170 lines
5.2 KiB
YAML
170 lines
5.2 KiB
YAML
Collections:
|
|
- Name: segformer
|
|
Metadata:
|
|
Training Data:
|
|
- ADE20k
|
|
Paper:
|
|
URL: https://arxiv.org/abs/2105.15203
|
|
Title: resize image to multiple of 32, improve SegFormer by 0.5-1.0 mIoU.
|
|
README: configs/segformer/README.md
|
|
Code:
|
|
URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mit.py#L246
|
|
Version: v0.17.0
|
|
Converted From:
|
|
Code: https://github.com/NVlabs/SegFormer
|
|
Models:
|
|
- Name: segformer_mit-b0_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B0
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 19.49
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 2.1
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 37.41
|
|
mIoU(ms+flip): 38.34
|
|
Config: configs/segformer/segformer_mit-b0_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b0_512x512_160k_ade20k/segformer_mit-b0_512x512_160k_ade20k_20210726_101530-8ffa8fda.pth
|
|
- Name: segformer_mit-b1_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B1
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 20.98
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 2.6
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 40.97
|
|
mIoU(ms+flip): 42.54
|
|
Config: configs/segformer/segformer_mit-b1_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b1_512x512_160k_ade20k/segformer_mit-b1_512x512_160k_ade20k_20210726_112106-d70e859d.pth
|
|
- Name: segformer_mit-b2_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B2
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 32.38
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 3.6
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 45.58
|
|
mIoU(ms+flip): 47.03
|
|
Config: configs/segformer/segformer_mit-b2_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b2_512x512_160k_ade20k/segformer_mit-b2_512x512_160k_ade20k_20210726_112103-cbd414ac.pth
|
|
- Name: segformer_mit-b3_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B3
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 45.23
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 4.8
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 47.82
|
|
mIoU(ms+flip): 48.81
|
|
Config: configs/segformer/segformer_mit-b3_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b3_512x512_160k_ade20k/segformer_mit-b3_512x512_160k_ade20k_20210726_081410-962b98d2.pth
|
|
- Name: segformer_mit-b4_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B4
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 64.72
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 6.1
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 48.46
|
|
mIoU(ms+flip): 49.76
|
|
Config: configs/segformer/segformer_mit-b4_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b4_512x512_160k_ade20k/segformer_mit-b4_512x512_160k_ade20k_20210728_183055-7f509d7d.pth
|
|
- Name: segformer_mit-b5_512x512_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B5
|
|
crop size: (512,512)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 84.1
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (512,512)
|
|
memory (GB): 7.2
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 49.13
|
|
mIoU(ms+flip): 50.22
|
|
Config: configs/segformer/segformer_mit-b5_512x512_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b5_512x512_160k_ade20k/segformer_mit-b5_512x512_160k_ade20k_20210726_145235-94cedf59.pth
|
|
- Name: segformer_mit-b5_640x640_160k_ade20k
|
|
In Collection: segformer
|
|
Metadata:
|
|
backbone: MIT-B5
|
|
crop size: (640,640)
|
|
lr schd: 160000
|
|
inference time (ms/im):
|
|
- value: 88.5
|
|
hardware: V100
|
|
backend: PyTorch
|
|
batch size: 1
|
|
mode: FP32
|
|
resolution: (640,640)
|
|
memory (GB): 11.5
|
|
Results:
|
|
- Task: Semantic Segmentation
|
|
Dataset: ADE20k
|
|
Metrics:
|
|
mIoU: 49.62
|
|
mIoU(ms+flip): 50.36
|
|
Config: configs/segformer/segformer_mit-b5_640x640_160k_ade20k.py
|
|
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/segformer/segformer_mit-b5_640x640_160k_ade20k/segformer_mit-b5_640x640_160k_ade20k_20210801_121243-41d2845b.pth
|