lkfmixer
LKFMixer: Exploring Large Kernel Feature For Efficient Image Super-Resolution
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (10.7%) to scientific vocabulary
Repository
LKFMixer: Exploring Large Kernel Feature For Efficient Image Super-Resolution
Basic Info
- Host: GitHub
- Owner: Supereeeee
- License: apache-2.0
- Language: Python
- Default Branch: master
- Size: 33.1 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
LKFMixer: Exploring Large Kernel Feature For Efficient Image Super-Resolution
Environment in our experiments
[python 3.8]
[Ubuntu 20.04]
PyTorch 1.13.0, Torchvision 0.14.0, Cuda 11.7
Installation
git clone https://github.com/Supereeeee/LKFMixer.git
pip install -r requirements.txt
python setup.py develop
How To Test
· Refer to ./options/test for the configuration file of the model to be tested and prepare the testing data.
· The pre-trained models have been palced in ./experiments/pretrained_models/
· Then run the follwing codes for testing:
python basicsr/test.py -opt options/test/test_LKFMixer_x2.yml
python basicsr/test.py -opt options/test/test_LKFMixer_x3.yml
python basicsr/test.py -opt options/test/test_LKFMixer_x4.yml
The testing results will be saved in the ./results folder.
How To Train
· Refer to ./options/train for the configuration file of the model to train.
· Preparation of training data can refer to this page. All datasets can be downloaded at the official website.
· Note that the default training dataset is based on lmdb, refer to docs in BasicSR to learn how to generate the training datasets.
· The training command is like following:
python basicsr/train.py -opt options/train/train_LKFMixer_x2.yml
python basicsr/train.py -opt options/train/train_LKFMixer_x3.yml
python basicsr/train.py -opt options/train/train_LKFMixer_x4.yml
For more training commands and details, please check the docs in BasicSR
Inference time
· You can run ./inference/main_inference.py on your decive to test the inference time.
Acknowledgement
This code is based on BasicSR toolbox. Thanks for the awesome work.
Contact
If you have any question, please email quanwei1277@163.com.
Owner
- Name: Quanwei
- Login: Supereeeee
- Kind: user
- Repositories: 1
- Profile: https://github.com/Supereeeee
Bittersweet.
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this project, please cite it as below."
title: "BasicSR: Open Source Image and Video Restoration Toolbox"
version: 1.3.5
date-released: 2022-02-16
url: "https://github.com/XPixelGroup/BasicSR"
license: Apache-2.0
authors:
- family-names: Wang
given-names: Xintao
- family-names: Xie
given-names: Liangbin
- family-names: Yu
given-names: Ke
- family-names: Chan
given-names: Kelvin C.K.
- family-names: Loy
given-names: Chen Change
- family-names: Dong
given-names: Chao
GitHub Events
Total
- Watch event: 1
- Push event: 3
- Create event: 3
Last Year
- Watch event: 1
- Push event: 3
- Create event: 3
Dependencies
- actions/checkout v2 composite
- actions/setup-python v1 composite
- pypa/gh-action-pypi-publish master composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v2 composite
- actions/create-release v1 composite
- Pillow *
- addict *
- future *
- lmdb *
- numpy *
- opencv-python *
- pyyaml *
- recommonmark *
- requests *
- scikit-image *
- scipy *
- sphinx *
- sphinx_intl *
- sphinx_markdown_tables *
- sphinx_rtd_theme *
- tb-nightly *
- torch >=1.7
- torchvision *
- tqdm *
- yapf *
- Pillow *
- addict *
- future *
- lmdb *
- numpy >=1.17
- opencv-python *
- pyyaml *
- requests *
- scikit-image *
- scipy *
- tb-nightly *
- torch >=1.7
- torchvision *
- tqdm *
- yapf *