62 lines
2.5 KiB
Markdown
62 lines
2.5 KiB
Markdown
# reproduce the GoPro dataset results
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### 1. Data Preparation
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##### Download the train set and place it in ```./datasets/GoPro/train```:
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* google drive [link](https://drive.google.com/file/d/1zgALzrLCC_tcXKu_iHQTHukKUVT1aodI/view?usp=sharing) or 百度网盘 [link](https://pan.baidu.com/s/1fdsn-M5JhxCL7oThEgt1Sw), (提取码: 9d26)
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* it should be like ```./datasets/GoPro/train/input ``` and ```./datasets/GoPro/train/target```
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* ```python scripts/data_preparation/gopro.py``` to crop the train image pairs to 512x512 patches and make the data into lmdb format.
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##### Download the evaluation data (in lmdb format) and place it in ```./datasets/GoPro/test/```:
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* google drive [link](https://drive.google.com/file/d/1abXSfeRGrzj2mQ2n2vIBHtObU6vXvr7C/view?usp=sharing) or 百度网盘 [link](https://pan.baidu.com/s/1oZtEtYB7-2p3fCIspky_mw), (提取码: rmv9)
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* it should be like ```./datasets/GoPro/test/input.lmdb``` and ```./datasets/GoPro/test/target.lmdb```
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### 2. Training
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* NAFNet-GoPro-width32:
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```
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python -m torch.distributed.launch --nproc_per_node=8 --master_port=4321 basicsr/train.py -opt options/train/GoPro/NAFNet-width32.yml --launcher pytorch
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```
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* NAFNet-GoPro-width64:
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```
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python -m torch.distributed.launch --nproc_per_node=8 --master_port=4321 basicsr/train.py -opt options/train/GoPro/NAFNet-width64.yml --launcher pytorch
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```
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* 8 gpus by default. Set ```--nproc_per_node``` to # of gpus for distributed validation.
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### 3. Evaluation
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##### Download the pretrain model in ```./experiments/pretrained_models/```
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* **NAFNet-GoPro-width32**: google drive [link](https://drive.google.com/file/d/1Fr2QadtDCEXg6iwWX8OzeZLbHOx2t5Bj/view?usp=sharing) or 百度网盘 [link](https://pan.baidu.com/s/1AbgG0yoROHmrRQN7dgzDvQ), (提取码: so6v)
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* **NAFNet-GoPro-width64**: google drive [link](https://drive.google.com/file/d/1S0PVRbyTakYY9a82kujgZLbMihfNBLfC/view?usp=sharing) or 百度网盘 [link](https://pan.baidu.com/s/1g-E1x6En-PbYXm94JfI1vg), (提取码: wnwh)
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##### Testing on GoPro dataset
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* NAFNet-GoPro-width32:
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```
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python -m torch.distributed.launch --nproc_per_node=1 --master_port=4321 basicsr/test.py -opt ./options/test/GoPro/NAFNet-width32.yml --launcher pytorch
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```
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* NAFNet-GoPro-width64:
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```
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python -m torch.distributed.launch --nproc_per_node=1 --master_port=4321 basicsr/test.py -opt ./options/test/GoPro/NAFNet-width64.yml --launcher pytorch
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```
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* Test by a single gpu by default. Set ```--nproc_per_node``` to # of gpus for distributed validation.
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