The response has been limited to 50k tokens of the smallest files in the repo. You can remove this limitation by removing the max tokens filter. 
├── .gitignore
├── LICENSE
├── README.md
├── configs
    ├── _base_
    │   ├── datasets
    │   │   ├── ade20k.py
    │   │   ├── chase_db1.py
    │   │   ├── cityscapes.py
    │   │   ├── cityscapes_768x768.py
    │   │   ├── cityscapes_769x769.py
    │   │   ├── drive.py
    │   │   ├── hrf.py
    │   │   ├── pascal_context.py
    │   │   ├── pascal_voc12.py
    │   │   ├── pascal_voc12_aug.py
    │   │   └── stare.py
    │   ├── default_runtime.py
    │   ├── models
    │   │   ├── ann_r50-d8.py
    │   │   ├── apcnet_r50-d8.py
    │   │   ├── ccnet_r50-d8.py
    │   │   ├── cgnet.py
    │   │   ├── danet_r50-d8.py
    │   │   ├── deeplabv3_r50-d8.py
    │   │   ├── deeplabv3_unet_s5-d16.py
    │   │   ├── deeplabv3plus_r50-d8.py
    │   │   ├── dmnet_r50-d8.py
    │   │   ├── dnl_r50-d8.py
    │   │   ├── emanet_r50-d8.py
    │   │   ├── encnet_r50-d8.py
    │   │   ├── fast_scnn.py
    │   │   ├── fcn_hr18.py
    │   │   ├── fcn_r50-d8.py
    │   │   ├── fcn_unet_s5-d16.py
    │   │   ├── fpn_r50.py
    │   │   ├── gcnet_r50-d8.py
    │   │   ├── lraspp_m-v3-d8.py
    │   │   ├── nonlocal_r50-d8.py
    │   │   ├── ocrnet_hr18.py
    │   │   ├── ocrnet_r50-d8.py
    │   │   ├── pointrend_r50.py
    │   │   ├── psanet_r50-d8.py
    │   │   ├── pspnet_r50-d8.py
    │   │   ├── pspnet_unet_s5-d16.py
    │   │   └── upernet_r50.py
    │   └── schedules
    │   │   ├── schedule_160k.py
    │   │   ├── schedule_20k.py
    │   │   ├── schedule_40k.py
    │   │   └── schedule_80k.py
    ├── ann
    │   ├── README.md
    │   ├── ann_r101-d8_512x1024_40k_cityscapes.py
    │   ├── ann_r101-d8_512x1024_80k_cityscapes.py
    │   ├── ann_r101-d8_512x512_160k_ade20k.py
    │   ├── ann_r101-d8_512x512_20k_voc12aug.py
    │   ├── ann_r101-d8_512x512_40k_voc12aug.py
    │   ├── ann_r101-d8_512x512_80k_ade20k.py
    │   ├── ann_r101-d8_769x769_40k_cityscapes.py
    │   ├── ann_r101-d8_769x769_80k_cityscapes.py
    │   ├── ann_r50-d8_512x1024_40k_cityscapes.py
    │   ├── ann_r50-d8_512x1024_80k_cityscapes.py
    │   ├── ann_r50-d8_512x512_160k_ade20k.py
    │   ├── ann_r50-d8_512x512_20k_voc12aug.py
    │   ├── ann_r50-d8_512x512_40k_voc12aug.py
    │   ├── ann_r50-d8_512x512_80k_ade20k.py
    │   ├── ann_r50-d8_769x769_40k_cityscapes.py
    │   └── ann_r50-d8_769x769_80k_cityscapes.py
    ├── apcnet
    │   ├── README.md
    │   ├── apcnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── apcnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── apcnet_r101-d8_512x512_160k_ade20k.py
    │   ├── apcnet_r101-d8_512x512_80k_ade20k.py
    │   ├── apcnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── apcnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── apcnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── apcnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── apcnet_r50-d8_512x512_160k_ade20k.py
    │   ├── apcnet_r50-d8_512x512_80k_ade20k.py
    │   ├── apcnet_r50-d8_769x769_40k_cityscapes.py
    │   └── apcnet_r50-d8_769x769_80k_cityscapes.py
    ├── ccnet
    │   ├── README.md
    │   ├── ccnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── ccnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── ccnet_r101-d8_512x512_160k_ade20k.py
    │   ├── ccnet_r101-d8_512x512_20k_voc12aug.py
    │   ├── ccnet_r101-d8_512x512_40k_voc12aug.py
    │   ├── ccnet_r101-d8_512x512_80k_ade20k.py
    │   ├── ccnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── ccnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── ccnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── ccnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── ccnet_r50-d8_512x512_160k_ade20k.py
    │   ├── ccnet_r50-d8_512x512_20k_voc12aug.py
    │   ├── ccnet_r50-d8_512x512_40k_voc12aug.py
    │   ├── ccnet_r50-d8_512x512_80k_ade20k.py
    │   ├── ccnet_r50-d8_769x769_40k_cityscapes.py
    │   └── ccnet_r50-d8_769x769_80k_cityscapes.py
    ├── cgnet
    │   ├── README.md
    │   ├── cgnet_512x1024_60k_cityscapes.py
    │   └── cgnet_680x680_60k_cityscapes.py
    ├── danet
    │   ├── README.md
    │   ├── danet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── danet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── danet_r101-d8_512x512_160k_ade20k.py
    │   ├── danet_r101-d8_512x512_20k_voc12aug.py
    │   ├── danet_r101-d8_512x512_40k_voc12aug.py
    │   ├── danet_r101-d8_512x512_80k_ade20k.py
    │   ├── danet_r101-d8_769x769_40k_cityscapes.py
    │   ├── danet_r101-d8_769x769_80k_cityscapes.py
    │   ├── danet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── danet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── danet_r50-d8_512x512_160k_ade20k.py
    │   ├── danet_r50-d8_512x512_20k_voc12aug.py
    │   ├── danet_r50-d8_512x512_40k_voc12aug.py
    │   ├── danet_r50-d8_512x512_80k_ade20k.py
    │   ├── danet_r50-d8_769x769_40k_cityscapes.py
    │   └── danet_r50-d8_769x769_80k_cityscapes.py
    ├── deeplabv3
    │   ├── README.md
    │   ├── deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes.py
    │   ├── deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r101-d8_480x480_40k_pascal_context.py
    │   ├── deeplabv3_r101-d8_480x480_80k_pascal_context.py
    │   ├── deeplabv3_r101-d8_512x1024_40k_cityscapes.py
    │   ├── deeplabv3_r101-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r101-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3_r101-d8_512x512_20k_voc12aug.py
    │   ├── deeplabv3_r101-d8_512x512_40k_voc12aug.py
    │   ├── deeplabv3_r101-d8_512x512_80k_ade20k.py
    │   ├── deeplabv3_r101-d8_769x769_40k_cityscapes.py
    │   ├── deeplabv3_r101-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3_r101b-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r101b-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3_r18-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r18-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3_r18b-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r18b-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3_r50-d8_480x480_40k_pascal_context.py
    │   ├── deeplabv3_r50-d8_480x480_80k_pascal_context.py
    │   ├── deeplabv3_r50-d8_512x1024_40k_cityscapes.py
    │   ├── deeplabv3_r50-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_r50-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3_r50-d8_512x512_20k_voc12aug.py
    │   ├── deeplabv3_r50-d8_512x512_40k_voc12aug.py
    │   ├── deeplabv3_r50-d8_512x512_80k_ade20k.py
    │   ├── deeplabv3_r50-d8_769x769_40k_cityscapes.py
    │   ├── deeplabv3_r50-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3_r50b-d8_512x1024_80k_cityscapes.py
    │   └── deeplabv3_r50b-d8_769x769_80k_cityscapes.py
    ├── deeplabv3plus
    │   ├── README.md
    │   ├── deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py
    │   ├── deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r101-d8_480x480_40k_pascal_context.py
    │   ├── deeplabv3plus_r101-d8_480x480_80k_pascal_context.py
    │   ├── deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py
    │   ├── deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r101-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3plus_r101-d8_512x512_20k_voc12aug.py
    │   ├── deeplabv3plus_r101-d8_512x512_40k_voc12aug.py
    │   ├── deeplabv3plus_r101-d8_512x512_80k_ade20k.py
    │   ├── deeplabv3plus_r101-d8_769x769_40k_cityscapes.py
    │   ├── deeplabv3plus_r101-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r18-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3plus_r50-d8_480x480_40k_pascal_context.py
    │   ├── deeplabv3plus_r50-d8_480x480_80k_pascal_context.py
    │   ├── deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py
    │   ├── deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_r50-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3plus_r50-d8_512x512_20k_voc12aug.py
    │   ├── deeplabv3plus_r50-d8_512x512_40k_voc12aug.py
    │   ├── deeplabv3plus_r50-d8_512x512_80k_ade20k.py
    │   ├── deeplabv3plus_r50-d8_769x769_40k_cityscapes.py
    │   ├── deeplabv3plus_r50-d8_769x769_80k_cityscapes.py
    │   ├── deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py
    │   └── deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py
    ├── dmnet
    │   ├── README.md
    │   ├── dmnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── dmnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── dmnet_r101-d8_512x512_160k_ade20k.py
    │   ├── dmnet_r101-d8_512x512_80k_ade20k.py
    │   ├── dmnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── dmnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── dmnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── dmnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── dmnet_r50-d8_512x512_160k_ade20k.py
    │   ├── dmnet_r50-d8_512x512_80k_ade20k.py
    │   ├── dmnet_r50-d8_769x769_40k_cityscapes.py
    │   └── dmnet_r50-d8_769x769_80k_cityscapes.py
    ├── dnlnet
    │   ├── README.md
    │   ├── dnl_r101-d8_512x1024_40k_cityscapes.py
    │   ├── dnl_r101-d8_512x1024_80k_cityscapes.py
    │   ├── dnl_r101-d8_512x512_160k_ade20k.py
    │   ├── dnl_r101-d8_512x512_80k_ade20k.py
    │   ├── dnl_r101-d8_769x769_40k_cityscapes.py
    │   ├── dnl_r101-d8_769x769_80k_cityscapes.py
    │   ├── dnl_r50-d8_512x1024_40k_cityscapes.py
    │   ├── dnl_r50-d8_512x1024_80k_cityscapes.py
    │   ├── dnl_r50-d8_512x512_160k_ade20k.py
    │   ├── dnl_r50-d8_512x512_80k_ade20k.py
    │   ├── dnl_r50-d8_769x769_40k_cityscapes.py
    │   └── dnl_r50-d8_769x769_80k_cityscapes.py
    ├── emanet
    │   ├── README.md
    │   ├── emanet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── emanet_r101-d8_769x769_80k_cityscapes.py
    │   ├── emanet_r50-d8_512x1024_80k_cityscapes.py
    │   └── emanet_r50-d8_769x769_80k_cityscapes.py
    ├── encnet
    │   ├── README.md
    │   ├── encnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── encnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── encnet_r101-d8_512x512_160k_ade20k.py
    │   ├── encnet_r101-d8_512x512_20k_voc12aug.py
    │   ├── encnet_r101-d8_512x512_40k_voc12aug.py
    │   ├── encnet_r101-d8_512x512_80k_ade20k.py
    │   ├── encnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── encnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── encnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── encnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── encnet_r50-d8_512x512_160k_ade20k.py
    │   ├── encnet_r50-d8_512x512_20k_voc12aug.py
    │   ├── encnet_r50-d8_512x512_40k_voc12aug.py
    │   ├── encnet_r50-d8_512x512_80k_ade20k.py
    │   ├── encnet_r50-d8_769x769_40k_cityscapes.py
    │   ├── encnet_r50-d8_769x769_80k_cityscapes.py
    │   └── encnet_r50s-d8_512x512_80k_ade20k.py
    ├── fastscnn
    │   ├── README.md
    │   └── fast_scnn_4x8_80k_lr0.12_cityscapes.py
    ├── fcn
    │   ├── README.md
    │   ├── fcn_r101-d8_480x480_40k_pascal_context.py
    │   ├── fcn_r101-d8_480x480_80k_pascal_context.py
    │   ├── fcn_r101-d8_512x1024_40k_cityscapes.py
    │   ├── fcn_r101-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_r101-d8_512x512_160k_ade20k.py
    │   ├── fcn_r101-d8_512x512_20k_voc12aug.py
    │   ├── fcn_r101-d8_512x512_40k_voc12aug.py
    │   ├── fcn_r101-d8_512x512_80k_ade20k.py
    │   ├── fcn_r101-d8_769x769_40k_cityscapes.py
    │   ├── fcn_r101-d8_769x769_80k_cityscapes.py
    │   ├── fcn_r101b-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_r101b-d8_769x769_80k_cityscapes.py
    │   ├── fcn_r18-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_r18-d8_769x769_80k_cityscapes.py
    │   ├── fcn_r18b-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_r18b-d8_769x769_80k_cityscapes.py
    │   ├── fcn_r50-d8_480x480_40k_pascal_context.py
    │   ├── fcn_r50-d8_480x480_80k_pascal_context.py
    │   ├── fcn_r50-d8_512x1024_40k_cityscapes.py
    │   ├── fcn_r50-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_r50-d8_512x512_160k_ade20k.py
    │   ├── fcn_r50-d8_512x512_20k_voc12aug.py
    │   ├── fcn_r50-d8_512x512_40k_voc12aug.py
    │   ├── fcn_r50-d8_512x512_80k_ade20k.py
    │   ├── fcn_r50-d8_769x769_40k_cityscapes.py
    │   ├── fcn_r50-d8_769x769_80k_cityscapes.py
    │   ├── fcn_r50b-d8_512x1024_80k_cityscapes.py
    │   └── fcn_r50b-d8_769x769_80k_cityscapes.py
    ├── fp16
    │   ├── README.md
    │   ├── deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py
    │   ├── deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py
    │   ├── fcn_r101-d8_512x1024_80k_fp16_cityscapes.py
    │   └── pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py
    ├── gcnet
    │   ├── README.md
    │   ├── gcnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── gcnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── gcnet_r101-d8_512x512_160k_ade20k.py
    │   ├── gcnet_r101-d8_512x512_20k_voc12aug.py
    │   ├── gcnet_r101-d8_512x512_40k_voc12aug.py
    │   ├── gcnet_r101-d8_512x512_80k_ade20k.py
    │   ├── gcnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── gcnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── gcnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── gcnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── gcnet_r50-d8_512x512_160k_ade20k.py
    │   ├── gcnet_r50-d8_512x512_20k_voc12aug.py
    │   ├── gcnet_r50-d8_512x512_40k_voc12aug.py
    │   ├── gcnet_r50-d8_512x512_80k_ade20k.py
    │   ├── gcnet_r50-d8_769x769_40k_cityscapes.py
    │   └── gcnet_r50-d8_769x769_80k_cityscapes.py
    ├── hrnet
    │   ├── README.md
    │   ├── fcn_hr18_480x480_40k_pascal_context.py
    │   ├── fcn_hr18_480x480_80k_pascal_context.py
    │   ├── fcn_hr18_512x1024_160k_cityscapes.py
    │   ├── fcn_hr18_512x1024_40k_cityscapes.py
    │   ├── fcn_hr18_512x1024_80k_cityscapes.py
    │   ├── fcn_hr18_512x512_160k_ade20k.py
    │   ├── fcn_hr18_512x512_20k_voc12aug.py
    │   ├── fcn_hr18_512x512_40k_voc12aug.py
    │   ├── fcn_hr18_512x512_80k_ade20k.py
    │   ├── fcn_hr18s_480x480_40k_pascal_context.py
    │   ├── fcn_hr18s_480x480_80k_pascal_context.py
    │   ├── fcn_hr18s_512x1024_160k_cityscapes.py
    │   ├── fcn_hr18s_512x1024_40k_cityscapes.py
    │   ├── fcn_hr18s_512x1024_80k_cityscapes.py
    │   ├── fcn_hr18s_512x512_160k_ade20k.py
    │   ├── fcn_hr18s_512x512_20k_voc12aug.py
    │   ├── fcn_hr18s_512x512_40k_voc12aug.py
    │   ├── fcn_hr18s_512x512_80k_ade20k.py
    │   ├── fcn_hr48_480x480_40k_pascal_context.py
    │   ├── fcn_hr48_480x480_80k_pascal_context.py
    │   ├── fcn_hr48_512x1024_160k_cityscapes.py
    │   ├── fcn_hr48_512x1024_40k_cityscapes.py
    │   ├── fcn_hr48_512x1024_80k_cityscapes.py
    │   ├── fcn_hr48_512x512_160k_ade20k.py
    │   ├── fcn_hr48_512x512_20k_voc12aug.py
    │   ├── fcn_hr48_512x512_40k_voc12aug.py
    │   └── fcn_hr48_512x512_80k_ade20k.py
    ├── mobilenet_v2
    │   ├── README.md
    │   ├── deeplabv3_m-v2-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_m-v2-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_m-v2-d8_512x512_160k_ade20k.py
    │   ├── fcn_m-v2-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_m-v2-d8_512x512_160k_ade20k.py
    │   ├── pspnet_m-v2-d8_512x1024_80k_cityscapes.py
    │   └── pspnet_m-v2-d8_512x512_160k_ade20k.py
    ├── mobilenet_v3
    │   ├── README.md
    │   ├── lraspp_m-v3-d8_512x1024_320k_cityscapes.py
    │   ├── lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py
    │   ├── lraspp_m-v3s-d8_512x1024_320k_cityscapes.py
    │   └── lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py
    ├── nonlocal_net
    │   ├── README.md
    │   ├── nonlocal_r101-d8_512x1024_40k_cityscapes.py
    │   ├── nonlocal_r101-d8_512x1024_80k_cityscapes.py
    │   ├── nonlocal_r101-d8_512x512_160k_ade20k.py
    │   ├── nonlocal_r101-d8_512x512_20k_voc12aug.py
    │   ├── nonlocal_r101-d8_512x512_40k_voc12aug.py
    │   ├── nonlocal_r101-d8_512x512_80k_ade20k.py
    │   ├── nonlocal_r101-d8_769x769_40k_cityscapes.py
    │   ├── nonlocal_r101-d8_769x769_80k_cityscapes.py
    │   ├── nonlocal_r50-d8_512x1024_40k_cityscapes.py
    │   ├── nonlocal_r50-d8_512x1024_80k_cityscapes.py
    │   ├── nonlocal_r50-d8_512x512_160k_ade20k.py
    │   ├── nonlocal_r50-d8_512x512_20k_voc12aug.py
    │   ├── nonlocal_r50-d8_512x512_40k_voc12aug.py
    │   ├── nonlocal_r50-d8_512x512_80k_ade20k.py
    │   ├── nonlocal_r50-d8_769x769_40k_cityscapes.py
    │   └── nonlocal_r50-d8_769x769_80k_cityscapes.py
    ├── ocrnet
    │   ├── README.md
    │   ├── ocrnet_hr18_512x1024_160k_cityscapes.py
    │   ├── ocrnet_hr18_512x1024_40k_cityscapes.py
    │   ├── ocrnet_hr18_512x1024_80k_cityscapes.py
    │   ├── ocrnet_hr18_512x512_160k_ade20k.py
    │   ├── ocrnet_hr18_512x512_20k_voc12aug.py
    │   ├── ocrnet_hr18_512x512_40k_voc12aug.py
    │   ├── ocrnet_hr18_512x512_80k_ade20k.py
    │   ├── ocrnet_hr18s_512x1024_160k_cityscapes.py
    │   ├── ocrnet_hr18s_512x1024_40k_cityscapes.py
    │   ├── ocrnet_hr18s_512x1024_80k_cityscapes.py
    │   ├── ocrnet_hr18s_512x512_160k_ade20k.py
    │   ├── ocrnet_hr18s_512x512_20k_voc12aug.py
    │   ├── ocrnet_hr18s_512x512_40k_voc12aug.py
    │   ├── ocrnet_hr18s_512x512_80k_ade20k.py
    │   ├── ocrnet_hr48_512x1024_160k_cityscapes.py
    │   ├── ocrnet_hr48_512x1024_40k_cityscapes.py
    │   ├── ocrnet_hr48_512x1024_80k_cityscapes.py
    │   ├── ocrnet_hr48_512x512_160k_ade20k.py
    │   ├── ocrnet_hr48_512x512_20k_voc12aug.py
    │   ├── ocrnet_hr48_512x512_40k_voc12aug.py
    │   ├── ocrnet_hr48_512x512_80k_ade20k.py
    │   ├── ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py
    │   ├── ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py
    │   └── ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py
    ├── point_rend
    │   ├── README.md
    │   ├── pointrend_r101_512x1024_80k_cityscapes.py
    │   ├── pointrend_r101_512x512_160k_ade20k.py
    │   ├── pointrend_r50_512x1024_80k_cityscapes.py
    │   └── pointrend_r50_512x512_160k_ade20k.py
    ├── psanet
    │   ├── README.md
    │   ├── psanet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── psanet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── psanet_r101-d8_512x512_160k_ade20k.py
    │   ├── psanet_r101-d8_512x512_20k_voc12aug.py
    │   ├── psanet_r101-d8_512x512_40k_voc12aug.py
    │   ├── psanet_r101-d8_512x512_80k_ade20k.py
    │   ├── psanet_r101-d8_769x769_40k_cityscapes.py
    │   ├── psanet_r101-d8_769x769_80k_cityscapes.py
    │   ├── psanet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── psanet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── psanet_r50-d8_512x512_160k_ade20k.py
    │   ├── psanet_r50-d8_512x512_20k_voc12aug.py
    │   ├── psanet_r50-d8_512x512_40k_voc12aug.py
    │   ├── psanet_r50-d8_512x512_80k_ade20k.py
    │   ├── psanet_r50-d8_769x769_40k_cityscapes.py
    │   └── psanet_r50-d8_769x769_80k_cityscapes.py
    ├── pspnet
    │   ├── README.md
    │   ├── pspnet_r101-d8_480x480_40k_pascal_context.py
    │   ├── pspnet_r101-d8_480x480_80k_pascal_context.py
    │   ├── pspnet_r101-d8_512x1024_40k_cityscapes.py
    │   ├── pspnet_r101-d8_512x1024_80k_cityscapes.py
    │   ├── pspnet_r101-d8_512x512_160k_ade20k.py
    │   ├── pspnet_r101-d8_512x512_20k_voc12aug.py
    │   ├── pspnet_r101-d8_512x512_40k_voc12aug.py
    │   ├── pspnet_r101-d8_512x512_80k_ade20k.py
    │   ├── pspnet_r101-d8_769x769_40k_cityscapes.py
    │   ├── pspnet_r101-d8_769x769_80k_cityscapes.py
    │   ├── pspnet_r101b-d8_512x1024_80k_cityscapes.py
    │   ├── pspnet_r101b-d8_769x769_80k_cityscapes.py
    │   ├── pspnet_r18-d8_512x1024_80k_cityscapes.py
    │   ├── pspnet_r18-d8_769x769_80k_cityscapes.py
    │   ├── pspnet_r18b-d8_512x1024_80k_cityscapes.py
    │   ├── pspnet_r18b-d8_769x769_80k_cityscapes.py
    │   ├── pspnet_r50-d8_480x480_40k_pascal_context.py
    │   ├── pspnet_r50-d8_480x480_80k_pascal_context.py
    │   ├── pspnet_r50-d8_512x1024_40k_cityscapes.py
    │   ├── pspnet_r50-d8_512x1024_80k_cityscapes.py
    │   ├── pspnet_r50-d8_512x512_160k_ade20k.py
    │   ├── pspnet_r50-d8_512x512_20k_voc12aug.py
    │   ├── pspnet_r50-d8_512x512_40k_voc12aug.py
    │   ├── pspnet_r50-d8_512x512_80k_ade20k.py
    │   ├── pspnet_r50-d8_769x769_40k_cityscapes.py
    │   ├── pspnet_r50-d8_769x769_80k_cityscapes.py
    │   ├── pspnet_r50b-d8_512x1024_80k_cityscapes.py
    │   └── pspnet_r50b-d8_769x769_80k_cityscapes.py
    ├── resnest
    │   ├── README.md
    │   ├── deeplabv3_s101-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3_s101-d8_512x512_160k_ade20k.py
    │   ├── deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py
    │   ├── deeplabv3plus_s101-d8_512x512_160k_ade20k.py
    │   ├── fcn_s101-d8_512x1024_80k_cityscapes.py
    │   ├── fcn_s101-d8_512x512_160k_ade20k.py
    │   ├── pspnet_s101-d8_512x1024_80k_cityscapes.py
    │   └── pspnet_s101-d8_512x512_160k_ade20k.py
    ├── sem_fpn
    │   ├── README.md
    │   ├── fpn_r101_512x512_80k_ade20k.py
    │   ├── fpn_r18_512x512_80k_ade20k.py
    │   ├── fpn_r50_512x512_80k_ade20k.py
    │   ├── fpn_x101324d_512x512_80k_ade20k.py
    │   └── fpn_x101644d_512x512_80k_ade20k.py
    ├── unet
    │   ├── README.md
    │   ├── deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py
    │   ├── deeplabv3_unet_s5-d16_128x128_40k_stare.py
    │   ├── deeplabv3_unet_s5-d16_256x256_40k_hrf.py
    │   ├── deeplabv3_unet_s5-d16_64x64_40k_drive.py
    │   ├── fcn_unet_s5-d16_128x128_40k_chase_db1.py
    │   ├── fcn_unet_s5-d16_128x128_40k_stare.py
    │   ├── fcn_unet_s5-d16_256x256_40k_hrf.py
    │   ├── fcn_unet_s5-d16_64x64_40k_drive.py
    │   ├── pspnet_unet_s5-d16_128x128_40k_chase_db1.py
    │   ├── pspnet_unet_s5-d16_128x128_40k_stare.py
    │   ├── pspnet_unet_s5-d16_256x256_40k_hrf.py
    │   └── pspnet_unet_s5-d16_64x64_40k_drive.py
    └── upernet
    │   ├── README.md
    │   ├── upernet_r101_512x1024_40k_cityscapes.py
    │   ├── upernet_r101_512x1024_80k_cityscapes.py
    │   ├── upernet_r101_512x512_160k_ade20k.py
    │   ├── upernet_r101_512x512_20k_voc12aug.py
    │   ├── upernet_r101_512x512_40k_voc12aug.py
    │   ├── upernet_r101_512x512_80k_ade20k.py
    │   ├── upernet_r101_769x769_40k_cityscapes.py
    │   ├── upernet_r101_769x769_80k_cityscapes.py
    │   ├── upernet_r50_512x1024_40k_cityscapes.py
    │   ├── upernet_r50_512x1024_80k_cityscapes.py
    │   ├── upernet_r50_512x512_160k_ade20k.py
    │   ├── upernet_r50_512x512_20k_voc12aug.py
    │   ├── upernet_r50_512x512_40k_voc12aug.py
    │   ├── upernet_r50_512x512_80k_ade20k.py
    │   ├── upernet_r50_769x769_40k_cityscapes.py
    │   └── upernet_r50_769x769_80k_cityscapes.py
├── demo
    ├── MMSegmentation_Tutorial.ipynb
    ├── demo.png
    ├── image_demo.py
    └── inference_demo.ipynb
├── docker
    └── Dockerfile
├── docs
    ├── Makefile
    ├── api.rst
    ├── changelog.md
    ├── conf.py
    ├── dataset_prepare.md
    ├── get_started.md
    ├── index.rst
    ├── inference.md
    ├── make.bat
    ├── model_zoo.md
    ├── stat.py
    ├── train.md
    ├── tutorials
    │   ├── config.md
    │   ├── customize_datasets.md
    │   ├── customize_models.md
    │   ├── customize_runtime.md
    │   ├── data_pipeline.md
    │   ├── index.rst
    │   └── training_tricks.md
    └── useful_tools.md
├── local_configs
    ├── _base_
    │   ├── datasets
    │   │   ├── ade20k.py
    │   │   ├── ade20k_repeat.py
    │   │   ├── chase_db1.py
    │   │   ├── cityscapes.py
    │   │   ├── cityscapes_1024x1024_repeat.py
    │   │   ├── cityscapes_768x768_repeat.py
    │   │   ├── cityscapes_repeat.py
    │   │   ├── drive.py
    │   │   ├── hrf.py
    │   │   ├── mapillary_1024x1024_repeat.py
    │   │   ├── mapillary_768x768_repeat.py
    │   │   ├── pascal_context.py
    │   │   ├── pascal_voc12.py
    │   │   ├── pascal_voc12_aug.py
    │   │   └── stare.py
    │   ├── default_runtime.py
    │   ├── models
    │   │   ├── ann_r50-d8.py
    │   │   ├── apcnet_r50-d8.py
    │   │   ├── ccnet_r50-d8.py
    │   │   ├── cgnet.py
    │   │   ├── danet_r50-d8.py
    │   │   ├── deeplabv3_r50-d8.py
    │   │   ├── deeplabv3_unet_s5-d16.py
    │   │   ├── deeplabv3plus_r50-d8.py
    │   │   ├── dmnet_r50-d8.py
    │   │   ├── dnl_r50-d8.py
    │   │   ├── emanet_r50-d8.py
    │   │   ├── encnet_r50-d8.py
    │   │   ├── fast_scnn.py
    │   │   ├── fcn_hr18.py
    │   │   ├── fcn_r50-d8.py
    │   │   ├── fcn_unet_s5-d16.py
    │   │   ├── fpn_r50.py
    │   │   ├── gcnet_r50-d8.py
    │   │   ├── lraspp_m-v3-d8.py
    │   │   ├── nonlocal_r50-d8.py
    │   │   ├── ocrnet_hr18.py
    │   │   ├── ocrnet_r50-d8.py
    │   │   ├── pointrend_r50.py
    │   │   ├── psanet_r50-d8.py
    │   │   ├── pspnet_r50-d8.py
    │   │   ├── pspnet_unet_s5-d16.py
    │   │   ├── segformer.py
    │   │   └── upernet_r50.py
    │   └── schedules
    │   │   ├── schedule_160k.py
    │   │   ├── schedule_160k_adamw.py
    │   │   ├── schedule_20k.py
    │   │   ├── schedule_40k.py
    │   │   ├── schedule_40k_adamw.py
    │   │   ├── schedule_80k.py
    │   │   └── schedule_80k_adamw.py
    └── segformer
    │   ├── B0
    │       ├── segformer.b0.1024x1024.city.160k.py
    │       ├── segformer.b0.512x1024.city.160k.py
    │       ├── segformer.b0.512x512.ade.160k.py
    │       ├── segformer.b0.640x1280.city.160k.py
    │       └── segformer.b0.768x768.city.160k.py
    │   ├── B1
    │       ├── segformer.b1.1024x1024.city.160k.py
    │       └── segformer.b1.512x512.ade.160k.py
    │   ├── B2
    │       ├── segformer.b2.1024x1024.city.160k.py
    │       └── segformer.b2.512x512.ade.160k.py
    │   ├── B3
    │       ├── segformer.b3.1024x1024.city.160k.py
    │       └── segformer.b3.512x512.ade.160k.py
    │   ├── B4
    │       ├── segformer.b4.1024x1024.city.160k.py
    │       └── segformer.b4.512x512.ade.160k.py
    │   └── B5
    │       ├── segformer.b5.1024x1024.city.160k.py
    │       └── segformer.b5.640x640.ade.160k.py
├── mmseg
    ├── __init__.py
    ├── apis
    │   ├── __init__.py
    │   ├── inference.py
    │   ├── test.py
    │   └── train.py
    ├── core
    │   ├── __init__.py
    │   ├── evaluation
    │   │   ├── __init__.py
    │   │   ├── class_names.py
    │   │   ├── eval_hooks.py
    │   │   └── metrics.py
    │   ├── seg
    │   │   ├── __init__.py
    │   │   ├── builder.py
    │   │   └── sampler
    │   │   │   ├── __init__.py
    │   │   │   ├── base_pixel_sampler.py
    │   │   │   └── ohem_pixel_sampler.py
    │   └── utils
    │   │   ├── __init__.py
    │   │   └── misc.py
    ├── datasets
    │   ├── __init__.py
    │   ├── ade.py
    │   ├── builder.py
    │   ├── chase_db1.py
    │   ├── cityscapes.py
    │   ├── cocostuff.py
    │   ├── custom.py
    │   ├── dataset_wrappers.py
    │   ├── drive.py
    │   ├── hrf.py
    │   ├── mapillary.py
    │   ├── pascal_context.py
    │   ├── pipelines
    │   │   ├── __init__.py
    │   │   ├── compose.py
    │   │   ├── formating.py
    │   │   ├── loading.py
    │   │   ├── test_time_aug.py
    │   │   └── transforms.py
    │   ├── stare.py
    │   └── voc.py
    ├── models
    │   ├── __init__.py
    │   ├── backbones
    │   │   ├── __init__.py
    │   │   ├── cgnet.py
    │   │   ├── fast_scnn.py
    │   │   ├── hrnet.py
    │   │   ├── mix_transformer.py
    │   │   ├── mobilenet_v2.py
    │   │   ├── mobilenet_v3.py
    │   │   ├── resnest.py
    │   │   ├── resnet.py
    │   │   ├── resnext.py
    │   │   └── unet.py
    │   ├── builder.py
    │   ├── decode_heads
    │   │   ├── __init__.py
    │   │   ├── ann_head.py
    │   │   ├── apc_head.py
    │   │   ├── aspp_head.py
    │   │   ├── cascade_decode_head.py
    │   │   ├── cc_head.py
    │   │   ├── da_head.py
    │   │   ├── decode_head.py
    │   │   ├── dm_head.py
    │   │   ├── dnl_head.py
    │   │   ├── ema_head.py
    │   │   ├── enc_head.py
    │   │   ├── fcn_head.py
    │   │   ├── fpn_head.py
    │   │   ├── gc_head.py
    │   │   ├── lraspp_head.py
    │   │   ├── nl_head.py
    │   │   ├── ocr_head.py
    │   │   ├── point_head.py
    │   │   ├── psa_head.py
    │   │   ├── psp_head.py
    │   │   ├── segformer_head.py
    │   │   ├── sep_aspp_head.py
    │   │   ├── sep_fcn_head.py
    │   │   └── uper_head.py
    │   ├── losses
    │   │   ├── __init__.py
    │   │   ├── accuracy.py
    │   │   ├── cross_entropy_loss.py
    │   │   ├── lovasz_loss.py
    │   │   └── utils.py
    │   ├── necks
    │   │   ├── __init__.py
    │   │   └── fpn.py
    │   ├── segmentors
    │   │   ├── __init__.py
    │   │   ├── base.py
    │   │   ├── cascade_encoder_decoder.py
    │   │   └── encoder_decoder.py
    │   └── utils
    │   │   ├── __init__.py
    │   │   ├── drop.py
    │   │   ├── inverted_residual.py
    │   │   ├── make_divisible.py
    │   │   ├── norm.py
    │   │   ├── res_layer.py
    │   │   ├── se_layer.py
    │   │   ├── self_attention_block.py
    │   │   └── up_conv_block.py
    ├── ops
    │   ├── __init__.py
    │   ├── encoding.py
    │   └── wrappers.py
    ├── utils
    │   ├── __init__.py
    │   ├── collect_env.py
    │   └── logger.py
    └── version.py
├── pytest.ini
├── requirements.txt
├── requirements
    ├── docs.txt
    ├── optional.txt
    ├── readthedocs.txt
    ├── runtime.txt
    └── tests.txt
├── resources
    ├── image.png
    ├── mmseg-logo.png
    └── seg_demo.gif
├── setup.cfg
├── setup.py
├── tests
    ├── test_config.py
    ├── test_data
    │   ├── test_dataset.py
    │   ├── test_dataset_builder.py
    │   ├── test_loading.py
    │   ├── test_transform.py
    │   └── test_tta.py
    ├── test_eval_hook.py
    ├── test_inference.py
    ├── test_metrics.py
    ├── test_models
    │   ├── test_backbone.py
    │   ├── test_forward.py
    │   ├── test_heads.py
    │   ├── test_losses.py
    │   ├── test_necks.py
    │   ├── test_segmentor.py
    │   └── test_unet.py
    ├── test_sampler.py
    └── test_utils
    │   ├── test_inverted_residual_module.py
    │   ├── test_make_divisible.py
    │   └── test_se_layer.py
└── tools
    ├── benchmark.py
    ├── convert_datasets
        ├── chase_db1.py
        ├── cityscapes.py
        ├── drive.py
        ├── hrf.py
        ├── pascal_context.py
        ├── stare.py
        └── voc_aug.py
    ├── convert_model.py
    ├── dist_test.sh
    ├── dist_train.sh
    ├── get_flops.py
    ├── print_config.py
    ├── publish_model.py
    ├── pytorch2onnx.py
    ├── slurm_test.sh
    ├── slurm_train.sh
    ├── test.py
    └── train.py


/configs/_base_/datasets/cityscapes_768x768.py:
--------------------------------------------------------------------------------
 1 | _base_ = './cityscapes.py'
 2 | img_norm_cfg = dict(
 3 |     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
 4 | crop_size = (768, 768)
 5 | train_pipeline = [
 6 |     dict(type='LoadImageFromFile'),
 7 |     dict(type='LoadAnnotations'),
 8 |     dict(type='Resize', img_scale=(2049, 1025), ratio_range=(0.5, 2.0)),
 9 |     dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
10 |     dict(type='RandomFlip', prob=0.5),
11 |     dict(type='PhotoMetricDistortion'),
12 |     dict(type='Normalize', **img_norm_cfg),
13 |     dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255),
14 |     dict(type='DefaultFormatBundle'),
15 |     dict(type='Collect', keys=['img', 'gt_semantic_seg']),
16 | ]
17 | test_pipeline = [
18 |     dict(type='LoadImageFromFile'),
19 |     dict(
20 |         type='MultiScaleFlipAug',
21 |         img_scale=(2049, 1025),
22 |         # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
23 |         flip=False,
24 |         transforms=[
25 |             dict(type='Resize', keep_ratio=True),
26 |             dict(type='RandomFlip'),
27 |             dict(type='Normalize', **img_norm_cfg),
28 |             dict(type='ImageToTensor', keys=['img']),
29 |             dict(type='Collect', keys=['img']),
30 |         ])
31 | ]
32 | data = dict(
33 |     train=dict(pipeline=train_pipeline),
34 |     val=dict(pipeline=test_pipeline),
35 |     test=dict(pipeline=test_pipeline))
36 | 


--------------------------------------------------------------------------------
/configs/_base_/datasets/cityscapes_769x769.py:
--------------------------------------------------------------------------------
 1 | _base_ = './cityscapes.py'
 2 | img_norm_cfg = dict(
 3 |     mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
 4 | crop_size = (769, 769)
 5 | train_pipeline = [
 6 |     dict(type='LoadImageFromFile'),
 7 |     dict(type='LoadAnnotations'),
 8 |     dict(type='Resize', img_scale=(2049, 1025), ratio_range=(0.5, 2.0)),
 9 |     dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
10 |     dict(type='RandomFlip', prob=0.5),
11 |     dict(type='PhotoMetricDistortion'),
12 |     dict(type='Normalize', **img_norm_cfg),
13 |     dict(type='Pad', size=crop_size, pad_val=0, seg_pad_val=255),
14 |     dict(type='DefaultFormatBundle'),
15 |     dict(type='Collect', keys=['img', 'gt_semantic_seg']),
16 | ]
17 | test_pipeline = [
18 |     dict(type='LoadImageFromFile'),
19 |     dict(
20 |         type='MultiScaleFlipAug',
21 |         img_scale=(2049, 1025),
22 |         # img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
23 |         flip=False,
24 |         transforms=[
25 |             dict(type='Resize', keep_ratio=True),
26 |             dict(type='RandomFlip'),
27 |             dict(type='Normalize', **img_norm_cfg),
28 |             dict(type='ImageToTensor', keys=['img']),
29 |             dict(type='Collect', keys=['img']),
30 |         ])
31 | ]
32 | data = dict(
33 |     train=dict(pipeline=train_pipeline),
34 |     val=dict(pipeline=test_pipeline),
35 |     test=dict(pipeline=test_pipeline))
36 | 


--------------------------------------------------------------------------------
/configs/_base_/datasets/pascal_voc12_aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pascal_voc12.py'
 2 | # dataset settings
 3 | data = dict(
 4 |     train=dict(
 5 |         ann_dir=['SegmentationClass', 'SegmentationClassAug'],
 6 |         split=[
 7 |             'ImageSets/Segmentation/train.txt',
 8 |             'ImageSets/Segmentation/aug.txt'
 9 |         ]))
10 | 


--------------------------------------------------------------------------------
/configs/_base_/default_runtime.py:
--------------------------------------------------------------------------------
 1 | # yapf:disable
 2 | log_config = dict(
 3 |     interval=50,
 4 |     hooks=[
 5 |         dict(type='TextLoggerHook', by_epoch=False),
 6 |         # dict(type='TensorboardLoggerHook')
 7 |     ])
 8 | # yapf:enable
 9 | dist_params = dict(backend='nccl')
10 | log_level = 'INFO'
11 | load_from = None
12 | resume_from = None
13 | workflow = [('train', 1)]
14 | cudnn_benchmark = True
15 | 


--------------------------------------------------------------------------------
/configs/_base_/models/cgnet.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', eps=1e-03, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     backbone=dict(
 6 |         type='CGNet',
 7 |         norm_cfg=norm_cfg,
 8 |         in_channels=3,
 9 |         num_channels=(32, 64, 128),
10 |         num_blocks=(3, 21),
11 |         dilations=(2, 4),
12 |         reductions=(8, 16)),
13 |     decode_head=dict(
14 |         type='FCNHead',
15 |         in_channels=256,
16 |         in_index=2,
17 |         channels=256,
18 |         num_convs=0,
19 |         concat_input=False,
20 |         dropout_ratio=0,
21 |         num_classes=19,
22 |         norm_cfg=norm_cfg,
23 |         loss_decode=dict(
24 |             type='CrossEntropyLoss',
25 |             use_sigmoid=False,
26 |             loss_weight=1.0,
27 |             class_weight=[
28 |                 2.5959933, 6.7415504, 3.5354059, 9.8663225, 9.690899, 9.369352,
29 |                 10.289121, 9.953208, 4.3097677, 9.490387, 7.674431, 9.396905,
30 |                 10.347791, 6.3927646, 10.226669, 10.241062, 10.280587,
31 |                 10.396974, 10.055647
32 |             ])),
33 |     # model training and testing settings
34 |     train_cfg=dict(sampler=None),
35 |     test_cfg=dict(mode='whole'))
36 | 


--------------------------------------------------------------------------------
/configs/_base_/models/fpn_r50.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     pretrained='open-mmlab://resnet50_v1c',
 6 |     backbone=dict(
 7 |         type='ResNetV1c',
 8 |         depth=50,
 9 |         num_stages=4,
10 |         out_indices=(0, 1, 2, 3),
11 |         dilations=(1, 1, 1, 1),
12 |         strides=(1, 2, 2, 2),
13 |         norm_cfg=norm_cfg,
14 |         norm_eval=False,
15 |         style='pytorch',
16 |         contract_dilation=True),
17 |     neck=dict(
18 |         type='FPN',
19 |         in_channels=[256, 512, 1024, 2048],
20 |         out_channels=256,
21 |         num_outs=4),
22 |     decode_head=dict(
23 |         type='FPNHead',
24 |         in_channels=[256, 256, 256, 256],
25 |         in_index=[0, 1, 2, 3],
26 |         feature_strides=[4, 8, 16, 32],
27 |         channels=128,
28 |         dropout_ratio=0.1,
29 |         num_classes=19,
30 |         norm_cfg=norm_cfg,
31 |         align_corners=False,
32 |         loss_decode=dict(
33 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
34 |     # model training and testing settings
35 |     train_cfg=dict(),
36 |     test_cfg=dict(mode='whole'))
37 | 


--------------------------------------------------------------------------------
/configs/_base_/models/lraspp_m-v3-d8.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', eps=0.001, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     backbone=dict(
 6 |         type='MobileNetV3',
 7 |         arch='large',
 8 |         out_indices=(1, 3, 16),
 9 |         norm_cfg=norm_cfg),
10 |     decode_head=dict(
11 |         type='LRASPPHead',
12 |         in_channels=(16, 24, 960),
13 |         in_index=(0, 1, 2),
14 |         channels=128,
15 |         input_transform='multiple_select',
16 |         dropout_ratio=0.1,
17 |         num_classes=19,
18 |         norm_cfg=norm_cfg,
19 |         act_cfg=dict(type='ReLU'),
20 |         align_corners=False,
21 |         loss_decode=dict(
22 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
23 |     # model training and testing settings
24 |     train_cfg=dict(),
25 |     test_cfg=dict(mode='whole'))
26 | 


--------------------------------------------------------------------------------
/configs/_base_/schedules/schedule_160k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=160000)
 8 | checkpoint_config = dict(by_epoch=False, interval=16000)
 9 | evaluation = dict(interval=16000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/configs/_base_/schedules/schedule_20k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=20000)
 8 | checkpoint_config = dict(by_epoch=False, interval=2000)
 9 | evaluation = dict(interval=2000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/configs/_base_/schedules/schedule_40k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=40000)
 8 | checkpoint_config = dict(by_epoch=False, interval=4000)
 9 | evaluation = dict(interval=4000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/configs/_base_/schedules/schedule_80k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=80000)
 8 | checkpoint_config = dict(by_epoch=False, interval=8000)
 9 | evaluation = dict(interval=8000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ann_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
7 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
7 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ann_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ann_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/ann/ann_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ann_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './apcnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/apcnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/apcnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/apcnet/apcnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/apcnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './ccnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ccnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ccnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/ccnet/ccnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ccnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './danet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/danet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/danet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/danet/danet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/danet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_512x1024_40k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet101_v1c',
 4 |     backbone=dict(
 5 |         depth=101,
 6 |         dilations=(1, 1, 1, 2),
 7 |         strides=(1, 2, 2, 1),
 8 |         multi_grid=(1, 2, 4)),
 9 |     decode_head=dict(
10 |         dilations=(1, 6, 12, 18),
11 |         sampler=dict(type='OHEMPixelSampler', min_kept=100000)))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d16-mg124_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet101_v1c',
 4 |     backbone=dict(
 5 |         depth=101,
 6 |         dilations=(1, 1, 1, 2),
 7 |         strides=(1, 2, 2, 1),
 8 |         multi_grid=(1, 2, 4)),
 9 |     decode_head=dict(
10 |         dilations=(1, 6, 12, 18),
11 |         sampler=dict(type='OHEMPixelSampler', min_kept=100000)))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_480x480_40k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_480x480_80k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r101b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r18b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r18b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60),
 8 |     auxiliary_head=dict(num_classes=60),
 9 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
10 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
11 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60),
 8 |     auxiliary_head=dict(num_classes=60),
 9 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
10 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
11 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3/deeplabv3_r50b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet101_v1c',
 4 |     backbone=dict(
 5 |         depth=101,
 6 |         dilations=(1, 1, 1, 2),
 7 |         strides=(1, 2, 2, 1),
 8 |         multi_grid=(1, 2, 4)),
 9 |     decode_head=dict(
10 |         dilations=(1, 6, 12, 18),
11 |         sampler=dict(type='OHEMPixelSampler', min_kept=100000)))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet101_v1c',
 4 |     backbone=dict(
 5 |         depth=101,
 6 |         dilations=(1, 1, 1, 2),
 7 |         strides=(1, 2, 2, 1),
 8 |         multi_grid=(1, 2, 4)),
 9 |     decode_head=dict(
10 |         dilations=(1, 6, 12, 18),
11 |         sampler=dict(type='OHEMPixelSampler', min_kept=100000)))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_480x480_40k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_480x480_80k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         c1_in_channels=64,
 7 |         c1_channels=12,
 8 |         in_channels=512,
 9 |         channels=128,
10 |     ),
11 |     auxiliary_head=dict(in_channels=256, channels=64))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         c1_in_channels=64,
 7 |         c1_channels=12,
 8 |         in_channels=512,
 9 |         channels=128,
10 |     ),
11 |     auxiliary_head=dict(in_channels=256, channels=64))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         c1_in_channels=64,
 7 |         c1_channels=12,
 8 |         in_channels=512,
 9 |         channels=128,
10 |     ),
11 |     auxiliary_head=dict(in_channels=256, channels=64))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         c1_in_channels=64,
 7 |         c1_channels=12,
 8 |         in_channels=512,
 9 |         channels=128,
10 |     ),
11 |     auxiliary_head=dict(in_channels=256, channels=64))
12 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60),
 8 |     auxiliary_head=dict(num_classes=60),
 9 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
10 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
11 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60),
 8 |     auxiliary_head=dict(num_classes=60),
 9 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
10 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
11 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
3 |     '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
3 |     '../_base_/datasets/cityscapes.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_80k.py'
5 | ]
6 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3plus_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/deeplabv3plus_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './deeplabv3plus_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dmnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dmnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/dmnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/dmnet/dmnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/dmnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './dnl_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/dnl_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/dnl_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/dnlnet/dnl_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/dnl_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | optimizer = dict(
11 |     paramwise_cfg=dict(
12 |         custom_keys=dict(theta=dict(wd_mult=0.), phi=dict(wd_mult=0.))))
13 | 


--------------------------------------------------------------------------------
/configs/emanet/emanet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './emanet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/emanet/emanet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './emanet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/emanet/emanet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/emanet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/emanet/emanet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/emanet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './encnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/encnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/encnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/encnet/encnet_r50s-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/encnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     backbone=dict(stem_channels=128),
7 |     decode_head=dict(num_classes=150),
8 |     auxiliary_head=dict(num_classes=150))
9 | 


--------------------------------------------------------------------------------
/configs/fastscnn/fast_scnn_4x8_80k_lr0.12_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/fast_scnn.py', '../_base_/datasets/cityscapes.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
 4 | ]
 5 | 
 6 | # Re-config the data sampler.
 7 | data = dict(samples_per_gpu=2, workers_per_gpu=4)
 8 | 
 9 | # Re-config the optimizer.
10 | optimizer = dict(type='SGD', lr=0.12, momentum=0.9, weight_decay=4e-5)
11 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_480x480_40k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_480x480_80k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r101b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r18-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r18-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r18b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r18b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=60),
7 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
9 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_context.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=60),
7 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
9 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
7 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
7 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/fcn_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/fcn_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/fcn/fcn_r50b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './fcn_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py'
2 | # fp16 settings
3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
4 | 


--------------------------------------------------------------------------------
/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py'
2 | # fp16 settings
3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
4 | 


--------------------------------------------------------------------------------
/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py'
2 | # fp16 settings
3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
4 | 


--------------------------------------------------------------------------------
/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py'
2 | # fp16 settings
3 | optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
4 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './gcnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/gcnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/gcnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/gcnet/gcnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/gcnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=60),
7 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
9 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_context.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=60),
7 |     test_cfg=dict(mode='slide', crop_size=(480, 480), stride=(320, 320)))
8 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
9 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x1024_160k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(decode_head=dict(num_classes=150))
6 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_20k.py'
4 | ]
5 | model = dict(decode_head=dict(num_classes=21))
6 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/pascal_voc12_aug.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(decode_head=dict(num_classes=21))
6 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_hr18.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(decode_head=dict(num_classes=150))
6 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_480x480_40k_pascal_context.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_480x480_80k_pascal_context.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x1024_160k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_160k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_40k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_20k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_40k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr18s_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_80k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_480x480_40k_pascal_context.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_480x480_80k_pascal_context.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x1024_160k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_160k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_40k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_20k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_40k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/hrnet/fcn_hr48_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './fcn_hr18_512x512_80k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w48',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage2=dict(num_channels=(48, 96)),
 7 |             stage3=dict(num_channels=(48, 96, 192)),
 8 |             stage4=dict(num_channels=(48, 96, 192, 384)))),
 9 |     decode_head=dict(
10 |         in_channels=[48, 96, 192, 384], channels=sum([48, 96, 192, 384])))
11 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/deeplabv3_m-v2-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/deeplabv3_m-v2-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320, c1_in_channels=24),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/deeplabv3plus_m-v2-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320, c1_in_channels=24),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/fcn_m-v2-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/fcn_m-v2-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../fcn/fcn_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/pspnet_m-v2-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v2/pspnet_m-v2-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../pspnet/pspnet_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='mmcls://mobilenet_v2',
 4 |     backbone=dict(
 5 |         _delete_=True,
 6 |         type='MobileNetV2',
 7 |         widen_factor=1.,
 8 |         strides=(1, 2, 2, 1, 1, 1, 1),
 9 |         dilations=(1, 1, 1, 2, 2, 4, 4),
10 |         out_indices=(1, 2, 4, 6)),
11 |     decode_head=dict(in_channels=320),
12 |     auxiliary_head=dict(in_channels=96))
13 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/lraspp_m-v3-d8.py', '../_base_/datasets/cityscapes.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
 4 | ]
 5 | 
 6 | model = dict(pretrained='open-mmlab://contrib/mobilenet_v3_large')
 7 | 
 8 | # Re-config the data sampler.
 9 | data = dict(samples_per_gpu=4, workers_per_gpu=4)
10 | 
11 | runner = dict(type='IterBasedRunner', max_iters=320000)
12 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/lraspp_m-v3-d8.py', '../_base_/datasets/cityscapes.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
 4 | ]
 5 | 
 6 | # Re-config the data sampler.
 7 | data = dict(samples_per_gpu=4, workers_per_gpu=4)
 8 | 
 9 | runner = dict(type='IterBasedRunner', max_iters=320000)
10 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v3/lraspp_m-v3s-d8_512x1024_320k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './lraspp_m-v3-d8_512x1024_320k_cityscapes.py'
 2 | norm_cfg = dict(type='SyncBN', eps=0.001, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     pretrained='open-mmlab://contrib/mobilenet_v3_small',
 6 |     backbone=dict(
 7 |         type='MobileNetV3',
 8 |         arch='small',
 9 |         out_indices=(0, 1, 12),
10 |         norm_cfg=norm_cfg),
11 |     decode_head=dict(
12 |         type='LRASPPHead',
13 |         in_channels=(16, 16, 576),
14 |         in_index=(0, 1, 2),
15 |         channels=128,
16 |         input_transform='multiple_select',
17 |         dropout_ratio=0.1,
18 |         num_classes=19,
19 |         norm_cfg=norm_cfg,
20 |         act_cfg=dict(type='ReLU'),
21 |         align_corners=False,
22 |         loss_decode=dict(
23 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)))
24 | 


--------------------------------------------------------------------------------
/configs/mobilenet_v3/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py'
 2 | norm_cfg = dict(type='SyncBN', eps=0.001, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     backbone=dict(
 6 |         type='MobileNetV3',
 7 |         arch='small',
 8 |         out_indices=(0, 1, 12),
 9 |         norm_cfg=norm_cfg),
10 |     decode_head=dict(
11 |         type='LRASPPHead',
12 |         in_channels=(16, 16, 576),
13 |         in_index=(0, 1, 2),
14 |         channels=128,
15 |         input_transform='multiple_select',
16 |         dropout_ratio=0.1,
17 |         num_classes=19,
18 |         norm_cfg=norm_cfg,
19 |         act_cfg=dict(type='ReLU'),
20 |         align_corners=False,
21 |         loss_decode=dict(
22 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)))
23 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './nonlocal_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/nonlocal_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/nonlocal_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/nonlocal_net/nonlocal_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/nonlocal_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x1024_160k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/ade20k.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
 4 | ]
 5 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 6 | model = dict(decode_head=[
 7 |     dict(
 8 |         type='FCNHead',
 9 |         in_channels=[18, 36, 72, 144],
10 |         channels=sum([18, 36, 72, 144]),
11 |         in_index=(0, 1, 2, 3),
12 |         input_transform='resize_concat',
13 |         kernel_size=1,
14 |         num_convs=1,
15 |         concat_input=False,
16 |         dropout_ratio=-1,
17 |         num_classes=150,
18 |         norm_cfg=norm_cfg,
19 |         align_corners=False,
20 |         loss_decode=dict(
21 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
22 |     dict(
23 |         type='OCRHead',
24 |         in_channels=[18, 36, 72, 144],
25 |         in_index=(0, 1, 2, 3),
26 |         input_transform='resize_concat',
27 |         channels=512,
28 |         ocr_channels=256,
29 |         dropout_ratio=-1,
30 |         num_classes=150,
31 |         norm_cfg=norm_cfg,
32 |         align_corners=False,
33 |         loss_decode=dict(
34 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
35 | ])
36 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ocrnet_hr18.py',
 3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_20k.py'
 5 | ]
 6 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 7 | model = dict(decode_head=[
 8 |     dict(
 9 |         type='FCNHead',
10 |         in_channels=[18, 36, 72, 144],
11 |         channels=sum([18, 36, 72, 144]),
12 |         in_index=(0, 1, 2, 3),
13 |         input_transform='resize_concat',
14 |         kernel_size=1,
15 |         num_convs=1,
16 |         concat_input=False,
17 |         dropout_ratio=-1,
18 |         num_classes=21,
19 |         norm_cfg=norm_cfg,
20 |         align_corners=False,
21 |         loss_decode=dict(
22 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
23 |     dict(
24 |         type='OCRHead',
25 |         in_channels=[18, 36, 72, 144],
26 |         in_index=(0, 1, 2, 3),
27 |         input_transform='resize_concat',
28 |         channels=512,
29 |         ocr_channels=256,
30 |         dropout_ratio=-1,
31 |         num_classes=21,
32 |         norm_cfg=norm_cfg,
33 |         align_corners=False,
34 |         loss_decode=dict(
35 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
36 | ])
37 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ocrnet_hr18.py',
 3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 7 | model = dict(decode_head=[
 8 |     dict(
 9 |         type='FCNHead',
10 |         in_channels=[18, 36, 72, 144],
11 |         channels=sum([18, 36, 72, 144]),
12 |         in_index=(0, 1, 2, 3),
13 |         input_transform='resize_concat',
14 |         kernel_size=1,
15 |         num_convs=1,
16 |         concat_input=False,
17 |         dropout_ratio=-1,
18 |         num_classes=21,
19 |         norm_cfg=norm_cfg,
20 |         align_corners=False,
21 |         loss_decode=dict(
22 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
23 |     dict(
24 |         type='OCRHead',
25 |         in_channels=[18, 36, 72, 144],
26 |         in_index=(0, 1, 2, 3),
27 |         input_transform='resize_concat',
28 |         channels=512,
29 |         ocr_channels=256,
30 |         dropout_ratio=-1,
31 |         num_classes=21,
32 |         norm_cfg=norm_cfg,
33 |         align_corners=False,
34 |         loss_decode=dict(
35 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
36 | ])
37 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/ocrnet_hr18.py', '../_base_/datasets/ade20k.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
 4 | ]
 5 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 6 | model = dict(decode_head=[
 7 |     dict(
 8 |         type='FCNHead',
 9 |         in_channels=[18, 36, 72, 144],
10 |         channels=sum([18, 36, 72, 144]),
11 |         in_index=(0, 1, 2, 3),
12 |         input_transform='resize_concat',
13 |         kernel_size=1,
14 |         num_convs=1,
15 |         concat_input=False,
16 |         dropout_ratio=-1,
17 |         num_classes=150,
18 |         norm_cfg=norm_cfg,
19 |         align_corners=False,
20 |         loss_decode=dict(
21 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=0.4)),
22 |     dict(
23 |         type='OCRHead',
24 |         in_channels=[18, 36, 72, 144],
25 |         in_index=(0, 1, 2, 3),
26 |         input_transform='resize_concat',
27 |         channels=512,
28 |         ocr_channels=256,
29 |         dropout_ratio=-1,
30 |         num_classes=150,
31 |         norm_cfg=norm_cfg,
32 |         align_corners=False,
33 |         loss_decode=dict(
34 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
35 | ])
36 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x1024_160k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x1024_160k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x1024_40k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x512_20k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x512_40k_voc12aug.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_hr18s_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = './ocrnet_hr18_512x512_80k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://msra/hrnetv2_w18_small',
 4 |     backbone=dict(
 5 |         extra=dict(
 6 |             stage1=dict(num_blocks=(2, )),
 7 |             stage2=dict(num_blocks=(2, 2)),
 8 |             stage3=dict(num_modules=3, num_blocks=(2, 2, 2)),
 9 |             stage4=dict(num_modules=2, num_blocks=(2, 2, 2, 2)))))
10 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
6 | optimizer = dict(lr=0.02)
7 | lr_config = dict(min_lr=2e-4)
8 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
6 | 


--------------------------------------------------------------------------------
/configs/ocrnet/ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/ocrnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
6 | optimizer = dict(lr=0.02)
7 | lr_config = dict(min_lr=2e-4)
8 | 


--------------------------------------------------------------------------------
/configs/point_rend/pointrend_r101_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pointrend_r50_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/point_rend/pointrend_r101_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './pointrend_r50_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/point_rend/pointrend_r50_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pointrend_r50.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | lr_config = dict(warmup='linear', warmup_iters=200)
6 | 


--------------------------------------------------------------------------------
/configs/point_rend/pointrend_r50_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/pointrend_r50.py', '../_base_/datasets/ade20k.py',
 3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
 4 | ]
 5 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 6 | model = dict(decode_head=[
 7 |     dict(
 8 |         type='FPNHead',
 9 |         in_channels=[256, 256, 256, 256],
10 |         in_index=[0, 1, 2, 3],
11 |         feature_strides=[4, 8, 16, 32],
12 |         channels=128,
13 |         dropout_ratio=-1,
14 |         num_classes=150,
15 |         norm_cfg=norm_cfg,
16 |         align_corners=False,
17 |         loss_decode=dict(
18 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
19 |     dict(
20 |         type='PointHead',
21 |         in_channels=[256],
22 |         in_index=[0],
23 |         channels=256,
24 |         num_fcs=3,
25 |         coarse_pred_each_layer=True,
26 |         dropout_ratio=-1,
27 |         num_classes=150,
28 |         align_corners=False,
29 |         loss_decode=dict(
30 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0))
31 | ])
32 | lr_config = dict(warmup='linear', warmup_iters=200)
33 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './psanet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(mask_size=(66, 66), num_classes=150),
7 |     auxiliary_head=dict(num_classes=150))
8 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/psanet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(mask_size=(66, 66), num_classes=150),
7 |     auxiliary_head=dict(num_classes=150))
8 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/psanet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/psanet/psanet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/psanet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_480x480_40k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_480x480_80k_pascal_context.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r101b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(
3 |     pretrained='torchvision://resnet101',
4 |     backbone=dict(type='ResNet', depth=101))
5 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r18-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnet18_v1c',
 4 |     backbone=dict(depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r18b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r18b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='torchvision://resnet18',
 4 |     backbone=dict(type='ResNet', depth=18),
 5 |     decode_head=dict(
 6 |         in_channels=512,
 7 |         channels=128,
 8 |     ),
 9 |     auxiliary_head=dict(in_channels=256, channels=64))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_480x480_40k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/pspnet_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
 8 | test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
 9 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_480x480_80k_pascal_context.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/pspnet_r50-d8.py',
 3 |     '../_base_/datasets/pascal_context.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(num_classes=60), auxiliary_head=dict(num_classes=60))
 8 | test_cfg = dict(mode='slide', crop_size=(480, 480), stride=(320, 320))
 9 | optimizer = dict(type='SGD', lr=0.004, momentum=0.9, weight_decay=0.0001)
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/pspnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/pspnet_r50-d8.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50b-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/pspnet/pspnet_r50b-d8_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './pspnet_r50-d8_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='torchvision://resnet50', backbone=dict(type='ResNet'))
3 | 


--------------------------------------------------------------------------------
/configs/resnest/deeplabv3_s101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/deeplabv3_s101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3/deeplabv3_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/deeplabv3plus_s101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/deeplabv3plus_s101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/fcn_s101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/fcn_s101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../fcn/fcn_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/pspnet_s101-d8_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/resnest/pspnet_s101-d8_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = '../pspnet/pspnet_r101-d8_512x512_160k_ade20k.py'
 2 | model = dict(
 3 |     pretrained='open-mmlab://resnest101',
 4 |     backbone=dict(
 5 |         type='ResNeSt',
 6 |         stem_channels=128,
 7 |         radix=2,
 8 |         reduction_factor=4,
 9 |         avg_down_stride=True))
10 | 


--------------------------------------------------------------------------------
/configs/sem_fpn/fpn_r101_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fpn_r50_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/sem_fpn/fpn_r18_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fpn_r50_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet18_v1c',
3 |              backbone=dict(depth=18),
4 |              neck=dict(in_channels=[64, 128, 256, 512]))
5 | 


--------------------------------------------------------------------------------
/configs/sem_fpn/fpn_r50_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/fpn_r50.py',
 3 |     '../_base_/datasets/ade20k.py',
 4 |     '../_base_/default_runtime.py'
 5 | ]
 6 | model = dict(decode_head=dict(num_classes=150))
 7 | 
 8 | gpu_factor = 2 #mmseg默认4卡训练 我这边8卡的话 lr*2, iter/2
 9 | # optimizer
10 | optimizer = dict(type='SGD', lr=0.01*gpu_factor, momentum=0.9, weight_decay=0.0005)
11 | optimizer_config = dict()
12 | # learning policy
13 | lr_config = dict(policy='poly', power=0.9, min_lr=0.0, by_epoch=False)
14 | # runtime settings
15 | runner = dict(type='IterBasedRunner', max_iters=80000//gpu_factor)
16 | checkpoint_config = dict(by_epoch=False, interval=8000//gpu_factor)
17 | evaluation = dict(interval=8000, metric='mIoU')
18 | 
19 | 


--------------------------------------------------------------------------------
/configs/sem_fpn/fpn_x101324d_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fpn_r50_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnext101_32x4d',
3 |              backbone=dict(
4 |                  type='ResNeXt',
5 |                  depth=101,
6 |                  groups=32,
7 |                  base_width=4))
8 | 


--------------------------------------------------------------------------------
/configs/sem_fpn/fpn_x101644d_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './fpn_r50_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnext101_64x4d',
3 |              backbone=dict(
4 |                  type='ResNeXt',
5 |                  depth=101,
6 |                  groups=64,
7 |                  base_width=4))
8 | 


--------------------------------------------------------------------------------
/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_chase_db1.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_unet_s5-d16.py',
3 |     '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
7 | evaluation = dict(metric='mDice')
8 | 


--------------------------------------------------------------------------------
/configs/unet/deeplabv3_unet_s5-d16_128x128_40k_stare.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/stare.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/deeplabv3_unet_s5-d16_256x256_40k_hrf.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/hrf.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/deeplabv3_unet_s5-d16_64x64_40k_drive.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/deeplabv3_unet_s5-d16.py', '../_base_/datasets/drive.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/fcn_unet_s5-d16_128x128_40k_chase_db1.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/chase_db1.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/fcn_unet_s5-d16_128x128_40k_stare.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/stare.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/fcn_unet_s5-d16_256x256_40k_hrf.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/hrf.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/fcn_unet_s5-d16_64x64_40k_drive.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/fcn_unet_s5-d16.py', '../_base_/datasets/drive.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/pspnet_unet_s5-d16_128x128_40k_chase_db1.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_unet_s5-d16.py',
3 |     '../_base_/datasets/chase_db1.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
7 | evaluation = dict(metric='mDice')
8 | 


--------------------------------------------------------------------------------
/configs/unet/pspnet_unet_s5-d16_128x128_40k_stare.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/stare.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(128, 128), stride=(85, 85)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/pspnet_unet_s5-d16_256x256_40k_hrf.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/hrf.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(256, 256), stride=(170, 170)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/unet/pspnet_unet_s5-d16_64x64_40k_drive.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/pspnet_unet_s5-d16.py', '../_base_/datasets/drive.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | model = dict(test_cfg=dict(crop_size=(64, 64), stride=(42, 42)))
6 | evaluation = dict(metric='mDice')
7 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x1024_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x1024_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x512_160k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x512_20k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x512_40k_voc12aug.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_512x512_80k_ade20k.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_769x769_40k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r101_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = './upernet_r50_769x769_80k_cityscapes.py'
2 | model = dict(pretrained='open-mmlab://resnet101_v1c', backbone=dict(depth=101))
3 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x1024_40k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_40k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x1024_80k_cityscapes.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py', '../_base_/datasets/cityscapes.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x512_160k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x512_20k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_20k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x512_40k_voc12aug.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py',
3 |     '../_base_/datasets/pascal_voc12_aug.py', '../_base_/default_runtime.py',
4 |     '../_base_/schedules/schedule_40k.py'
5 | ]
6 | model = dict(
7 |     decode_head=dict(num_classes=21), auxiliary_head=dict(num_classes=21))
8 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_512x512_80k_ade20k.py:
--------------------------------------------------------------------------------
1 | _base_ = [
2 |     '../_base_/models/upernet_r50.py', '../_base_/datasets/ade20k.py',
3 |     '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
4 | ]
5 | model = dict(
6 |     decode_head=dict(num_classes=150), auxiliary_head=dict(num_classes=150))
7 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_769x769_40k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/upernet_r50.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_40k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/configs/upernet/upernet_r50_769x769_80k_cityscapes.py:
--------------------------------------------------------------------------------
 1 | _base_ = [
 2 |     '../_base_/models/upernet_r50.py',
 3 |     '../_base_/datasets/cityscapes_769x769.py', '../_base_/default_runtime.py',
 4 |     '../_base_/schedules/schedule_80k.py'
 5 | ]
 6 | model = dict(
 7 |     decode_head=dict(align_corners=True),
 8 |     auxiliary_head=dict(align_corners=True),
 9 |     test_cfg=dict(mode='slide', crop_size=(769, 769), stride=(513, 513)))
10 | 


--------------------------------------------------------------------------------
/demo/demo.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVlabs/SegFormer/65fa8cfa9b52b6ee7e8897a98705abf8570f9e32/demo/demo.png


--------------------------------------------------------------------------------
/demo/image_demo.py:
--------------------------------------------------------------------------------
 1 | from argparse import ArgumentParser
 2 | 
 3 | from mmseg.apis import inference_segmentor, init_segmentor, show_result_pyplot
 4 | from mmseg.core.evaluation import get_palette
 5 | 
 6 | 
 7 | def main():
 8 |     parser = ArgumentParser()
 9 |     parser.add_argument('img', help='Image file')
10 |     parser.add_argument('config', help='Config file')
11 |     parser.add_argument('checkpoint', help='Checkpoint file')
12 |     parser.add_argument(
13 |         '--device', default='cuda:0', help='Device used for inference')
14 |     parser.add_argument(
15 |         '--palette',
16 |         default='cityscapes',
17 |         help='Color palette used for segmentation map')
18 |     args = parser.parse_args()
19 | 
20 |     # build the model from a config file and a checkpoint file
21 |     model = init_segmentor(args.config, args.checkpoint, device=args.device)
22 |     # test a single image
23 |     result = inference_segmentor(model, args.img)
24 |     # show the results
25 |     show_result_pyplot(model, args.img, result, get_palette(args.palette))
26 | 
27 | 
28 | if __name__ == '__main__':
29 |     main()
30 | 


--------------------------------------------------------------------------------
/docker/Dockerfile:
--------------------------------------------------------------------------------
 1 | ARG PYTORCH="1.6.0"
 2 | ARG CUDA="10.1"
 3 | ARG CUDNN="7"
 4 | 
 5 | FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
 6 | 
 7 | ENV TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0+PTX"
 8 | ENV TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
 9 | ENV CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
10 | 
11 | RUN apt-get update && apt-get install -y git ninja-build libglib2.0-0 libsm6 libxrender-dev libxext6 \
12 |  && apt-get clean \
13 |  && rm -rf /var/lib/apt/lists/*
14 | 
15 | # Install mmsegmentation
16 | RUN conda clean --all
17 | 
18 | RUN pip install mmcv-full==latest+torch1.6.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
19 | RUN git clone https://github.com/open-mmlab/mmsegmenation.git /mmsegmentation
20 | WORKDIR /mmsegmentation
21 | RUN pip install -r requirements/build.txt
22 | RUN pip install --no-cache-dir -e .
23 | 


--------------------------------------------------------------------------------
/docs/Makefile:
--------------------------------------------------------------------------------
 1 | # Minimal makefile for Sphinx documentation
 2 | #
 3 | 
 4 | # You can set these variables from the command line, and also
 5 | # from the environment for the first two.
 6 | SPHINXOPTS    ?=
 7 | SPHINXBUILD   ?= sphinx-build
 8 | SOURCEDIR     = .
 9 | BUILDDIR      = _build
10 | 
11 | # Put it first so that "make" without argument is like "make help".
12 | help:
13 | 	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
14 | 
15 | .PHONY: help Makefile
16 | 
17 | # Catch-all target: route all unknown targets to Sphinx using the new
18 | # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
19 | %: Makefile
20 | 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
21 | 


--------------------------------------------------------------------------------
/docs/api.rst:
--------------------------------------------------------------------------------
 1 | API Reference
 2 | ==============
 3 | 
 4 | mmseg.apis
 5 | --------------
 6 | .. automodule:: mmseg.apis
 7 |     :members:
 8 | 
 9 | mmseg.core
10 | --------------
11 | 
12 | seg
13 | ^^^^^^^^^^
14 | .. automodule:: mmseg.core.seg
15 |     :members:
16 | 
17 | evaluation
18 | ^^^^^^^^^^
19 | .. automodule:: mmseg.core.evaluation
20 |     :members:
21 | 
22 | utils
23 | ^^^^^^^^^^
24 | .. automodule:: mmseg.core.utils
25 |     :members:
26 | 
27 | mmseg.datasets
28 | --------------
29 | 
30 | datasets
31 | ^^^^^^^^^^
32 | .. automodule:: mmseg.datasets
33 |     :members:
34 | 
35 | pipelines
36 | ^^^^^^^^^^
37 | .. automodule:: mmseg.datasets.pipelines
38 |     :members:
39 | 
40 | mmseg.models
41 | --------------
42 | 
43 | segmentors
44 | ^^^^^^^^^^
45 | .. automodule:: mmseg.models.segmentors
46 |     :members:
47 | 
48 | backbones
49 | ^^^^^^^^^^
50 | .. automodule:: mmseg.models.backbones
51 |     :members:
52 | 
53 | decode_heads
54 | ^^^^^^^^^^^^
55 | .. automodule:: mmseg.models.decode_heads
56 |     :members:
57 | 
58 | losses
59 | ^^^^^^^^^^
60 | .. automodule:: mmseg.models.losses
61 |     :members:
62 | 


--------------------------------------------------------------------------------
/docs/index.rst:
--------------------------------------------------------------------------------
 1 | Welcome to MMSegmenation's documentation!
 2 | =======================================
 3 | 
 4 | .. toctree::
 5 |    :maxdepth: 2
 6 |    :caption: Get Started
 7 | 
 8 |    get_started.md
 9 | 
10 | .. toctree::
11 |    :maxdepth: 1
12 |    :caption: Dataset Preparation
13 | 
14 |    dataset_prepare.md
15 | 
16 | .. toctree::
17 |    :maxdepth: 1
18 |    :caption: Model Zoo
19 | 
20 |    model_zoo.md
21 |    modelzoo_statistics.md
22 | 
23 | .. toctree::
24 |    :maxdepth: 2
25 |    :caption: Quick Run
26 | 
27 |    train.md
28 |    inference.md
29 | 
30 | .. toctree::
31 |    :maxdepth: 2
32 |    :caption: Tutorials
33 | 
34 |    tutorials/index.rst
35 | 
36 | .. toctree::
37 |    :maxdepth: 2
38 |    :caption: Useful Tools and Scripts
39 | 
40 |    useful_tools.md
41 | 
42 | .. toctree::
43 |    :maxdepth: 2
44 |    :caption: Notes
45 | 
46 |    changelog.md
47 | 
48 | .. toctree::
49 |    :caption: API Reference
50 | 
51 |    api.rst
52 | 
53 | Indices and tables
54 | ==================
55 | 
56 | * :ref:`genindex`
57 | * :ref:`search`
58 | 


--------------------------------------------------------------------------------
/docs/make.bat:
--------------------------------------------------------------------------------
 1 | @ECHO OFF
 2 | 
 3 | pushd %~dp0
 4 | 
 5 | REM Command file for Sphinx documentation
 6 | 
 7 | if "%SPHINXBUILD%" == "" (
 8 | 	set SPHINXBUILD=sphinx-build
 9 | )
10 | set SOURCEDIR=.
11 | set BUILDDIR=_build
12 | 
13 | if "%1" == "" goto help
14 | 
15 | %SPHINXBUILD% >NUL 2>NUL
16 | if errorlevel 9009 (
17 | 	echo.
18 | 	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
19 | 	echo.installed, then set the SPHINXBUILD environment variable to point
20 | 	echo.to the full path of the 'sphinx-build' executable. Alternatively you
21 | 	echo.may add the Sphinx directory to PATH.
22 | 	echo.
23 | 	echo.If you don't have Sphinx installed, grab it from
24 | 	echo.http://sphinx-doc.org/
25 | 	exit /b 1
26 | )
27 | 
28 | %SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
29 | goto end
30 | 
31 | :help
32 | %SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
33 | 
34 | :end
35 | popd
36 | 


--------------------------------------------------------------------------------
/docs/tutorials/index.rst:
--------------------------------------------------------------------------------
 1 | .. toctree::
 2 |    :maxdepth: 2
 3 | 
 4 |    config.md
 5 |    customize_datasets.md
 6 |    data_pipeline.md
 7 |    customize_models.md
 8 |    training_tricks.md
 9 |    customize_runtime.md
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/datasets/pascal_voc12_aug.py:
--------------------------------------------------------------------------------
 1 | _base_ = './pascal_voc12.py'
 2 | # dataset settings
 3 | data = dict(
 4 |     train=dict(
 5 |         ann_dir=['SegmentationClass', 'SegmentationClassAug'],
 6 |         split=[
 7 |             'ImageSets/Segmentation/train.txt',
 8 |             'ImageSets/Segmentation/aug.txt'
 9 |         ]))
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/default_runtime.py:
--------------------------------------------------------------------------------
 1 | # yapf:disable
 2 | log_config = dict(
 3 |     interval=50,
 4 |     hooks=[
 5 |         dict(type='TextLoggerHook', by_epoch=False),
 6 |         # dict(type='TensorboardLoggerHook')
 7 |     ])
 8 | # yapf:enable
 9 | dist_params = dict(backend='nccl')
10 | log_level = 'INFO'
11 | load_from = None
12 | resume_from = None
13 | workflow = [('train', 1)]
14 | cudnn_benchmark = True
15 | 


--------------------------------------------------------------------------------
/local_configs/_base_/models/cgnet.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', eps=1e-03, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     backbone=dict(
 6 |         type='CGNet',
 7 |         norm_cfg=norm_cfg,
 8 |         in_channels=3,
 9 |         num_channels=(32, 64, 128),
10 |         num_blocks=(3, 21),
11 |         dilations=(2, 4),
12 |         reductions=(8, 16)),
13 |     decode_head=dict(
14 |         type='FCNHead',
15 |         in_channels=256,
16 |         in_index=2,
17 |         channels=256,
18 |         num_convs=0,
19 |         concat_input=False,
20 |         dropout_ratio=0,
21 |         num_classes=19,
22 |         norm_cfg=norm_cfg,
23 |         loss_decode=dict(
24 |             type='CrossEntropyLoss',
25 |             use_sigmoid=False,
26 |             loss_weight=1.0,
27 |             class_weight=[
28 |                 2.5959933, 6.7415504, 3.5354059, 9.8663225, 9.690899, 9.369352,
29 |                 10.289121, 9.953208, 4.3097677, 9.490387, 7.674431, 9.396905,
30 |                 10.347791, 6.3927646, 10.226669, 10.241062, 10.280587,
31 |                 10.396974, 10.055647
32 |             ])),
33 |     # model training and testing settings
34 |     train_cfg=dict(sampler=None),
35 |     test_cfg=dict(mode='whole'))
36 | 


--------------------------------------------------------------------------------
/local_configs/_base_/models/fpn_r50.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     pretrained='open-mmlab://resnet50_v1c',
 6 |     backbone=dict(
 7 |         type='ResNetV1c',
 8 |         depth=50,
 9 |         num_stages=4,
10 |         out_indices=(0, 1, 2, 3),
11 |         dilations=(1, 1, 1, 1),
12 |         strides=(1, 2, 2, 2),
13 |         norm_cfg=norm_cfg,
14 |         norm_eval=False,
15 |         style='pytorch',
16 |         contract_dilation=True),
17 |     neck=dict(
18 |         type='FPN',
19 |         in_channels=[256, 512, 1024, 2048],
20 |         out_channels=256,
21 |         num_outs=4),
22 |     decode_head=dict(
23 |         type='FPNHead',
24 |         in_channels=[256, 256, 256, 256],
25 |         in_index=[0, 1, 2, 3],
26 |         feature_strides=[4, 8, 16, 32],
27 |         channels=128,
28 |         dropout_ratio=0.1,
29 |         num_classes=19,
30 |         norm_cfg=norm_cfg,
31 |         align_corners=False,
32 |         loss_decode=dict(
33 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
34 |     # model training and testing settings
35 |     train_cfg=dict(),
36 |     test_cfg=dict(mode='whole'))
37 | 


--------------------------------------------------------------------------------
/local_configs/_base_/models/lraspp_m-v3-d8.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', eps=0.001, requires_grad=True)
 3 | model = dict(
 4 |     type='EncoderDecoder',
 5 |     backbone=dict(
 6 |         type='MobileNetV3',
 7 |         arch='large',
 8 |         out_indices=(1, 3, 16),
 9 |         norm_cfg=norm_cfg),
10 |     decode_head=dict(
11 |         type='LRASPPHead',
12 |         in_channels=(16, 24, 960),
13 |         in_index=(0, 1, 2),
14 |         channels=128,
15 |         input_transform='multiple_select',
16 |         dropout_ratio=0.1,
17 |         num_classes=19,
18 |         norm_cfg=norm_cfg,
19 |         act_cfg=dict(type='ReLU'),
20 |         align_corners=False,
21 |         loss_decode=dict(
22 |             type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
23 |     # model training and testing settings
24 |     train_cfg=dict(),
25 |     test_cfg=dict(mode='whole'))
26 | 


--------------------------------------------------------------------------------
/local_configs/_base_/models/segformer.py:
--------------------------------------------------------------------------------
 1 | # model settings
 2 | norm_cfg = dict(type='SyncBN', requires_grad=True)
 3 | find_unused_parameters = True
 4 | model = dict(
 5 |     type='EncoderDecoder',
 6 |     pretrained=None,
 7 |     backbone=dict(
 8 |         type='IMTRv21_5',
 9 |         style='pytorch'),
10 |     decode_head=dict(
11 |         type='SegFormerHead',
12 |         in_channels=[64, 128, 320, 512],
13 |         in_index=[0, 1, 2, 3],
14 |         feature_strides=[4, 8, 16, 32],
15 |         channels=128,
16 |         dropout_ratio=0.1,
17 |         num_classes=19,
18 |         norm_cfg=norm_cfg,
19 |         align_corners=False,
20 |         decoder_params=dict(),
21 |         loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
22 |     # model training and testing settings
23 |     train_cfg=dict(),
24 |     test_cfg=dict(mode='whole'))
25 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_160k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=160000)
 8 | checkpoint_config = dict(by_epoch=False, interval=16000)
 9 | evaluation = dict(interval=16000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_160k_adamw.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='AdamW', lr=0.0002, weight_decay=0.0001)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=0.0, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=160000)
 8 | checkpoint_config = dict(by_epoch=False, interval=4000)
 9 | evaluation = dict(interval=4000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_20k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=20000)
 8 | checkpoint_config = dict(by_epoch=False, interval=2000)
 9 | evaluation = dict(interval=2000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_40k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=40000)
 8 | checkpoint_config = dict(by_epoch=False, interval=4000)
 9 | evaluation = dict(interval=4000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_40k_adamw.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='AdamW', lr=0.0002, weight_decay=0.0001)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=0.0, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=40000)
 8 | checkpoint_config = dict(by_epoch=False, interval=4000)
 9 | evaluation = dict(interval=4000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_80k.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=80000)
 8 | checkpoint_config = dict(by_epoch=False, interval=8000)
 9 | evaluation = dict(interval=8000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/local_configs/_base_/schedules/schedule_80k_adamw.py:
--------------------------------------------------------------------------------
 1 | # optimizer
 2 | optimizer = dict(type='AdamW', lr=0.0002, weight_decay=0.0001)
 3 | optimizer_config = dict()
 4 | # learning policy
 5 | lr_config = dict(policy='poly', power=0.9, min_lr=0.0, by_epoch=False)
 6 | # runtime settings
 7 | runner = dict(type='IterBasedRunner', max_iters=80000)
 8 | checkpoint_config = dict(by_epoch=False, interval=4000)
 9 | evaluation = dict(interval=4000, metric='mIoU')
10 | 


--------------------------------------------------------------------------------
/mmseg/__init__.py:
--------------------------------------------------------------------------------
 1 | import mmcv
 2 | 
 3 | from .version import __version__, version_info
 4 | 
 5 | MMCV_MIN = '1.1.4'
 6 | MMCV_MAX = '1.3.0'
 7 | 
 8 | 
 9 | def digit_version(version_str):
10 |     digit_version = []
11 |     for x in version_str.split('.'):
12 |         if x.isdigit():
13 |             digit_version.append(int(x))
14 |         elif x.find('rc') != -1:
15 |             patch_version = x.split('rc')
16 |             digit_version.append(int(patch_version[0]) - 1)
17 |             digit_version.append(int(patch_version[1]))
18 |     return digit_version
19 | 
20 | 
21 | mmcv_min_version = digit_version(MMCV_MIN)
22 | mmcv_max_version = digit_version(MMCV_MAX)
23 | mmcv_version = digit_version(mmcv.__version__)
24 | 
25 | 
26 | assert (mmcv_min_version <= mmcv_version <= mmcv_max_version), \
27 |     f'MMCV=={mmcv.__version__} is used but incompatible. ' \
28 |     f'Please install mmcv>={mmcv_min_version}, <={mmcv_max_version}.'
29 | 
30 | __all__ = ['__version__', 'version_info']
31 | 


--------------------------------------------------------------------------------
/mmseg/apis/__init__.py:
--------------------------------------------------------------------------------
 1 | from .inference import inference_segmentor, init_segmentor, show_result_pyplot
 2 | from .test import multi_gpu_test, single_gpu_test
 3 | from .train import get_root_logger, set_random_seed, train_segmentor
 4 | 
 5 | __all__ = [
 6 |     'get_root_logger', 'set_random_seed', 'train_segmentor', 'init_segmentor',
 7 |     'inference_segmentor', 'multi_gpu_test', 'single_gpu_test',
 8 |     'show_result_pyplot'
 9 | ]
10 | 


--------------------------------------------------------------------------------
/mmseg/core/__init__.py:
--------------------------------------------------------------------------------
1 | from .evaluation import *  # noqa: F401, F403
2 | from .seg import *  # noqa: F401, F403
3 | from .utils import *  # noqa: F401, F403
4 | 


--------------------------------------------------------------------------------
/mmseg/core/evaluation/__init__.py:
--------------------------------------------------------------------------------
1 | from .class_names import get_classes, get_palette
2 | from .eval_hooks import DistEvalHook, EvalHook
3 | from .metrics import eval_metrics, mean_dice, mean_iou
4 | 
5 | __all__ = [
6 |     'EvalHook', 'DistEvalHook', 'mean_dice', 'mean_iou', 'eval_metrics',
7 |     'get_classes', 'get_palette'
8 | ]
9 | 


--------------------------------------------------------------------------------
/mmseg/core/seg/__init__.py:
--------------------------------------------------------------------------------
1 | from .builder import build_pixel_sampler
2 | from .sampler import BasePixelSampler, OHEMPixelSampler
3 | 
4 | __all__ = ['build_pixel_sampler', 'BasePixelSampler', 'OHEMPixelSampler']
5 | 


--------------------------------------------------------------------------------
/mmseg/core/seg/builder.py:
--------------------------------------------------------------------------------
1 | from mmcv.utils import Registry, build_from_cfg
2 | 
3 | PIXEL_SAMPLERS = Registry('pixel sampler')
4 | 
5 | 
6 | def build_pixel_sampler(cfg, **default_args):
7 |     """Build pixel sampler for segmentation map."""
8 |     return build_from_cfg(cfg, PIXEL_SAMPLERS, default_args)
9 | 


--------------------------------------------------------------------------------
/mmseg/core/seg/sampler/__init__.py:
--------------------------------------------------------------------------------
1 | from .base_pixel_sampler import BasePixelSampler
2 | from .ohem_pixel_sampler import OHEMPixelSampler
3 | 
4 | __all__ = ['BasePixelSampler', 'OHEMPixelSampler']
5 | 


--------------------------------------------------------------------------------
/mmseg/core/seg/sampler/base_pixel_sampler.py:
--------------------------------------------------------------------------------
 1 | from abc import ABCMeta, abstractmethod
 2 | 
 3 | 
 4 | class BasePixelSampler(metaclass=ABCMeta):
 5 |     """Base class of pixel sampler."""
 6 | 
 7 |     def __init__(self, **kwargs):
 8 |         pass
 9 | 
10 |     @abstractmethod
11 |     def sample(self, seg_logit, seg_label):
12 |         """Placeholder for sample function."""
13 |         pass
14 | 


--------------------------------------------------------------------------------
/mmseg/core/utils/__init__.py:
--------------------------------------------------------------------------------
1 | from .misc import add_prefix
2 | 
3 | __all__ = ['add_prefix']
4 | 


--------------------------------------------------------------------------------
/mmseg/core/utils/misc.py:
--------------------------------------------------------------------------------
 1 | def add_prefix(inputs, prefix):
 2 |     """Add prefix for dict.
 3 | 
 4 |     Args:
 5 |         inputs (dict): The input dict with str keys.
 6 |         prefix (str): The prefix to add.
 7 | 
 8 |     Returns:
 9 | 
10 |         dict: The dict with keys updated with ``prefix``.
11 |     """
12 | 
13 |     outputs = dict()
14 |     for name, value in inputs.items():
15 |         outputs[f'{prefix}.{name}'] = value
16 | 
17 |     return outputs
18 | 


--------------------------------------------------------------------------------
/mmseg/datasets/__init__.py:
--------------------------------------------------------------------------------
 1 | from .ade import ADE20KDataset
 2 | from .builder import DATASETS, PIPELINES, build_dataloader, build_dataset
 3 | from .chase_db1 import ChaseDB1Dataset
 4 | from .cityscapes import CityscapesDataset
 5 | from .custom import CustomDataset
 6 | from .dataset_wrappers import ConcatDataset, RepeatDataset
 7 | from .drive import DRIVEDataset
 8 | from .hrf import HRFDataset
 9 | from .pascal_context import PascalContextDataset
10 | from .stare import STAREDataset
11 | from .voc import PascalVOCDataset
12 | from .mapillary import MapillaryDataset
13 | from .cocostuff import CocoStuff
14 | 
15 | __all__ = [
16 |     'CustomDataset', 'build_dataloader', 'ConcatDataset', 'RepeatDataset',
17 |     'DATASETS', 'build_dataset', 'PIPELINES', 'CityscapesDataset',
18 |     'PascalVOCDataset', 'ADE20KDataset', 'PascalContextDataset',
19 |     'ChaseDB1Dataset', 'DRIVEDataset', 'HRFDataset', 'STAREDataset', 'MapillaryDataset', 'CocoStuff'
20 | ]
21 | 


--------------------------------------------------------------------------------
/mmseg/datasets/chase_db1.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | from .builder import DATASETS
 4 | from .custom import CustomDataset
 5 | 
 6 | 
 7 | @DATASETS.register_module()
 8 | class ChaseDB1Dataset(CustomDataset):
 9 |     """Chase_db1 dataset.
10 | 
11 |     In segmentation map annotation for Chase_db1, 0 stands for background,
12 |     which is included in 2 categories. ``reduce_zero_label`` is fixed to False.
13 |     The ``img_suffix`` is fixed to '.png' and ``seg_map_suffix`` is fixed to
14 |     '_1stHO.png'.
15 |     """
16 | 
17 |     CLASSES = ('background', 'vessel')
18 | 
19 |     PALETTE = [[120, 120, 120], [6, 230, 230]]
20 | 
21 |     def __init__(self, **kwargs):
22 |         super(ChaseDB1Dataset, self).__init__(
23 |             img_suffix='.png',
24 |             seg_map_suffix='_1stHO.png',
25 |             reduce_zero_label=False,
26 |             **kwargs)
27 |         assert osp.exists(self.img_dir)
28 | 


--------------------------------------------------------------------------------
/mmseg/datasets/drive.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | from .builder import DATASETS
 4 | from .custom import CustomDataset
 5 | 
 6 | 
 7 | @DATASETS.register_module()
 8 | class DRIVEDataset(CustomDataset):
 9 |     """DRIVE dataset.
10 | 
11 |     In segmentation map annotation for DRIVE, 0 stands for background, which is
12 |     included in 2 categories. ``reduce_zero_label`` is fixed to False. The
13 |     ``img_suffix`` is fixed to '.png' and ``seg_map_suffix`` is fixed to
14 |     '_manual1.png'.
15 |     """
16 | 
17 |     CLASSES = ('background', 'vessel')
18 | 
19 |     PALETTE = [[120, 120, 120], [6, 230, 230]]
20 | 
21 |     def __init__(self, **kwargs):
22 |         super(DRIVEDataset, self).__init__(
23 |             img_suffix='.png',
24 |             seg_map_suffix='_manual1.png',
25 |             reduce_zero_label=False,
26 |             **kwargs)
27 |         assert osp.exists(self.img_dir)
28 | 


--------------------------------------------------------------------------------
/mmseg/datasets/hrf.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | from .builder import DATASETS
 4 | from .custom import CustomDataset
 5 | 
 6 | 
 7 | @DATASETS.register_module()
 8 | class HRFDataset(CustomDataset):
 9 |     """HRF dataset.
10 | 
11 |     In segmentation map annotation for HRF, 0 stands for background, which is
12 |     included in 2 categories. ``reduce_zero_label`` is fixed to False. The
13 |     ``img_suffix`` is fixed to '.png' and ``seg_map_suffix`` is fixed to
14 |     '.png'.
15 |     """
16 | 
17 |     CLASSES = ('background', 'vessel')
18 | 
19 |     PALETTE = [[120, 120, 120], [6, 230, 230]]
20 | 
21 |     def __init__(self, **kwargs):
22 |         super(HRFDataset, self).__init__(
23 |             img_suffix='.png',
24 |             seg_map_suffix='.png',
25 |             reduce_zero_label=False,
26 |             **kwargs)
27 |         assert osp.exists(self.img_dir)
28 | 


--------------------------------------------------------------------------------
/mmseg/datasets/pipelines/__init__.py:
--------------------------------------------------------------------------------
 1 | from .compose import Compose
 2 | from .formating import (Collect, ImageToTensor, ToDataContainer, ToTensor,
 3 |                         Transpose, to_tensor)
 4 | from .loading import LoadAnnotations, LoadImageFromFile
 5 | from .test_time_aug import MultiScaleFlipAug
 6 | from .transforms import (AlignedResize, CLAHE, AdjustGamma, Normalize, Pad,
 7 |                          PhotoMetricDistortion, RandomCrop, RandomFlip,
 8 |                          RandomRotate, Rerange, Resize, RGB2Gray, SegRescale)
 9 | 
10 | __all__ = [
11 |     'Compose', 'to_tensor', 'ToTensor', 'ImageToTensor', 'ToDataContainer',
12 |     'Transpose', 'Collect', 'LoadAnnotations', 'LoadImageFromFile',
13 |     'MultiScaleFlipAug', 'AlignedResize', 'Resize', 'RandomFlip', 'Pad', 'RandomCrop',
14 |     'Normalize', 'SegRescale', 'PhotoMetricDistortion', 'RandomRotate',
15 |     'AdjustGamma', 'CLAHE', 'Rerange', 'RGB2Gray'
16 | ]
17 | 


--------------------------------------------------------------------------------
/mmseg/datasets/stare.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | from .builder import DATASETS
 4 | from .custom import CustomDataset
 5 | 
 6 | 
 7 | @DATASETS.register_module()
 8 | class STAREDataset(CustomDataset):
 9 |     """STARE dataset.
10 | 
11 |     In segmentation map annotation for STARE, 0 stands for background, which is
12 |     included in 2 categories. ``reduce_zero_label`` is fixed to False. The
13 |     ``img_suffix`` is fixed to '.png' and ``seg_map_suffix`` is fixed to
14 |     '.ah.png'.
15 |     """
16 | 
17 |     CLASSES = ('background', 'vessel')
18 | 
19 |     PALETTE = [[120, 120, 120], [6, 230, 230]]
20 | 
21 |     def __init__(self, **kwargs):
22 |         super(STAREDataset, self).__init__(
23 |             img_suffix='.png',
24 |             seg_map_suffix='.ah.png',
25 |             reduce_zero_label=False,
26 |             **kwargs)
27 |         assert osp.exists(self.img_dir)
28 | 


--------------------------------------------------------------------------------
/mmseg/datasets/voc.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | from .builder import DATASETS
 4 | from .custom import CustomDataset
 5 | 
 6 | 
 7 | @DATASETS.register_module()
 8 | class PascalVOCDataset(CustomDataset):
 9 |     """Pascal VOC dataset.
10 | 
11 |     Args:
12 |         split (str): Split txt file for Pascal VOC.
13 |     """
14 | 
15 |     CLASSES = ('background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle',
16 |                'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog',
17 |                'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa',
18 |                'train', 'tvmonitor')
19 | 
20 |     PALETTE = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0], [0, 0, 128],
21 |                [128, 0, 128], [0, 128, 128], [128, 128, 128], [64, 0, 0],
22 |                [192, 0, 0], [64, 128, 0], [192, 128, 0], [64, 0, 128],
23 |                [192, 0, 128], [64, 128, 128], [192, 128, 128], [0, 64, 0],
24 |                [128, 64, 0], [0, 192, 0], [128, 192, 0], [0, 64, 128]]
25 | 
26 |     def __init__(self, split, **kwargs):
27 |         super(PascalVOCDataset, self).__init__(
28 |             img_suffix='.jpg', seg_map_suffix='.png', split=split, **kwargs)
29 |         assert osp.exists(self.img_dir) and self.split is not None
30 | 


--------------------------------------------------------------------------------
/mmseg/models/__init__.py:
--------------------------------------------------------------------------------
 1 | from .backbones import *  # noqa: F401,F403
 2 | from .builder import (BACKBONES, HEADS, LOSSES, SEGMENTORS, build_backbone,
 3 |                       build_head, build_loss, build_segmentor)
 4 | from .decode_heads import *  # noqa: F401,F403
 5 | from .losses import *  # noqa: F401,F403
 6 | from .necks import *  # noqa: F401,F403
 7 | from .segmentors import *  # noqa: F401,F403
 8 | 
 9 | __all__ = [
10 |     'BACKBONES', 'HEADS', 'LOSSES', 'SEGMENTORS', 'build_backbone',
11 |     'build_head', 'build_loss', 'build_segmentor'
12 | ]
13 | 


--------------------------------------------------------------------------------
/mmseg/models/backbones/__init__.py:
--------------------------------------------------------------------------------
 1 | from .cgnet import CGNet
 2 | from .fast_scnn import FastSCNN
 3 | from .hrnet import HRNet
 4 | from .mobilenet_v2 import MobileNetV2
 5 | from .mobilenet_v3 import MobileNetV3
 6 | from .resnest import ResNeSt
 7 | from .resnet import ResNet, ResNetV1c, ResNetV1d
 8 | from .resnext import ResNeXt
 9 | from .unet import UNet
10 | 
11 | from .mix_transformer import *
12 | 
13 | __all__ = [
14 |     'ResNet', 'ResNetV1c', 'ResNetV1d', 'ResNeXt', 'HRNet', 'FastSCNN',
15 |     'ResNeSt', 'MobileNetV2', 'UNet', 'CGNet', 'MobileNetV3',]
16 | 


--------------------------------------------------------------------------------
/mmseg/models/decode_heads/__init__.py:
--------------------------------------------------------------------------------
 1 | from .ann_head import ANNHead
 2 | from .apc_head import APCHead
 3 | from .aspp_head import ASPPHead
 4 | from .cc_head import CCHead
 5 | from .da_head import DAHead
 6 | from .dm_head import DMHead
 7 | from .dnl_head import DNLHead
 8 | from .ema_head import EMAHead
 9 | from .enc_head import EncHead
10 | from .fcn_head import FCNHead
11 | from .fpn_head import FPNHead
12 | from .gc_head import GCHead
13 | from .lraspp_head import LRASPPHead
14 | from .nl_head import NLHead
15 | from .ocr_head import OCRHead
16 | from .point_head import PointHead
17 | from .psa_head import PSAHead
18 | from .psp_head import PSPHead
19 | from .sep_aspp_head import DepthwiseSeparableASPPHead
20 | from .sep_fcn_head import DepthwiseSeparableFCNHead
21 | from .uper_head import UPerHead
22 | 
23 | 
24 | from .segformer_head import SegFormerHead
25 | 
26 | __all__ = [
27 |     'FCNHead', 'PSPHead', 'ASPPHead', 'PSAHead', 'NLHead', 'GCHead', 'CCHead',
28 |     'UPerHead', 'DepthwiseSeparableASPPHead', 'ANNHead', 'DAHead', 'OCRHead',
29 |     'EncHead', 'DepthwiseSeparableFCNHead', 'FPNHead', 'EMAHead', 'DNLHead',
30 |     'PointHead', 'APCHead', 'DMHead', 'LRASPPHead',
31 |     'SegFormerHead',
32 | ]
33 | 


--------------------------------------------------------------------------------
/mmseg/models/losses/__init__.py:
--------------------------------------------------------------------------------
 1 | from .accuracy import Accuracy, accuracy
 2 | from .cross_entropy_loss import (CrossEntropyLoss, binary_cross_entropy,
 3 |                                  cross_entropy, mask_cross_entropy)
 4 | from .lovasz_loss import LovaszLoss
 5 | from .utils import reduce_loss, weight_reduce_loss, weighted_loss
 6 | 
 7 | __all__ = [
 8 |     'accuracy', 'Accuracy', 'cross_entropy', 'binary_cross_entropy',
 9 |     'mask_cross_entropy', 'CrossEntropyLoss', 'reduce_loss',
10 |     'weight_reduce_loss', 'weighted_loss', 'LovaszLoss'
11 | ]
12 | 


--------------------------------------------------------------------------------
/mmseg/models/necks/__init__.py:
--------------------------------------------------------------------------------
1 | from .fpn import FPN
2 | 
3 | __all__ = ['FPN']
4 | 


--------------------------------------------------------------------------------
/mmseg/models/segmentors/__init__.py:
--------------------------------------------------------------------------------
1 | from .cascade_encoder_decoder import CascadeEncoderDecoder
2 | from .encoder_decoder import EncoderDecoder
3 | 
4 | __all__ = ['EncoderDecoder', 'CascadeEncoderDecoder']
5 | 


--------------------------------------------------------------------------------
/mmseg/models/utils/__init__.py:
--------------------------------------------------------------------------------
 1 | from .inverted_residual import InvertedResidual, InvertedResidualV3
 2 | from .make_divisible import make_divisible
 3 | from .res_layer import ResLayer
 4 | from .self_attention_block import SelfAttentionBlock
 5 | from .up_conv_block import UpConvBlock
 6 | 
 7 | __all__ = [
 8 |     'ResLayer', 'SelfAttentionBlock', 'make_divisible', 'InvertedResidual',
 9 |     'UpConvBlock', 'InvertedResidualV3'
10 | ]
11 | 


--------------------------------------------------------------------------------
/mmseg/models/utils/make_divisible.py:
--------------------------------------------------------------------------------
 1 | def make_divisible(value, divisor, min_value=None, min_ratio=0.9):
 2 |     """Make divisible function.
 3 | 
 4 |     This function rounds the channel number to the nearest value that can be
 5 |     divisible by the divisor. It is taken from the original tf repo. It ensures
 6 |     that all layers have a channel number that is divisible by divisor. It can
 7 |     be seen here: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/mobilenet.py  # noqa
 8 | 
 9 |     Args:
10 |         value (int): The original channel number.
11 |         divisor (int): The divisor to fully divide the channel number.
12 |         min_value (int): The minimum value of the output channel.
13 |             Default: None, means that the minimum value equal to the divisor.
14 |         min_ratio (float): The minimum ratio of the rounded channel number to
15 |             the original channel number. Default: 0.9.
16 | 
17 |     Returns:
18 |         int: The modified output channel number.
19 |     """
20 | 
21 |     if min_value is None:
22 |         min_value = divisor
23 |     new_value = max(min_value, int(value + divisor / 2) // divisor * divisor)
24 |     # Make sure that round down does not go down by more than (1-min_ratio).
25 |     if new_value < min_ratio * value:
26 |         new_value += divisor
27 |     return new_value
28 | 


--------------------------------------------------------------------------------
/mmseg/ops/__init__.py:
--------------------------------------------------------------------------------
1 | from .encoding import Encoding
2 | from .wrappers import Upsample, resize
3 | 
4 | __all__ = ['Upsample', 'resize', 'Encoding']
5 | 


--------------------------------------------------------------------------------
/mmseg/utils/__init__.py:
--------------------------------------------------------------------------------
1 | from .collect_env import collect_env
2 | from .logger import get_root_logger, print_log
3 | 
4 | __all__ = ['get_root_logger', 'collect_env', 'print_log']
5 | 


--------------------------------------------------------------------------------
/mmseg/utils/collect_env.py:
--------------------------------------------------------------------------------
 1 | from mmcv.utils import collect_env as collect_base_env
 2 | from mmcv.utils import get_git_hash
 3 | 
 4 | import mmseg
 5 | 
 6 | 
 7 | def collect_env():
 8 |     """Collect the information of the running environments."""
 9 |     env_info = collect_base_env()
10 |     env_info['MMSegmentation'] = f'{mmseg.__version__}+{get_git_hash()[:7]}'
11 | 
12 |     return env_info
13 | 
14 | 
15 | if __name__ == '__main__':
16 |     for name, val in collect_env().items():
17 |         print('{}: {}'.format(name, val))
18 | 


--------------------------------------------------------------------------------
/mmseg/version.py:
--------------------------------------------------------------------------------
 1 | # Copyright (c) Open-MMLab. All rights reserved.
 2 | 
 3 | __version__ = '0.11.0'
 4 | 
 5 | 
 6 | def parse_version_info(version_str):
 7 |     version_info = []
 8 |     for x in version_str.split('.'):
 9 |         if x.isdigit():
10 |             version_info.append(int(x))
11 |         elif x.find('rc') != -1:
12 |             patch_version = x.split('rc')
13 |             version_info.append(int(patch_version[0]))
14 |             version_info.append(f'rc{patch_version[1]}')
15 |     return tuple(version_info)
16 | 
17 | 
18 | version_info = parse_version_info(__version__)
19 | 


--------------------------------------------------------------------------------
/pytest.ini:
--------------------------------------------------------------------------------
1 | [pytest]
2 | addopts = --xdoctest --xdoctest-style=auto
3 | norecursedirs = .git ignore build __pycache__ data docker docs .eggs
4 | 
5 | filterwarnings= default
6 |                 ignore:.*No cfgstr given in Cacher constructor or call.*:Warning
7 |                 ignore:.*Define the __nice__ method for.*:Warning
8 | 


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | -r requirements/optional.txt
2 | -r requirements/runtime.txt
3 | -r requirements/tests.txt
4 | 


--------------------------------------------------------------------------------
/requirements/docs.txt:
--------------------------------------------------------------------------------
1 | recommonmark
2 | sphinx
3 | sphinx_markdown_tables
4 | sphinx_rtd_theme
5 | 


--------------------------------------------------------------------------------
/requirements/optional.txt:
--------------------------------------------------------------------------------
1 | cityscapesscripts
2 | 


--------------------------------------------------------------------------------
/requirements/readthedocs.txt:
--------------------------------------------------------------------------------
1 | mmcv
2 | torch
3 | torchvision
4 | 


--------------------------------------------------------------------------------
/requirements/runtime.txt:
--------------------------------------------------------------------------------
1 | matplotlib
2 | numpy
3 | terminaltables
4 | 


--------------------------------------------------------------------------------
/requirements/tests.txt:
--------------------------------------------------------------------------------
1 | codecov
2 | flake8
3 | interrogate
4 | isort==4.3.21
5 | pytest
6 | xdoctest>=0.10.0
7 | yapf
8 | 


--------------------------------------------------------------------------------
/resources/image.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVlabs/SegFormer/65fa8cfa9b52b6ee7e8897a98705abf8570f9e32/resources/image.png


--------------------------------------------------------------------------------
/resources/mmseg-logo.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVlabs/SegFormer/65fa8cfa9b52b6ee7e8897a98705abf8570f9e32/resources/mmseg-logo.png


--------------------------------------------------------------------------------
/resources/seg_demo.gif:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/NVlabs/SegFormer/65fa8cfa9b52b6ee7e8897a98705abf8570f9e32/resources/seg_demo.gif


--------------------------------------------------------------------------------
/setup.cfg:
--------------------------------------------------------------------------------
 1 | [yapf]
 2 | based_on_style = pep8
 3 | blank_line_before_nested_class_or_def = true
 4 | split_before_expression_after_opening_paren = true
 5 | 
 6 | [isort]
 7 | line_length = 79
 8 | multi_line_output = 0
 9 | known_standard_library = setuptools
10 | known_first_party = mmseg
11 | known_third_party = PIL,cityscapesscripts,cv2,detail,matplotlib,mmcv,numpy,onnxruntime,oss2,pytest,scipy,terminaltables,torch
12 | no_lines_before = STDLIB,LOCALFOLDER
13 | default_section = THIRDPARTY
14 | 


--------------------------------------------------------------------------------
/tests/test_inference.py:
--------------------------------------------------------------------------------
 1 | import os.path as osp
 2 | 
 3 | import mmcv
 4 | 
 5 | from mmseg.apis import inference_segmentor, init_segmentor
 6 | 
 7 | 
 8 | def test_test_time_augmentation_on_cpu():
 9 |     config_file = 'configs/pspnet/pspnet_r50-d8_512x1024_40k_cityscapes.py'
10 |     config = mmcv.Config.fromfile(config_file)
11 | 
12 |     # Remove pretrain model download for testing
13 |     config.model.pretrained = None
14 |     # Replace SyncBN with BN to inference on CPU
15 |     norm_cfg = dict(type='BN', requires_grad=True)
16 |     config.model.backbone.norm_cfg = norm_cfg
17 |     config.model.decode_head.norm_cfg = norm_cfg
18 |     config.model.auxiliary_head.norm_cfg = norm_cfg
19 | 
20 |     # Enable test time augmentation
21 |     config.data.test.pipeline[1].flip = True
22 | 
23 |     checkpoint_file = None
24 |     model = init_segmentor(config, checkpoint_file, device='cpu')
25 | 
26 |     img = mmcv.imread(
27 |         osp.join(osp.dirname(__file__), 'data/color.jpg'), 'color')
28 |     result = inference_segmentor(model, img)
29 |     assert result[0].shape == (288, 512)
30 | 


--------------------------------------------------------------------------------
/tests/test_models/test_necks.py:
--------------------------------------------------------------------------------
 1 | import torch
 2 | 
 3 | from mmseg.models import FPN
 4 | 
 5 | 
 6 | def test_fpn():
 7 |     in_channels = [256, 512, 1024, 2048]
 8 |     inputs = [
 9 |         torch.randn(1, c, 56 // 2**i, 56 // 2**i)
10 |         for i, c in enumerate(in_channels)
11 |     ]
12 | 
13 |     fpn = FPN(in_channels, 256, len(in_channels))
14 |     outputs = fpn(inputs)
15 |     assert outputs[0].shape == torch.Size([1, 256, 56, 56])
16 |     assert outputs[1].shape == torch.Size([1, 256, 28, 28])
17 |     assert outputs[2].shape == torch.Size([1, 256, 14, 14])
18 |     assert outputs[3].shape == torch.Size([1, 256, 7, 7])
19 | 


--------------------------------------------------------------------------------
/tests/test_utils/test_make_divisible.py:
--------------------------------------------------------------------------------
 1 | from mmseg.models.utils import make_divisible
 2 | 
 3 | 
 4 | def test_make_divisible():
 5 |     # test with min_value = None
 6 |     assert make_divisible(10, 4) == 12
 7 |     assert make_divisible(9, 4) == 12
 8 |     assert make_divisible(1, 4) == 4
 9 | 
10 |     # test with min_value = 8
11 |     assert make_divisible(10, 4, 8) == 12
12 |     assert make_divisible(9, 4, 8) == 12
13 |     assert make_divisible(1, 4, 8) == 8
14 | 


--------------------------------------------------------------------------------
/tools/dist_test.sh:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env bash
 2 | 
 3 | CONFIG=$1
 4 | CHECKPOINT=$2
 5 | GPUS=$3
 6 | PORT=${PORT:-29500}
 7 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
 8 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \
 9 |     $(dirname "$0")/test.py $CONFIG $CHECKPOINT --launcher pytorch ${@:4}
10 | 


--------------------------------------------------------------------------------
/tools/dist_train.sh:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env bash
 2 | 
 3 | CONFIG=$1
 4 | GPUS=$2
 5 | PORT=${PORT:-29500}
 6 | 
 7 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
 8 | python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \
 9 |     $(dirname "$0")/train.py $CONFIG --launcher pytorch ${@:3}
10 | 


--------------------------------------------------------------------------------
/tools/print_config.py:
--------------------------------------------------------------------------------
 1 | import argparse
 2 | 
 3 | from mmcv import Config, DictAction
 4 | 
 5 | 
 6 | def parse_args():
 7 |     parser = argparse.ArgumentParser(description='Print the whole config')
 8 |     parser.add_argument('config', help='config file path')
 9 |     parser.add_argument(
10 |         '--options', nargs='+', action=DictAction, help='arguments in dict')
11 |     args = parser.parse_args()
12 | 
13 |     return args
14 | 
15 | 
16 | def main():
17 |     args = parse_args()
18 | 
19 |     cfg = Config.fromfile(args.config)
20 |     if args.options is not None:
21 |         cfg.merge_from_dict(args.options)
22 |     print(f'Config:\n{cfg.pretty_text}')
23 |     # dump config
24 |     cfg.dump('example.py')
25 | 
26 | 
27 | if __name__ == '__main__':
28 |     main()
29 | 


--------------------------------------------------------------------------------
/tools/publish_model.py:
--------------------------------------------------------------------------------
 1 | import argparse
 2 | import subprocess
 3 | 
 4 | import torch
 5 | 
 6 | 
 7 | def parse_args():
 8 |     parser = argparse.ArgumentParser(
 9 |         description='Process a checkpoint to be published')
10 |     parser.add_argument('in_file', help='input checkpoint filename')
11 |     parser.add_argument('out_file', help='output checkpoint filename')
12 |     args = parser.parse_args()
13 |     return args
14 | 
15 | 
16 | def process_checkpoint(in_file, out_file):
17 |     checkpoint = torch.load(in_file, map_location='cpu')
18 |     # remove optimizer for smaller file size
19 |     if 'optimizer' in checkpoint:
20 |         del checkpoint['optimizer']
21 |     # if it is necessary to remove some sensitive data in checkpoint['meta'],
22 |     # add the code here.
23 |     torch.save(checkpoint, out_file)
24 |     sha = subprocess.check_output(['sha256sum', out_file]).decode()
25 |     final_file = out_file.rstrip('.pth') + '-{}.pth'.format(sha[:8])
26 |     subprocess.Popen(['mv', out_file, final_file])
27 | 
28 | 
29 | def main():
30 |     args = parse_args()
31 |     process_checkpoint(args.in_file, args.out_file)
32 | 
33 | 
34 | if __name__ == '__main__':
35 |     main()
36 | 


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/tools/slurm_test.sh:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env bash
 2 | 
 3 | set -x
 4 | 
 5 | PARTITION=$1
 6 | JOB_NAME=$2
 7 | CONFIG=$3
 8 | CHECKPOINT=$4
 9 | GPUS=${GPUS:-4}
10 | GPUS_PER_NODE=${GPUS_PER_NODE:-4}
11 | CPUS_PER_TASK=${CPUS_PER_TASK:-5}
12 | PY_ARGS=${@:5}
13 | SRUN_ARGS=${SRUN_ARGS:-""}
14 | 
15 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
16 | srun -p ${PARTITION} \
17 |     --job-name=${JOB_NAME} \
18 |     --gres=gpu:${GPUS_PER_NODE} \
19 |     --ntasks=${GPUS} \
20 |     --ntasks-per-node=${GPUS_PER_NODE} \
21 |     --cpus-per-task=${CPUS_PER_TASK} \
22 |     --kill-on-bad-exit=1 \
23 |     ${SRUN_ARGS} \
24 |     python -u tools/test.py ${CONFIG} ${CHECKPOINT} --launcher="slurm" ${PY_ARGS}
25 | 


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/tools/slurm_train.sh:
--------------------------------------------------------------------------------
 1 | #!/usr/bin/env bash
 2 | 
 3 | set -x
 4 | 
 5 | PARTITION=$1
 6 | JOB_NAME='mmseg'
 7 | CONFIG=$2
 8 | GPUS=${GPUS:-8}
 9 | GPUS_PER_NODE=${GPUS_PER_NODE:-8}
10 | CPUS_PER_TASK=${CPUS_PER_TASK:-5}
11 | SRUN_ARGS=${SRUN_ARGS:-""}
12 | PY_ARGS=${@:3}
13 | 
14 | PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
15 | srun -p ${PARTITION} \
16 |     --job-name=${JOB_NAME} \
17 |     --gres=gpu:${GPUS_PER_NODE} \
18 |     --ntasks=${GPUS} \
19 |     --ntasks-per-node=${GPUS_PER_NODE} \
20 |     --cpus-per-task=${CPUS_PER_TASK} \
21 |     --kill-on-bad-exit=1 \
22 |     ${SRUN_ARGS} \
23 |     python -u tools/train.py ${CONFIG} --launcher="slurm" ${PY_ARGS}
24 | 


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