文件名称:Zero-DCE:零参考深曲线估计的Pytorch实施,用于弱光图像增强
文件大小:4.19MB
文件格式:ZIP
更新时间:2024-06-11 09:09:52
deep-learning pytorch hdr zero-shot-learning low-light-enhance
零DCE 零参考深曲线估计的Pytorch实施以实现低光图像增强( )。 使用活页夹访问笔记本: 在Wandb上找到培训日志: ://wandb.ai/19soumik-rakshit96/zero-dce 结果 嘈杂结果示例 引文 @article{2001.06826, Author = {Chunle Guo and Chongyi Li and Jichang Guo and Chen Change Loy and Junhui Hou and Sam Kwong and Runmin Cong}, Title = {Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement}, Year = {2020}, Eprint = {arXiv:2001
【文件预览】:
Zero-DCE-master
----zero_dce()
--------utils.py(3KB)
--------dataloader.py(931B)
--------losses.py(4KB)
--------__init__.py(130B)
--------trainer.py(6KB)
--------model.py(2KB)
----main.py(721B)
----assets()
--------inference_6.jpeg(59KB)
--------inference_1.png(240KB)
--------inference_2.png(237KB)
--------inference_3.png(247KB)
--------inference_10.png(226KB)
--------inference_11.png(233KB)
--------inference_8.jpeg(52KB)
--------inference_9.png(203KB)
--------inference_4.png(225KB)
--------inference_5.png(338KB)
--------inference_13.png(314KB)
--------inference_7.jpeg(59KB)
--------inference_12.png(233KB)
----LICENSE(1KB)
----checkpoints()
--------.gitkeep(0B)
----requirements.txt(162B)
----.gitignore(38B)
----build_docs.sh(43B)
----pretrained-models()
--------model200_dark_faces.pth(315KB)
----README.md(3KB)
----notebooks()
--------Zero_DCE_Train.ipynb(1.88MB)
--------Zero_DCE_Test.ipynb(1.58MB)