Hi, @GOATmessi7 @yancie-yjr great wokrs. Can you enrich the readme about datasets preparing、how to training & validation and so on. hope to finish it soon. thanks

hi everyone, I got this issue ...File "cfgs/m_s50_onex_dfp_tal_flip.py", line 189, in get_trainer from exps.train_utils.double_trainer import Trainer ModuleNotFoundError: No module named 'exps'

Actually I ran code on local I got this error but when I try "echo export PYTHONPATH=$PYTHONPATH:$ADDPATH >> " it worked. But as you can guess my local GPU didn't enough for training. And I established everything on colab but this time "echo export..." didn't save me.

For Developers

Hi! When reproducing your results on Argoverse-HD, I found that the directory structure you provided in Quick Start - Dataset preparation section doesn't match the original directory structure of Argoverse-HD dataset, as well as your code required. The directory structure in Quick Start - Dataset preparation section:

StreamYOLO
├── exps
├── tools
├── yolox
├── data
│   ├── Argoverse-1.1
│   │   ├── annotations
│   │       ├── tracking
│   │           ├── train
│   │           ├── val
│   │           ├── test
│   ├── Argoverse-HD
│   │   ├── annotations
│   │       ├── test-meta.json
│   │       ├── train.json
│   │       ├── val.json

should be edited as:

StreamYOLO
├── exps
├── tools
├── yolox
├── data
│   ├── Argoverse-1.1
│   │   ├── tracking
│   │       ├── train
│   │       ├── val
│   │       ├── test
│   ├── Argoverse-HD
│   │   ├── annotations
│   │       ├── test-meta.json
│   │       ├── train.json
│   │       ├── val.json

which matches the directory structure of the Argoverse-HD dataset:

For Stargazers

BTW, if anyone manually modifies the directory structure to fit the one provided in README, an AssertionError will occur: (some parts of file path was edited)

AssertionError: Caught AssertionError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "%HOME%\anaconda3\envs\streamyolo\lib\site-packages\torch\utils\data\_utils\worker.py", line 198, in _worker_loop
    data = fetcher.fetch(index)
  File "%HOME%\anaconda3\envs\streamyolo\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "%HOME%\anaconda3\envs\streamyolo\lib\site-packages\torch\utils\data\_utils\fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "%HOME%\anaconda3\envs\streamyolo\lib\site-packages\yolox\data\datasets\datasets_wrapper.py", line 110, in wrapper
    ret_val = getitem_fn(self, index)
  File "%WORKSPACE%\StreamYOLO\exps\data\tal_flip_mosaicdetection.py", line 255, in __getitem__
    img, support_img, label, support_label, img_info, id_ = self._dataset.pull_item(idx)
  File "%WORKSPACE%\StreamYOLO\exps\dataset\tal_flip_one_future_argoversedataset.py", line 227, in pull_item
    img = self.load_resized_img(index)
  File "%WORKSPACE%\StreamYOLO\exps\dataset\tal_flip_one_future_argoversedataset.py", line 180, in load_resized_img
    img = self.load_image(index)
  File "%WORKSPACE%\StreamYOLO\exps\dataset\tal_flip_one_future_argoversedataset.py", line 196, in load_image
    assert img is not None
AssertionError

If anyone gets the similar error message, the content in For Developers may be helpful.

Hi, I have read your paper.

I have a question in figure 2.

On the page3 in the paper, you wrote the expression "the output y1 of the frame F1 is matched and evaluated with the ground truth of F3 and the result of F2 is missed" about Figure 2.

I understood like that expression mean y1 is the output of the none-real-time detectors of frame F1.

But, before the frame F3 is received, the frame F2 is received in first.

So I can't understand that point and I also want to ask when the output of the frame f0 come out.

Hi, thank you for suggesting your nice code.

I trained the model using Argoverse dataset following your readme.

I want to run demo and save detection results (image or video), how can i do that?

thank you.