基于GFPGAN的超分辨率模型
1.支持任意大小的图片输入
2.输入模糊的图片，输出清晰的图片
3.采用pytorch框架实现，带有预训练权重，压缩包中带有完整的测试样例和代码
4.开箱即用，只需要两行代码即可使用
文件下载
资源详情
[{"title":"（ 70 个子文件 309.18MB ） 基于GFPGAN的超分辨率模型","children":[{"title":"pretrained_model","children":[{"title":"GFPGANCleanv1-NoCE-C2.pth <span style='color:#111;'> 332.48MB </span>","children":null,"spread":false}],"spread":true},{"title":"utils.py <span style='color:#111;'> 9.06KB </span>","children":null,"spread":false},{"title":"super_resolution","children":[{"title":"inference.ipynb <span style='color:#111;'> 2.41KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"gfpgan_model.py <span style='color:#111;'> 2.81KB </span>","children":null,"spread":false},{"title":"config.json <span style='color:#111;'> 250B </span>","children":null,"spread":false},{"title":"gfpgan","children":[{"title":"utils.py <span style='color:#111;'> 7.53KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 125B </span>","children":null,"spread":false},{"title":"data","children":[{"title":"__init__.py <span style='color:#111;'> 118B </span>","children":null,"spread":false},{"title":"ffhq_degradation_dataset.py <span style='color:#111;'> 10.55KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"__init__.cpython-39.pyc <span style='color:#111;'> 706B </span>","children":null,"spread":false},{"title":"ffhq_degradation_dataset.cpython-39.pyc <span style='color:#111;'> 7.00KB </span>","children":null,"spread":false},{"title":"ffhq_degradation_dataset.cpython-38.pyc <span style='color:#111;'> 7.06KB </span>","children":null,"spread":false},{"title":"__init__.cpython-38.pyc <span style='color:#111;'> 323B </span>","children":null,"spread":false}],"spread":true},{"title":".ipynb_checkpoints","children":[{"title":"ffhq_degradation_dataset-checkpoint.py <span style='color:#111;'> 10.55KB </span>","children":null,"spread":false},{"title":"__init__-checkpoint.py <span style='color:#111;'> 118B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"models","children":[{"title":"__init__.py <span style='color:#111;'> 106B </span>","children":null,"spread":false},{"title":"gfpgan_model.py <span style='color:#111;'> 27.47KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"gfpgan_model.cpython-38.pyc <span style='color:#111;'> 14.12KB </span>","children":null,"spread":false},{"title":"gfpgan_model.cpython-39.pyc <span style='color:#111;'> 13.83KB </span>","children":null,"spread":false},{"title":"__init__.cpython-39.pyc <span style='color:#111;'> 705B </span>","children":null,"spread":false},{"title":"__init__.cpython-38.pyc <span style='color:#111;'> 313B </span>","children":null,"spread":false}],"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"gfpgan_model-checkpoint.py <span style='color:#111;'> 27.47KB </span>","children":null,"spread":false},{"title":"__init__-checkpoint.py <span style='color:#111;'> 106B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"archs","children":[{"title":"__init__.py <span style='color:#111;'> 276B </span>","children":null,"spread":false},{"title":"gfpganv1_clean_arch.py <span style='color:#111;'> 14.70KB </span>","children":null,"spread":false},{"title":"stylegan2_clean_arch.py <span style='color:#111;'> 14.64KB </span>","children":null,"spread":false},{"title":"gfpgan_bilinear_arch.py <span style='color:#111;'> 14.17KB </span>","children":null,"spread":false},{"title":"stylegan2_bilinear_arch.py <span style='color:#111;'> 22.80KB </span>","children":null,"spread":false},{"title":"gfpganv1_arch.py <span style='color:#111;'> 19.47KB </span>","children":null,"spread":false},{"title":"arcface_arch.py <span style='color:#111;'> 8.14KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"stylegan2_clean_arch.cpython-39.pyc <span style='color:#111;'> 11.52KB </span>","children":null,"spread":false},{"title":"gfpgan_bilinear_arch.cpython-38.pyc <span style='color:#111;'> 9.08KB </span>","children":null,"spread":false},{"title":"stylegan2_bilinear_arch.cpython-39.pyc <span style='color:#111;'> 17.56KB </span>","children":null,"spread":false},{"title":"gfpganv1_clean_arch.cpython-39.pyc <span style='color:#111;'> 9.32KB </span>","children":null,"spread":false},{"title":"stylegan2_bilinear_arch.cpython-38.pyc <span style='color:#111;'> 17.68KB </span>","children":null,"spread":false},{"title":"arcface_arch.cpython-39.pyc <span style='color:#111;'> 7.22KB </span>","children":null,"spread":false},{"title":"arcface_arch.cpython-38.pyc <span style='color:#111;'> 7.30KB </span>","children":null,"spread":false},{"title":"gfpganv1_clean_arch.cpython-38.pyc <span style='color:#111;'> 9.41KB </span>","children":null,"spread":false},{"title":"gfpganv1_arch.cpython-39.pyc <span style='color:#111;'> 12.56KB </span>","children":null,"spread":false},{"title":"__init__.cpython-39.pyc <span style='color:#111;'> 699B </span>","children":null,"spread":false},{"title":"gfpganv1_arch.cpython-38.pyc <span style='color:#111;'> 12.84KB </span>","children":null,"spread":false},{"title":"stylegan2_clean_arch.cpython-38.pyc <span style='color:#111;'> 11.63KB </span>","children":null,"spread":false},{"title":"gfpgan_bilinear_arch.cpython-39.pyc <span style='color:#111;'> 8.90KB </span>","children":null,"spread":false},{"title":"__init__.cpython-38.pyc <span style='color:#111;'> 522B </span>","children":null,"spread":false}],"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"arcface_arch-checkpoint.py <span style='color:#111;'> 8.14KB </span>","children":null,"spread":false},{"title":"gfpgan_bilinear_arch-checkpoint.py <span style='color:#111;'> 14.17KB </span>","children":null,"spread":false},{"title":"__init__-checkpoint.py <span style='color:#111;'> 276B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"train.py <span style='color:#111;'> 269B </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"__init__.cpython-39.pyc <span style='color:#111;'> 218B </span>","children":null,"spread":false},{"title":"utils.cpython-39.pyc <span style='color:#111;'> 3.98KB </span>","children":null,"spread":false},{"title":"utils.cpython-38.pyc <span style='color:#111;'> 4.03KB </span>","children":null,"spread":false},{"title":"__init__.cpython-38.pyc <span style='color:#111;'> 235B </span>","children":null,"spread":false}],"spread":false},{"title":".ipynb_checkpoints","children":[{"title":"utils-checkpoint.py <span style='color:#111;'> 7.53KB </span>","children":null,"spread":false},{"title":"__init__-checkpoint.py <span style='color:#111;'> 125B </span>","children":null,"spread":false}],"spread":false}],"spread":true},{"title":"__pycache__","children":[{"title":"inference.cpython-38.pyc <span style='color:#111;'> 1.88KB </span>","children":null,"spread":false},{"title":"gfpgan_model.cpython-38.pyc <span style='color:#111;'> 1.97KB </span>","children":null,"spread":false},{"title":"__init__.cpython-38.pyc <span style='color:#111;'> 231B </span>","children":null,"spread":false}],"spread":true},{"title":".ipynb_checkpoints","children":[{"title":"inference-checkpoint.ipynb <span style='color:#111;'> 3.92KB </span>","children":null,"spread":false},{"title":"config-v1-checkpoint.json <span style='color:#111;'> 261B </span>","children":null,"spread":false},{"title":"config-checkpoint.json <span style='color:#111;'> 251B </span>","children":null,"spread":false},{"title":"gfpgan_model-checkpoint.py <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"__init__-checkpoint.py <span style='color:#111;'> 46B </span>","children":null,"spread":false}],"spread":true},{"title":"config-v1.json <span style='color:#111;'> 261B </span>","children":null,"spread":false}],"spread":true},{"title":"2.jpg <span style='color:#111;'> 103.18KB </span>","children":null,"spread":false},{"title":"example.html <span style='color:#111;'> 634.86KB </span>","children":null,"spread":false},{"title":"1.jpeg <span style='color:#111;'> 8.18KB </span>","children":null,"spread":false},{"title":"example.ipynb <span style='color:#111;'> 136.49KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"utils.cpython-38.pyc <span style='color:#111;'> 8.58KB </span>","children":null,"spread":false}],"spread":true},{"title":".ipynb_checkpoints","children":[{"title":"example-checkpoint.ipynb <span style='color:#111;'> 72B </span>","children":null,"spread":false}],"spread":true}],"spread":true}]
评论信息
其他资源
- 现代数字信号处理扫描版
- 基于Labview的调制解调2ASK,2DPSK,2FSK,2PSK,AM,DSB,FM,PCM,
- CPU设计与实践 ISE工程文件（直接可运行）
- 圆极化天线设计手册
- 集装箱装箱计算源代码
- 北航961初试资料 真题+ppt+期中期末+教材+解析
- 微软TTS语音引擎实现文本朗读代码
- 数模模数转换器ADC0809/DAC0832等
- dx图像增强
- 3D打印机控制软件Cura源码
- C语言期末考试全部知识点复习资料--重点--常考点.pdf
- ADF4106 之C语言驱动代码.zip
- 2014年重庆理工大学《复变函数与积分变换II》期末考试AB试卷.pdf
- 全国计算机等级考试二级C语言上机题库考试真题50套
- 【离散数学】MIT 6.042J - Fall 2010 - Note for Lecture 5
- Xshell-6.0.exe.7z
- freer-cofreer：更自由的单子和cofreer comonads-源码
- lianxubo.m连续波调频代码仿真
- 人体24小时使用手册.doc
- C/C++语言大作业、小游戏
- KMP中文字符匹配算法的C++实现
- 深入应用C++11：代码优化与工程级应用
- Flash 送给父母的flash小动画，很有爱的
免责申明
【只为小站】的资源来自网友分享，仅供学习研究，请务必在下载后24小时内给予删除，不得用于其他任何用途，否则后果自负。基于互联网的特殊性，【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查；无论 【只为小站】 经营者是否已进行审查，用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明