diff --git a/configs/hrnet/README.md b/configs/hrnet/README.md index a34a4bc31..345d175df 100644 --- a/configs/hrnet/README.md +++ b/configs/hrnet/README.md @@ -89,6 +89,6 @@ High-resolution representations are essential for position-sensitive vision prob | Method | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU | mIoU(ms+flip) | config | download | | ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| FCN | HRNetV2p-W18-Small | 512x512 | 80000 | 1.72 | 30.07 | 49.3 | 49.23 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18s_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825-41dcc5dc.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825.log.json) | -| FCN | HRNetV2p-W18 | 512x512 | 80000 | 2.90 | 16.77 | 50.87 | 51.24 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542-95be4d2b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542.log.json) | -| FCN | HRNetV2p-W48 | 512x512 | 80000 | 6.25 | 9.09 | 51.04 | 51.12 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr48_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509-f07e47c6.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509.log.json) | +| FCN | HRNetV2p-W18-Small | 512x512 | 80000 | 1.59 | 24.87 | 49.28 | 49.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18s_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228.log.json) | +| FCN | HRNetV2p-W18 | 512x512 | 80000 | 2.76 | 12.92 | 50.81 | 50.95 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr18_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952.log.json) | +| FCN | HRNetV2p-W48 | 512x512 | 80000 | 6.20 | 9.61 | 51.42 | 51.64 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/hrnet/fcn_hr48_512x512_80k_loveda.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756.log.json) | diff --git a/configs/hrnet/fcn_hr18_512x512_80k_loveda.py b/configs/hrnet/fcn_hr18_512x512_80k_loveda.py index f7bc764f8..3bc4d0a32 100644 --- a/configs/hrnet/fcn_hr18_512x512_80k_loveda.py +++ b/configs/hrnet/fcn_hr18_512x512_80k_loveda.py @@ -2,3 +2,4 @@ _base_ = [ '../_base_/models/fcn_hr18.py', '../_base_/datasets/loveda.py', '../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py' ] +model = dict(decode_head=dict(num_classes=7)) diff --git a/configs/hrnet/hrnet.yml b/configs/hrnet/hrnet.yml index 404abc013..5cef15ef2 100644 --- a/configs/hrnet/hrnet.yml +++ b/configs/hrnet/hrnet.yml @@ -455,21 +455,21 @@ Models: crop size: (512,512) lr schd: 80000 inference time (ms/im): - - value: 33.26 + - value: 40.21 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (512,512) - Training Memory (GB): 1.72 + Training Memory (GB): 1.59 Results: - Task: Semantic Segmentation Dataset: LoveDA Metrics: - mIoU: 49.3 - mIoU(ms+flip): 49.23 + mIoU: 49.28 + mIoU(ms+flip): 49.42 Config: configs/hrnet/fcn_hr18s_512x512_80k_loveda.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211105_180825-41dcc5dc.pth + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18s_512x512_80k_loveda/fcn_hr18s_512x512_80k_loveda_20211210_203228-60a86a7a.pth - Name: fcn_hr18_512x512_80k_loveda In Collection: hrnet Metadata: @@ -477,21 +477,21 @@ Models: crop size: (512,512) lr schd: 80000 inference time (ms/im): - - value: 59.63 + - value: 77.4 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (512,512) - Training Memory (GB): 2.9 + Training Memory (GB): 2.76 Results: - Task: Semantic Segmentation Dataset: LoveDA Metrics: - mIoU: 50.87 - mIoU(ms+flip): 51.24 + mIoU: 50.81 + mIoU(ms+flip): 50.95 Config: configs/hrnet/fcn_hr18_512x512_80k_loveda.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211105_165542-95be4d2b.pth + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr18_512x512_80k_loveda/fcn_hr18_512x512_80k_loveda_20211210_203952-93d9c3b3.pth - Name: fcn_hr48_512x512_80k_loveda In Collection: hrnet Metadata: @@ -499,18 +499,18 @@ Models: crop size: (512,512) lr schd: 80000 inference time (ms/im): - - value: 110.01 + - value: 104.06 hardware: V100 backend: PyTorch batch size: 1 mode: FP32 resolution: (512,512) - Training Memory (GB): 6.25 + Training Memory (GB): 6.2 Results: - Task: Semantic Segmentation Dataset: LoveDA Metrics: - mIoU: 51.04 - mIoU(ms+flip): 51.12 + mIoU: 51.42 + mIoU(ms+flip): 51.64 Config: configs/hrnet/fcn_hr48_512x512_80k_loveda.py - Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211105_131509-f07e47c6.pth + Weights: https://download.openmmlab.com/mmsegmentation/v0.5/hrnet/fcn_hr48_512x512_80k_loveda/fcn_hr48_512x512_80k_loveda_20211211_044756-67072f55.pth