fmahoudeau / mict-net-pytorch Goto Github PK

Is there any colab version for the work done?

Excuse me, how can I solve this problem：
python train.py --model mictresnet --version v1 --backbone resnet18 --lr 1e-2 --weight-decay 5e-4 --dropout 0.5 --batch-size 112 --base-size 192 --crop-size 160 --split 1 --checkname MiCTResNet_V1 --crop-vid 16 --epochs 120 --pretrained --lr-scheduler step --lr-step 80
=> creating output/ucf101/mictresnet/MiCTResNet_V1/
Namespace(backbone='resnet18', base_size=192, batch_size=112, checkname='MiCTResNet_V1', crop_size=160, crop_vid=16, cuda=True, data_folder='/home/y/MiCT/Datasets/', dataset='ucf101', dropout=0.5, epochs=120, eval=False, ft=False, gpu_id=0, lr=0.01, lr_scheduler='step', lr_step=80, model='mictresnet', model_zoo=None, momentum=0.9, no_cuda=False, no_val=False, pretrained=True, resume='', seed=1, split=1, start_epoch=0, test_batch_size=112, test_folder=None, version='v1', weight_decay=0.0005, workers=8)
Compute device: cuda:0
Loading UCF101 train1.csv
9537it [00:00, 254159.06it/s]
Loading UCF101 val1.csv
3783it [00:00, 239066.04it/s]
Total number of parameters: 16051685
Using step LR scheduler
0%| | 0/85 [00:00<?, ?it/s]
Traceback (most recent call last):
File "train.py", line 221, in
trainer.training(epoch)
File "train.py", line 148, in training
for i, (video, target) in enumerate(tbar):
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/tqdm/std.py", line 1127, in iter
for obj in iterable:
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 345, in next
data = self._next_data()
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 856, in _next_data
return self._process_data(data)
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 881, in _process_data
data.reraise()
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/_utils.py", line 394, in reraise
raise self.exc_type(msg)
IndexError: Caught IndexError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 178, in _worker_loop
data = fetcher.fetch(index)
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/y/Anaconda/envs/mm/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "../../mictnet/datasets/ucf101.py", line 115, in getitem
vid = self._train_transform(vid)
File "../../mictnet/datasets/ucf101.py", line 188, in _train_transform
w, h = vid[0].size
IndexError: list index out of range

Hi, sorry to bother you but can you share pre-trained weights?
Also I have a question accuracy which is you presented in in readme this is validation or train accuracy ?

Can you share the pretrained weight files.
Thank you.

Excuse me, I want to do pre-training on the kinetics700, but I don't know how to do it, can you give me some advice? I haven't found a similar pre-training code for reference. Do you know if there is one?

Dear authors,
I have read your code, but I have one question about the concatenting connection about 3/2D convolution.

The paper (MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition) try to select one channel ( a tensor with NCWH) to ahieve 2D convolution operation and select several channels (a tensor with NCDW*H) to achieve 3D convolution operation. I don't konw how to concatenate the feature maps of 3D convolution and the features maps of 2D convolution. If convenient, please answer this question.

Regards,
Lee

Dear authors,
I have read your code, but I have one question about the 2D convolution.
Normal 3D convolution is convolution of 3 frames of images. Can each 2D convolution in the code be interpreted as a simultaneous convolution of 16 frames of images?