# BAM-CBAM-pytorch

**Repository Path**: linkchainiii/BAM-CBAM-pytorch

## Basic Information

- **Project Name**: BAM-CBAM-pytorch
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-29
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

BAM & CBAM Pytorch
==================

Pytorch implementation of BAM and CBAM.
## BAM & CBAM Pytorch

This code purpose to evaluate of popular attention model architectures, such as BAM, CBAM on the CIFAR dataset.

#### Getting Started
```bash
$ git clone https://github.com/asdf2kr/BAM-CBAM-pytorch.git
$ cd BAM-CBAM-pytorch
$ python main.py --arch bam (default: bam network based on resnet50)
```

#### Performance
The table below shows models, dataset and performances

Model | Backbone | Dataset | Top-1 | Top-5 | Size
:----:| :----:| :------:| :----:|:-----:|:----:
ResNet| resnet50 |CIFAR-100 | 78.93% | - | 23.70M
BAM   | resnet50 |CIFAR-100 | 79.62% | - | 24.06M
CBAM  | resnet50 |CIFAR-100 | 81.02% | - | 26.23M

#### To-do
Simple setup readme
Add ImageNet datasets.