GALD-DGCNet:源代码和模型GALD net(BMVC-2019)和Dual-Seg Net(BMVC-2019)

上传者: 42133329 | 上传时间: 2022-11-29 21:21:01 | 文件大小: 2.1MB | 文件类型: ZIP
GALD-Net和Dual-Seg网(BMVC-2019) 这是GALD-net和Dual-Seg的PyTorch重新实现。 这两篇论文均被BMVC-2019接受,并在Cityscapes和Pascal Context数据集上取得了最新的成果。 高性能道路场景语义分割 :party_popper: 还有一个用于快速道路场景语义分割的: 并感谢您的关注 :grinning_face_with_big_eyes: GALDNet DualGCNSegNet 培训与验证 要求 pytorch> = 1.1.0顶点opencv-python 预训练模型 百度Pan链接: ://pan.baidu.com/s/1MWzpkI3PwtnEl1LSOyLrLw passwd:4lwf Google云端硬盘链接: ://drive.google.com/file/d/1JlERBWT8fHvf-uD36k5-LRZ5taqUbraj/view?usp sharing

文件下载

资源详情

[{"title":"( 39 个子文件 2.1MB ) GALD-DGCNet:源代码和模型GALD net(BMVC-2019)和Dual-Seg Net(BMVC-2019)","children":[{"title":"GALD-DGCNet-master","children":[{"title":".gitignore <span style='color:#111;'> 402B </span>","children":null,"spread":false},{"title":"inferenceGALD.py <span style='color:#111;'> 2.68KB </span>","children":null,"spread":false},{"title":"data","children":[{"title":"camvid","children":[{"title":"camvid_trainval_list.txt <span style='color:#111;'> 23.23KB </span>","children":null,"spread":false},{"title":"camvid_train_list.txt <span style='color:#111;'> 18.60KB </span>","children":null,"spread":false},{"title":"camvid_test_list.txt <span style='color:#111;'> 11.94KB </span>","children":null,"spread":false},{"title":"camvid_val_list.txt <span style='color:#111;'> 4.64KB </span>","children":null,"spread":false}],"spread":true},{"title":"cityscapes","children":[{"title":"test.txt <span style='color:#111;'> 91.60KB </span>","children":null,"spread":false},{"title":"train+.txt <span style='color:#111;'> 3.24MB </span>","children":null,"spread":false},{"title":"trainval.txt <span style='color:#111;'> 436.82KB </span>","children":null,"spread":false},{"title":"train.txt <span style='color:#111;'> 374.91KB </span>","children":null,"spread":false},{"title":"val.txt <span style='color:#111;'> 61.91KB </span>","children":null,"spread":false},{"title":"train++.txt <span style='color:#111;'> 3.30MB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"eval.py <span style='color:#111;'> 10.25KB </span>","children":null,"spread":false},{"title":"exp","children":[{"title":"train_dualseg_r_50_city_finetrain.sh <span style='color:#111;'> 562B </span>","children":null,"spread":false},{"title":"train_gald_r_101_city_finetrain.sh <span style='color:#111;'> 563B </span>","children":null,"spread":false},{"title":"test_dualseg_r_50_city_finetrain.sh <span style='color:#111;'> 295B </span>","children":null,"spread":false},{"title":"train_gald_r_50_city_finetrain.sh <span style='color:#111;'> 559B </span>","children":null,"spread":false},{"title":"train_dualseg_r_101_city_finetrain.sh <span style='color:#111;'> 565B </span>","children":null,"spread":false}],"spread":true},{"title":"Common.md <span style='color:#111;'> 762B </span>","children":null,"spread":false},{"title":"fig","children":[{"title":"gald.jpeg <span style='color:#111;'> 210.52KB </span>","children":null,"spread":false},{"title":"dual_seg.jpeg <span style='color:#111;'> 1.58MB </span>","children":null,"spread":false}],"spread":true},{"title":"libs","children":[{"title":"core","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"operators.py <span style='color:#111;'> 10.01KB </span>","children":null,"spread":false},{"title":"loss.py <span style='color:#111;'> 3.72KB </span>","children":null,"spread":false}],"spread":true},{"title":"datasets","children":[{"title":"cityscapes.py <span style='color:#111;'> 4.26KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"mapillary.py <span style='color:#111;'> 11.80KB </span>","children":null,"spread":false},{"title":"camvid.py <span style='color:#111;'> 6.59KB </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"models","children":[{"title":"GALDNet.py <span style='color:#111;'> 10.20KB </span>","children":null,"spread":false},{"title":"DualGCNNet.py <span style='color:#111;'> 8.58KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 71B </span>","children":null,"spread":false},{"title":"PSPNet.py <span style='color:#111;'> 8.30KB </span>","children":null,"spread":false}],"spread":true},{"title":"utils","children":[{"title":"image_utils.py <span style='color:#111;'> 5.73KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"tools.py <span style='color:#111;'> 2.26KB </span>","children":null,"spread":false},{"title":"logger.py <span style='color:#111;'> 5.68KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"README.md <span style='color:#111;'> 4.64KB </span>","children":null,"spread":false},{"title":"train_distribute.py <span style='color:#111;'> 10.96KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

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