[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-80173":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":8,"htmlUrl":8,"language":9,"languages":8,"totalLinesOfCode":8,"stars":10,"forks":11,"watchers":11,"openIssues":12,"contributorsCount":13,"subscribersCount":13,"size":13,"stars1d":13,"stars7d":13,"stars30d":13,"stars90d":13,"forks30d":13,"starsTrendScore":13,"compositeScore":14,"rankGlobal":8,"rankLanguage":8,"license":8,"archived":15,"fork":15,"defaultBranch":16,"hasWiki":17,"hasPages":15,"topics":18,"createdAt":8,"pushedAt":8,"updatedAt":19,"readmeContent":20,"aiSummary":21,"trendingCount":13,"starSnapshotCount":13,"syncStatus":22,"lastSyncTime":23,"discoverSource":24},80173,"SwinGSR","qianchentao9\u002FSwinGSR","qianchentao9",null,"Python",51,1,3,0,0.9,false,"main",true,[],"2026-06-12 02:03:59","## Paper\n\nThe official implementation for the paper. You can access the article here:\n[Springer Link: 10.1007\u002Fs13042-025-02796-6](https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs13042-025-02796-6)\n\n## Dependencies\n\n- Python 3.8\n- PyTorch 1.8.0\n- NVIDIA GPU + [CUDA](https:\u002F\u002Fdeveloper.nvidia.com\u002Fcuda-downloads)\n\n```bash\n# Clone the github repo and go to the default directory 'SwinGSR'.\ngit clone https:\u002F\u002Fgithub.com\u002Fchentaoqian\u002FSwinGSR.git\nconda create -n SwinGSR python=3.8\nconda activate SwinGSR\npip install -r requirements.txt\npython setup.py develop\n```\n\n## Training\n- Run the following scripts. The training configuration is in `options\u002Ftrain\u002F`.\n  ```shell\n  python basicsr\u002Ftrain.py -opt options\u002FTrain\u002FSwinGSR\u002Ftrain_SwinGSR_x2.yml\n  python basicsr\u002Ftrain.py --opt options\u002Ftrain\u002FSwinGSR\u002Ftrain_SwinGSR_x4.yml\n\n  ```\n- The training experiment is in `experiments\u002F`.\n  \n## Testing\n- Run the following scripts. The testing configuration is in `options\u002Ftest\u002F`.\n  ```shell\n  python basicsr\u002Ftrain.py -opt options\u002FTest\u002Fmy_test_SwinGSR_x2.yml\n  python basicsr\u002Ftrain.py -opt options\u002FTest\u002Fmy_test_SwinGSR_x4.yml\n  ```\n- The output is in `results\u002F`.\n\n## Acknowledgements\n\nThis code is built on  [SwinIR]([https:\u002F\u002Fgithub.com\u002Fzhengchen1999\u002FDAT.git](https:\u002F\u002Fgithub.com\u002FJingyunLiang\u002FSwinIR\u002Ftree\u002Fmain)).\n\n","SwinGSR 是一个基于 Swin Transformer 的图像超分辨率项目。该项目通过使用 PyTorch 框架，在 NVIDIA GPU 上运行，能够实现图像的2倍和4倍超分辨率处理。它依赖于 Python 3.8 和特定版本的 PyTorch 等环境配置，并提供了详细的训练与测试脚本，使得用户可以轻松地根据自己的需求调整参数并执行实验。适用于需要提高图像分辨率的各种场景，如高清视频生成、老旧照片修复等。",2,"2026-06-11 03:59:32","CREATED_QUERY"]