recurrent-visual-attention
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A PyTorch Implementation of "Recurrent Models of Visual Attention"
HI, @clvcooke @kevinzakka @malashinroman Is this model can support multi-labels per an image ? I need classification model for images which has multiple classes. I wonder ... Thanks in advance....
The comment in module.py (line 21) says "x" is a 4D tensor of shape (B, H, W, C) but it's actually a 4d tensor of shape (B, C, H, W)...
The loss may be negative number in the model. The reason is that the reinforce loss is often to be a negative number since the reward is the larger the...
python3 main.py --use_gpu False --is_train True ~~~~~~~~~~~~~~~~~~main.py~~~~~~~~~~~~~~~ #kwargs = {} if config.use_gpu: torch.cuda.manual_seed(config.random_seed) kwargs = {"num_workers": 1, "pin_memory": True} else: kwargs = {} # instantiate data loaders '''if config.is_train: dloader...
Epoch: 1/1500 - LR: 0.000300 0%| | 0/11044 [00:04
Hi, @kevinzakka I entered my own data with MNIST Format(256x256, Gray Images, 5000 Images/class) But Performance is not good. What's wrong with me? ------------------------------------------------ Epoch: 196/500 - LR: 0.000300 0.8s...
I am trying ot understand the code for my own data, how to provide this data to the repo in pytorch data format?
Does anyone know how can I start with random initial coordinates for the first square patch?
At the moment the location tensor _l_t_ is never detached from the computational graph in spite of both being produced by and 'consumed' by trainable modules. As far as I...
How do you calculate the final accuracy? If you have 8 steps with one glimpse, do you only consider last step as final prediction for accuracy calculations or do you...