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- Collections:
- - Name: DeepLabV3+
- Metadata:
- Training Data:
- - Cityscapes
- - ADE20K
- - Pascal VOC 2012 + Aug
- - Pascal Context
- - Pascal Context 59
- - LoveDA
- - Potsdam
- - Vaihingen
- - iSAID
- Paper:
- URL: https://arxiv.org/abs/1802.02611
- Title: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
- README: configs/deeplabv3plus/README.md
- Code:
- URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/decode_heads/sep_aspp_head.py#L30
- Version: v0.17.0
- Converted From:
- Code: https://github.com/tensorflow/models/tree/master/research/deeplab
- Models:
- - Name: deeplabv3plus_r50-d8_512x1024_40k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,1024)
- lr schd: 40000
- inference time (ms/im):
- - value: 253.81
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 7.5
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.61
- mIoU(ms+flip): 81.01
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_40k_cityscapes/deeplabv3plus_r50-d8_512x1024_40k_cityscapes_20200605_094610-d222ffcd.pth
- - Name: deeplabv3plus_r101-d8_512x1024_40k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,1024)
- lr schd: 40000
- inference time (ms/im):
- - value: 384.62
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 11.0
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.21
- mIoU(ms+flip): 81.82
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_40k_cityscapes/deeplabv3plus_r101-d8_512x1024_40k_cityscapes_20200605_094614-3769eecf.pth
- - Name: deeplabv3plus_r50-d8_769x769_40k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (769,769)
- lr schd: 40000
- inference time (ms/im):
- - value: 581.4
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 8.5
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 78.97
- mIoU(ms+flip): 80.46
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_40k_cityscapes/deeplabv3plus_r50-d8_769x769_40k_cityscapes_20200606_114143-1dcb0e3c.pth
- - Name: deeplabv3plus_r101-d8_769x769_40k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (769,769)
- lr schd: 40000
- inference time (ms/im):
- - value: 869.57
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 12.5
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.46
- mIoU(ms+flip): 80.5
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_40k_cityscapes/deeplabv3plus_r101-d8_769x769_40k_cityscapes_20200606_114304-ff414b9e.pth
- - Name: deeplabv3plus_r18-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (512,1024)
- lr schd: 80000
- inference time (ms/im):
- - value: 70.08
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 2.2
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 76.89
- mIoU(ms+flip): 78.76
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes_20201226_080942-cff257fe.pth
- - Name: deeplabv3plus_r50-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,1024)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.09
- mIoU(ms+flip): 81.13
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049-f9fb496d.pth
- - Name: deeplabv3plus_r101-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,1024)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.97
- mIoU(ms+flip): 82.03
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth
- - Name: deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,1024)
- lr schd: 80000
- inference time (ms/im):
- - value: 127.06
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP16
- resolution: (512,1024)
- Training Memory (GB): 6.35
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.46
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth
- - Name: deeplabv3plus_r18-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (769,769)
- lr schd: 80000
- inference time (ms/im):
- - value: 174.22
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 2.5
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 76.26
- mIoU(ms+flip): 77.91
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes_20201226_083346-f326e06a.pth
- - Name: deeplabv3plus_r50-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (769,769)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.83
- mIoU(ms+flip): 81.48
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233-0e9dfdc4.pth
- - Name: deeplabv3plus_r101-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (769,769)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.65
- mIoU(ms+flip): 81.47
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20220406_154720-dfcc0b68.pth
- - Name: deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D16-MG124
- crop size: (512,1024)
- lr schd: 40000
- inference time (ms/im):
- - value: 133.69
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 5.8
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.09
- mIoU(ms+flip): 80.36
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes/deeplabv3plus_r101-d16-mg124_512x1024_40k_cityscapes_20200908_005644-cf9ce186.pth
- - Name: deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D16-MG124
- crop size: (512,1024)
- lr schd: 80000
- Training Memory (GB): 9.9
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.9
- mIoU(ms+flip): 81.33
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes/deeplabv3plus_r101-d16-mg124_512x1024_80k_cityscapes_20200908_005644-ee6158e0.pth
- - Name: deeplabv3plus_r18b-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18b-D8
- crop size: (512,1024)
- lr schd: 80000
- inference time (ms/im):
- - value: 66.89
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 2.1
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 75.87
- mIoU(ms+flip): 77.52
- Config: configs/deeplabv3plus/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes/deeplabv3plus_r18b-d8_512x1024_80k_cityscapes_20201226_090828-e451abd9.pth
- - Name: deeplabv3plus_r50b-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50b-D8
- crop size: (512,1024)
- lr schd: 80000
- inference time (ms/im):
- - value: 253.81
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 7.4
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.28
- mIoU(ms+flip): 81.44
- Config: configs/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes/deeplabv3plus_r50b-d8_512x1024_80k_cityscapes_20201225_213645-a97e4e43.pth
- - Name: deeplabv3plus_r101b-d8_512x1024_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101b-D8
- crop size: (512,1024)
- lr schd: 80000
- inference time (ms/im):
- - value: 384.62
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,1024)
- Training Memory (GB): 10.9
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 80.16
- mIoU(ms+flip): 81.41
- Config: configs/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes/deeplabv3plus_r101b-d8_512x1024_80k_cityscapes_20201226_190843-9c3c93a4.pth
- - Name: deeplabv3plus_r18b-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18b-D8
- crop size: (769,769)
- lr schd: 80000
- inference time (ms/im):
- - value: 167.79
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 2.4
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 76.36
- mIoU(ms+flip): 78.24
- Config: configs/deeplabv3plus/deeplabv3plus_r18b-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18b-d8_769x769_80k_cityscapes/deeplabv3plus_r18b-d8_769x769_80k_cityscapes_20201226_151312-2c868aff.pth
- - Name: deeplabv3plus_r50b-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50b-D8
- crop size: (769,769)
- lr schd: 80000
- inference time (ms/im):
- - value: 581.4
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 8.4
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.41
- mIoU(ms+flip): 80.56
- Config: configs/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50b-d8_769x769_80k_cityscapes/deeplabv3plus_r50b-d8_769x769_80k_cityscapes_20201225_224655-8b596d1c.pth
- - Name: deeplabv3plus_r101b-d8_769x769_80k_cityscapes
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101b-D8
- crop size: (769,769)
- lr schd: 80000
- inference time (ms/im):
- - value: 909.09
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (769,769)
- Training Memory (GB): 12.3
- Results:
- - Task: Semantic Segmentation
- Dataset: Cityscapes
- Metrics:
- mIoU: 79.88
- mIoU(ms+flip): 81.46
- Config: configs/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes/deeplabv3plus_r101b-d8_769x769_80k_cityscapes_20201226_205041-227cdf7c.pth
- - Name: deeplabv3plus_r50-d8_512x512_80k_ade20k
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 47.6
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 10.6
- Results:
- - Task: Semantic Segmentation
- Dataset: ADE20K
- Metrics:
- mIoU: 42.72
- mIoU(ms+flip): 43.75
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_ade20k/deeplabv3plus_r50-d8_512x512_80k_ade20k_20200614_185028-bf1400d8.pth
- - Name: deeplabv3plus_r101-d8_512x512_80k_ade20k
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 70.62
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 14.1
- Results:
- - Task: Semantic Segmentation
- Dataset: ADE20K
- Metrics:
- mIoU: 44.6
- mIoU(ms+flip): 46.06
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_ade20k/deeplabv3plus_r101-d8_512x512_80k_ade20k_20200615_014139-d5730af7.pth
- - Name: deeplabv3plus_r50-d8_512x512_160k_ade20k
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 160000
- Results:
- - Task: Semantic Segmentation
- Dataset: ADE20K
- Metrics:
- mIoU: 43.95
- mIoU(ms+flip): 44.93
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_160k_ade20k/deeplabv3plus_r50-d8_512x512_160k_ade20k_20200615_124504-6135c7e0.pth
- - Name: deeplabv3plus_r101-d8_512x512_160k_ade20k
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 160000
- Results:
- - Task: Semantic Segmentation
- Dataset: ADE20K
- Metrics:
- mIoU: 45.47
- mIoU(ms+flip): 46.35
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_160k_ade20k/deeplabv3plus_r101-d8_512x512_160k_ade20k_20200615_123232-38ed86bb.pth
- - Name: deeplabv3plus_r50-d8_512x512_20k_voc12aug
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 20000
- inference time (ms/im):
- - value: 47.62
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 7.6
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal VOC 2012 + Aug
- Metrics:
- mIoU: 75.93
- mIoU(ms+flip): 77.5
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_20k_voc12aug/deeplabv3plus_r50-d8_512x512_20k_voc12aug_20200617_102323-aad58ef1.pth
- - Name: deeplabv3plus_r101-d8_512x512_20k_voc12aug
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 20000
- inference time (ms/im):
- - value: 72.05
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 11.0
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal VOC 2012 + Aug
- Metrics:
- mIoU: 77.22
- mIoU(ms+flip): 78.59
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_20k_voc12aug/deeplabv3plus_r101-d8_512x512_20k_voc12aug_20200617_102345-c7ff3d56.pth
- - Name: deeplabv3plus_r50-d8_512x512_40k_voc12aug
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 40000
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal VOC 2012 + Aug
- Metrics:
- mIoU: 76.81
- mIoU(ms+flip): 77.57
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_40k_voc12aug/deeplabv3plus_r50-d8_512x512_40k_voc12aug_20200613_161759-e1b43aa9.pth
- - Name: deeplabv3plus_r101-d8_512x512_40k_voc12aug
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 40000
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal VOC 2012 + Aug
- Metrics:
- mIoU: 78.62
- mIoU(ms+flip): 79.53
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_40k_voc12aug/deeplabv3plus_r101-d8_512x512_40k_voc12aug_20200613_205333-faf03387.pth
- - Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (480,480)
- lr schd: 40000
- inference time (ms/im):
- - value: 110.01
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (480,480)
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal Context
- Metrics:
- mIoU: 47.3
- mIoU(ms+flip): 48.47
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context/deeplabv3plus_r101-d8_480x480_40k_pascal_context_20200911_165459-d3c8a29e.pth
- - Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (480,480)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal Context
- Metrics:
- mIoU: 47.23
- mIoU(ms+flip): 48.26
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context/deeplabv3plus_r101-d8_480x480_80k_pascal_context_20200911_155322-145d3ee8.pth
- - Name: deeplabv3plus_r101-d8_480x480_40k_pascal_context_59
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (480,480)
- lr schd: 40000
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal Context 59
- Metrics:
- mIoU: 52.86
- mIoU(ms+flip): 54.54
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59_20210416_111233-ed937f15.pth
- - Name: deeplabv3plus_r101-d8_480x480_80k_pascal_context_59
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (480,480)
- lr schd: 80000
- Results:
- - Task: Semantic Segmentation
- Dataset: Pascal Context 59
- Metrics:
- mIoU: 53.2
- mIoU(ms+flip): 54.67
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59_20210416_111127-7ca0331d.pth
- - Name: deeplabv3plus_r18-d8_512x512_80k_loveda
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 39.11
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 1.93
- Results:
- - Task: Semantic Segmentation
- Dataset: LoveDA
- Metrics:
- mIoU: 50.28
- mIoU(ms+flip): 50.47
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_loveda.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_loveda/deeplabv3plus_r18-d8_512x512_80k_loveda_20211104_132800-ce0fa0ca.pth
- - Name: deeplabv3plus_r50-d8_512x512_80k_loveda
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 166.67
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 7.37
- Results:
- - Task: Semantic Segmentation
- Dataset: LoveDA
- Metrics:
- mIoU: 50.99
- mIoU(ms+flip): 50.65
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_loveda.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_loveda/deeplabv3plus_r50-d8_512x512_80k_loveda_20211105_080442-f0720392.pth
- - Name: deeplabv3plus_r101-d8_512x512_80k_loveda
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 230.95
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 10.84
- Results:
- - Task: Semantic Segmentation
- Dataset: LoveDA
- Metrics:
- mIoU: 51.47
- mIoU(ms+flip): 51.32
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_loveda.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_loveda/deeplabv3plus_r101-d8_512x512_80k_loveda_20211105_110759-4c1f297e.pth
- - Name: deeplabv3plus_r18-d8_512x512_80k_potsdam
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 12.24
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 1.91
- Results:
- - Task: Semantic Segmentation
- Dataset: Potsdam
- Metrics:
- mIoU: 77.09
- mIoU(ms+flip): 78.44
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_potsdam.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x512_80k_potsdam/deeplabv3plus_r18-d8_512x512_80k_potsdam_20211219_020601-75fd5bc3.pth
- - Name: deeplabv3plus_r50-d8_512x512_80k_potsdam
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 37.82
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 7.36
- Results:
- - Task: Semantic Segmentation
- Dataset: Potsdam
- Metrics:
- mIoU: 78.33
- mIoU(ms+flip): 79.27
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_potsdam.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x512_80k_potsdam/deeplabv3plus_r50-d8_512x512_80k_potsdam_20211219_031508-7e7a2b24.pth
- - Name: deeplabv3plus_r101-d8_512x512_80k_potsdam
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 56.95
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 10.83
- Results:
- - Task: Semantic Segmentation
- Dataset: Potsdam
- Metrics:
- mIoU: 78.7
- mIoU(ms+flip): 79.47
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_potsdam.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x512_80k_potsdam/deeplabv3plus_r101-d8_512x512_80k_potsdam_20211219_031508-8b112708.pth
- - Name: deeplabv3plus_r18-d8_4x4_512x512_80k_vaihingen
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 13.74
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 1.91
- Results:
- - Task: Semantic Segmentation
- Dataset: Vaihingen
- Metrics:
- mIoU: 72.5
- mIoU(ms+flip): 74.13
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_4x4_512x512_80k_vaihingen.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_4x4_512x512_80k_vaihingen/deeplabv3plus_r18-d8_4x4_512x512_80k_vaihingen_20211231_230805-7626a263.pth
- - Name: deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 37.16
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 7.36
- Results:
- - Task: Semantic Segmentation
- Dataset: Vaihingen
- Metrics:
- mIoU: 73.97
- mIoU(ms+flip): 75.05
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen/deeplabv3plus_r50-d8_4x4_512x512_80k_vaihingen_20211231_230816-5040938d.pth
- - Name: deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-101-D8
- crop size: (512,512)
- lr schd: 80000
- inference time (ms/im):
- - value: 53.79
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (512,512)
- Training Memory (GB): 10.83
- Results:
- - Task: Semantic Segmentation
- Dataset: Vaihingen
- Metrics:
- mIoU: 73.06
- mIoU(ms+flip): 74.14
- Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen/deeplabv3plus_r101-d8_4x4_512x512_80k_vaihingen_20211231_230816-8a095afa.pth
- - Name: deeplabv3plus_r18-d8_4x4_896x896_80k_isaid
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-18-D8
- crop size: (896,896)
- lr schd: 80000
- inference time (ms/im):
- - value: 40.31
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (896,896)
- Training Memory (GB): 6.19
- Results:
- - Task: Semantic Segmentation
- Dataset: iSAID
- Metrics:
- mIoU: 61.35
- mIoU(ms+flip): 62.61
- Config: configs/deeplabv3plus/deeplabv3plus_r18-d8_4x4_896x896_80k_isaid.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_4x4_896x896_80k_isaid/deeplabv3plus_r18-d8_4x4_896x896_80k_isaid_20220110_180526-7059991d.pth
- - Name: deeplabv3plus_r50-d8_4x4_896x896_80k_isaid
- In Collection: DeepLabV3+
- Metadata:
- backbone: R-50-D8
- crop size: (896,896)
- lr schd: 80000
- inference time (ms/im):
- - value: 118.76
- hardware: V100
- backend: PyTorch
- batch size: 1
- mode: FP32
- resolution: (896,896)
- Training Memory (GB): 21.45
- Results:
- - Task: Semantic Segmentation
- Dataset: iSAID
- Metrics:
- mIoU: 67.06
- mIoU(ms+flip): 68.02
- Config: configs/deeplabv3plus/deeplabv3plus_r50-d8_4x4_896x896_80k_isaid.py
- Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_4x4_896x896_80k_isaid/deeplabv3plus_r50-d8_4x4_896x896_80k_isaid_20220110_180526-598be439.pth
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