module has no attribute about bottom-up-features HOT 5 OPEN

I have solved this problem, but I have a new problem, I want to know what the extracted image feature dimension is 2048 (10-100)?

Because when I use the extracted image features to train the model, the following problem arises

RuntimeError: stack expects each tensor to be equal size, but got [100, 10] at entry 0 and [100, 18] at entry 1

from bottom-up-features.

Hi. It outputs 10-100 features (1 for each detected object), so the value will differ for each image.

from bottom-up-features.

So how do I use these features in the dataloader function? Because the following error was reported in the program

Traceback (most recent call last):
File "E:/vizwiz-vqa/mcan-vqa-master/run.py", line 155, in
execution.run(__C.RUN_MODE)
File "E:\vizwiz-vqa\mcan-vqa-master\core\exec.py", line 513, in run
self.train(self.dataset, self.dataset_eval)
File "E:\vizwiz-vqa\mcan-vqa-master\core\exec.py", line 149, in train
for step, (
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data\dataloader.py", line 521, in next
data = self._next_data()
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data\dataloader.py", line 561, in _next_data
data = self._dataset_fetcher.fetch(index) # may raise StopIteration
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data_utils\fetch.py", line 52, in fetch
return self.collate_fn(data)
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data_utils\collate.py", line 84, in default_collate
return [default_collate(samples) for samples in transposed]
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data_utils\collate.py", line 84, in
return [default_collate(samples) for samples in transposed]
File "C:\Users\KAI.conda\envs\fw\lib\site-packages\torch\utils\data_utils\collate.py", line 56, in default_collate
return torch.stack(batch, 0, out=out)
RuntimeError: stack expects each tensor to be equal size, but got [100, 14] at entry 0 and [100, 11] at entry 1

进程已结束,退出代码1

from bottom-up-features.

Can you provide some reference code to load these features?

from bottom-up-features.

You can pad all the features to the max size (100 in this case) with 0. That's what they do in the original MCAN model: code (in proc_img_feat function)

from bottom-up-features.