yanbeic / ccl Goto Github PK

I run the scripts you provided and I can not get the results on UCF51 you list in your paper. Could you provide some pretrained models on each dataset?

Hi,
Thank you for putting out the source code. I downloaded the data as instructed and made the json file. But running your scripts gives the following error:
label_id = class_to_idx[label]
KeyError: 'BaseballPitch'

Also, when i read the ucf51_json file, there is no BaseballPitch label. Could you perhaps tell what might be the issue.

Thanks,

Hi,

Would it be possible to know a rough estimate of time before you release the code here?

Thank you,

Thanks a lot for your insightful work. Since I want to reproduce your method, I wonder how many computation resources you used and how long you spent training your network? Looking forward to your reply.

As we can see, there are four functions for train. I found a problem, In train_epoch function which is baseline, write_to_epoch_logger() are excuted after finishing the batch calculation("for" loop). But in the other 3 training functions(train_a_epoch, train_i_epoch, train_ai_epoch), that write_to_epoch_logger() function is inside the for loop which is different from the baseline. This should be placed outside the for loop.
Meanwhile that write_to_epoch_logger() function's write log argument should be avg, not val. If you use val, it means that you are using the acc of the last input in this batch, not the average acc of the whole batch。
If my understanding is wrong, please correct me! I would be grateful if you could reply as soon as possible.

Hi,

When I tried to run scripts/run_ccl_ai.sh after generating the json file. I received the error below..

Traceback (most recent call last): │
File "main.py", line 569, in │
main_worker(-1, opt) │
File "main.py", line 522, in main_worker │
tb_writer=tb_writer, distributed=opt.distributed, image_size=image_size, loss_weight=opt.loss_weigh│
t) │
File "/media/data/huwang/experiments/multimodal/CCL/training.py", line 402, in train_ai_epoch │
features_img = image_model(images) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/modules/module.p│
y", line 493, in call │
result = self.forward(*input, **kwargs) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/parallel/data_pa│
rallel.py", line 152, in forward │
outputs = self.parallel_apply(replicas, inputs, kwargs) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/parallel/data_pa│
rallel.py", line 162, in parallel_apply │
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)]) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/parallel/paralle│
l_apply.py", line 83, in parallel_apply │
raise output │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/parallel/paralle│
l_apply.py", line 59, in _worker │
output = module(*input, **kwargs) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/modules/module.p│
y", line 493, in call │
result = self.forward(*input, **kwargs) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/modules/containe│
r.py", line 92, in forward │
input = module(input) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/modules/module.p│
y", line 493, in call │
result = self.forward(*input, **kwargs) │
File "/media/data/huwang/program_files/venv/CCL/lib/python3.6/site-packages/torch/nn/modules/pooling.│
py", line 563, in forward │
self.padding, self.ceil_mode, self.count_include_pad) │
RuntimeError: Given input size: (512x4x4). Calculated output size: (512x-2x-2). Output size is too smal│
l at /pytorch/aten/src/THCUNN/generic/SpatialAveragePooling.cu:47

Can you offer some help.. Thank you

I tried CCL baseline, audio & AI but they all have this issue

random crop
/scratch1/zhe031/envs/minic220426/lib/python3.9/site-packages/torchvision/transforms/transforms.py:890: UserWarning: Argument interpolation should be of type InterpolationMode instead of int. Please, use InterpolationMode enum.
warnings.warn(
Traceback (most recent call last):
File "/scratch1/zhe031/CCL/main.py", line 569, in
main_worker(-1, opt)
File "/scratch1/zhe031/CCL/main.py", line 463, in main_worker
get_train_utils(opt, model_parameters=parameters, av_parameters=aud_para, iv_parameters=img_para)
File "/scratch1/zhe031/CCL/main.py", line 189, in get_train_utils
train_loader = torch.utils.data.DataLoader(train_data,
File "/scratch1/zhe031/envs/minic220426/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 277, in init
sampler = RandomSampler(dataset, generator=generator) # type: ignore[arg-type]
File "/scratch1/zhe031/envs/minic220426/lib/python3.9/site-packages/torch/utils/data/sampler.py", line 97, in init
raise ValueError("num_samples should be a positive integer "
**_

ValueError: num_samples should be a positive integer value, but got num_samples=0

_**

I guess normally it is a dataloader issue. I have double-checked that my hdf5 data & audio data is not 0K (exactly have data), and the file path is the same as given in readme file. So have you suffered the same bug previously? Or do you have any idea about how to fix it?

Thanks

Hi,

Thank you for sharing such good codes and work.

When I tried to generate the json files, ../data/UCF101/UCF101_hdf5/HandstandPushups/v_HandStandPushups_g08_c01.hdf5 to ../data/UCF101/UCF101_hdf5/HandstandPushups/v_HandStandPushups_g07_c04.hdf5. It returns Cannot find the file...

I tried to regenerate the hdf5 of HandstandPushups, the problem is still there.
Really appreciate if you can offer some help!

Best,
Hu