if you change the template crop size (output size stay the same) a little bit during the inference time, the model would give very poor performance. So it seems that some information sensitive to absolute positions are learned in this setting. Would passing the exact coordinates into the transformer help in any way?

Hi guys, according to the readme, I should create a folder called data, just under the root stark folder. This folder should contain different datasets: lasot, got10k, coco and trackingnet.

How can I add all this datasets to that data folder?

Hi guys, I'm trying to run this tracker but it is throwing the error:

FileNotFoundError: [Errno 2] No such file or directory: '/home/salva/submit_STARK_LT-code/checkpoints/train/stark_ref/baseline/STARKST_ep0500.pth.tar'

I cannot find STARKST_ep0500.pth.tar in the links provided in the modelzoo, so, how can I solve this error?

Thanks in advance.

Hi! the checkpoint file of stark-st1 link has expired(https://drive.google.com/file/d/1HswUW0oHKjiTL9xR7d2WNW9QOLE040vS/view?usp=sharing), can you re-upload the model of the first stage（ (baseline / baseline_got10k_only / baseline_R101 / baseline_R101_got10k_only) ）, and then give a new link, thank you very much, or send me an email：[email protected], thank you again!

Have you tried to use Alpha-Refine for evaluation on datasets such as GOT-1OK and TrackingNet? If you have tried, can you provide this part of the code? Thanks.