Bridge-Attention

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Bridge-Attention

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The code for the paper 'BA-Net: Bridge Attention for Deep Convolutional Neural Networks'

Bridge-Attention 최신버젼 다운로드

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# Bridge-Attention
The code for the paper 'BA-Net: Bridge Attention for Deep Convolutional Neural Networks'
## Description
**'./model/'**  contains the .py files of various backbones architectures, the BA module and the SE module.   
**'./results/'**  saves the checkpoints and log files. 
## Usage
### Training
If you want to train the BA-Net under the backbone architectures like ResNet, ResNeXt, MobileNetv3, use the code ↓. 
```Python
python main.py -a ba_resnet50 {datapath_of_ImageNet} --lr 0.1 --scheduler cos -b 256

# -a: the target architecture, including ba_resnet{18/34/50/101/152}, ba_resnext{18/34/50/101/152}, ba_mobilenetv3_large and ba_mobilenetv3_small. 
#Or you want to train the origin architectures, we also provide resnext{18/34/50/101/152}, mobilenetv3_large and mobilenetv3_small.

# {datapath_of_ImageNet}: directly type the path of the ImageNet-1K, which should contain directories of 'train' and 'val'.

# --lr: the initial learning rate.

# --scheduler: the training scheduler, including 'cos' and 'step'.

# -b: batchsize. 
```

If you want to train the BA-Net under the backbone architecture of EfficientNet, use the code ↓.
```Python
nohup python main_EfficientNet.py -a efficientnet-b0 {datapath_of_ImageNet}
```

### Testing
```Python
python main.py -a ba_resnet50 {datapath_of_ImageNet} -b 256 --resume {path_of_checkpoint} -e

# --resume: the path of checkpoint

# -e: evaluation mode.
```

Bridge-Attention

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