History

sennnnn d3dc4f9583 [Enhancement] Add Dev tools to boost develop (#798 ) * Modify default work dir when training. * Refactor gather_models.py. * Add train and test matching list. * Regression benchmark list. * lower readme name to upper readme name. * Add url check tool and model inference test tool. * Modify tool name. * Support duplicate mode of log json url check. * Add regression benchmark evaluation automatic tool. * Add train script generator. * Only Support script running. * Add evaluation results gather. * Add exec Authority. * Automatically make checkpoint root folder. * Modify gather results save path. * Coarse-grained train results gather tool. * Complete benchmark train script. * Make some little modifications. * Fix checkpoint urls. * Fix unet checkpoint urls. * Fix fast scnn & fcn checkpoint url. * Fix fast scnn checkpoint urls. * Fix fast scnn url. * Add differential results calculation. * Add differential results of regression benchmark train results. * Add an extra argument to select model. * Update nonlocal_net & hrnet checkpoint url. * Fix checkpoint url of hrnet and Fix some tta evaluation results and modify gather models tool. * Modify fast scnn checkpoint url. * Resolve new comments. * Fix url check status code bug. * Resolve some comments. * Modify train scripts generator. * Modify work_dir of regression benchmark results. * model gather tool modification.		2021-09-02 09:44:51 -07:00
..
README.md	[Enhancement] Add Dev tools to boost develop (#798 )	2021-09-02 09:44:51 -07:00
deeplabv3_unet_s5-d16_64x64_40k_drive.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
deeplabv3_unet_s5-d16_128x128_40k_stare.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
deeplabv3_unet_s5-d16_256x256_40k_hrf.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
fcn_unet_s5-d16_64x64_40k_drive.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
fcn_unet_s5-d16_128x128_40k_chase_db1.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
fcn_unet_s5-d16_128x128_40k_stare.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
fcn_unet_s5-d16_256x256_40k_hrf.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
pspnet_unet_s5-d16_64x64_40k_drive.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
pspnet_unet_s5-d16_128x128_40k_chase_db1.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
pspnet_unet_s5-d16_128x128_40k_stare.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
pspnet_unet_s5-d16_256x256_40k_hrf.py	[Improvement] Move train_cfg/test_cfg inside model (#341 )	2021-01-19 17:06:23 -08:00
unet.yml	[Enhancement] Add Dev tools to boost develop (#798 )	2021-09-02 09:44:51 -07:00

README.md

U-Net: Convolutional Networks for Biomedical Image Segmentation

Introduction

@inproceedings{ronneberger2015u,
  title={U-net: Convolutional networks for biomedical image segmentation},
  author={Ronneberger, Olaf and Fischer, Philipp and Brox, Thomas},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={234--241},
  year={2015},
  organization={Springer}
}

Results and models

DRIVE

Method	Backbone	Image Size	Crop Size	Stride	Lr schd	Mem (GB)	Inf time (fps)	Dice	config	download
FCN	UNet-S5-D16	584x565	64x64	42x42	40000	0.680	-	78.67	config	model \| log
PSPNet	UNet-S5-D16	584x565	64x64	42x42	40000	0.599	-	78.62	config	model \| log
DeepLabV3	UNet-S5-D16	584x565	64x64	42x42	40000	0.596	-	78.69	config	model \| log

STARE

Method	Backbone	Image Size	Crop Size	Stride	Lr schd	Mem (GB)	Inf time (fps)	Dice	config	download
FCN	UNet-S5-D16	605x700	128x128	85x85	40000	0.968	-	81.02	config	model \| log
PSPNet	UNet-S5-D16	605x700	128x128	85x85	40000	0.982	-	81.22	config	model \| log
DeepLabV3	UNet-S5-D16	605x700	128x128	85x85	40000	0.999	-	80.93	config	model \| log

CHASE_DB1

Method	Backbone	Image Size	Crop Size	Stride	Lr schd	Mem (GB)	Inf time (fps)	Dice	config	download
FCN	UNet-S5-D16	960x999	128x128	85x85	40000	0.968	-	80.24	config	model \| log
PSPNet	UNet-S5-D16	960x999	128x128	85x85	40000	0.982	-	80.36	config	model \| log
DeepLabV3	UNet-S5-D16	960x999	128x128	85x85	40000	0.999	-	80.47	config	model \| log

HRF

Method	Backbone	Image Size	Crop Size	Stride	Lr schd	Mem (GB)	Inf time (fps)	Dice	config	download
FCN	UNet-S5-D16	2336x3504	256x256	170x170	40000	2.525	-	79.45	config	model \| log
PSPNet	UNet-S5-D16	2336x3504	256x256	170x170	40000	2.588	-	80.07	config	model \| log
DeepLabV3	UNet-S5-D16	2336x3504	256x256	170x170	40000	2.604	-	80.21	config	model \| log