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ARM-Net

★ 81 Open GitHub ↗

Pytorch implementation of our paper accepted by ECCV 2022 -- ARM: Any-Time Super-Resolution Method (https://arxiv.org/abs/2203.10812)

// repository documentation

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# ARM: Any-Time Super-Resolution Method ([Paper Link](https://arxiv.org/abs/2203.10812)) ![](https://visitor-badge.glitch.me/badge?page_id=chenbong.ARM-Net)

Pytorch implementation of ARM-Net in ECCV 2022.

## Dependencies

* Python 3.6
* Pytorch 1.7

## Results

Run the command `python img/plot_psnr_flops.py` to get the above figure.

![tab1](https://raw.githubusercontent.com/chenbong/ARM-Net/main/img/tab1.png)

![tab2](https://raw.githubusercontent.com/chenbong/ARM-Net/main/img/tab2.png)

## Train

### Data preprocessing

```bash
cd data_scripts
python extract_subimages_test.py
python data_augmentation.py
python generate_mod_LR_bic.py
python extract_subimages_train.py
```

## Modify the configuration file (options/*.yml)

```bash
# train_us_fsrcnn.yml
is_train: True

# train_us_carn.yml
is_train: True

# train_us_srresnet.yml
is_train: True
```

### Run training scripts

```bash
python main.py -opt options/train_us_fsrcnn.yml
python main.py -opt options/train_us_carn.yml
python main.py -opt options/train_us_srresnet.yml
```

## Test

### Modify the configuration file (options/*.yml)

```bash
# train_us_fsrcnn.yml
path:
  pretrain_model_G: ckpt/arm-fsrcnn.pth
  resume_state: ckpt/arm-fsrcnn.state
is_train: False
is_test: True

# train_us_carn.yml
path:
  pretrain_model_G: ckpt/arm-carn.pth
  resume_state: ckpt/arm-carn.state
is_train: False
is_test: True

# train_us_srresnet.yml
path:
  pretrain_model_G: ckpt/arm-srresnet.pth
  resume_state: ckpt/arm-srresnet.state
is_train: False
is_test: True
```

### Run test scripts

```bash
python main.py -opt options/train_us_fsrcnn.yml
python main.py -opt options/train_us_carn.yml
python main.py -opt options/train_us_srresnet.yml
```

ARM-Net

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