forked from open-mmlab/mmsegmentation
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathbisenetv2.yml
88 lines (88 loc) · 3.03 KB
/
bisenetv2.yml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
Collections:
- Name: BiSeNetV2
Metadata:
Training Data:
- Cityscapes
Paper:
URL: https://arxiv.org/abs/2004.02147
Title: 'Bisenet v2: Bilateral Network with Guided Aggregation for Real-time Semantic
Segmentation'
README: configs/bisenetv2/README.md
Code:
URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/backbones/bisenetv2.py#L545
Version: v0.18.0
Models:
- Name: bisenetv2_fcn_4x4_1024x1024_160k_cityscapes
In Collection: BiSeNetV2
Metadata:
backbone: BiSeNetV2
crop size: (1024,1024)
lr schd: 160000
inference time (ms/im):
- value: 31.48
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (1024,1024)
Training Memory (GB): 7.64
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 73.21
mIoU(ms+flip): 75.74
Config: configs/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_4x4_1024x1024_160k_cityscapes_20210902_015551-bcf10f09.pth
- Name: bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes
In Collection: BiSeNetV2
Metadata:
backbone: BiSeNetV2
crop size: (1024,1024)
lr schd: 160000
Training Memory (GB): 7.64
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 75.3
mIoU(ms+flip): 77.06
Config: configs/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_ohem_4x4_1024x1024_160k_cityscapes_20220808_172324-8bf0aaba.pth
- Name: bisenetv2_fcn_4x8_1024x1024_160k_cityscapes
In Collection: BiSeNetV2
Metadata:
backbone: BiSeNetV2
crop size: (1024,1024)
lr schd: 160000
Training Memory (GB): 15.05
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 75.76
mIoU(ms+flip): 77.79
Config: configs/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes/bisenetv2_fcn_4x8_1024x1024_160k_cityscapes_20210903_000032-e1a2eed6.pth
- Name: bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes
In Collection: BiSeNetV2
Metadata:
backbone: BiSeNetV2
crop size: (1024,1024)
lr schd: 160000
inference time (ms/im):
- value: 27.29
hardware: V100
backend: PyTorch
batch size: 1
mode: FP16
resolution: (1024,1024)
Training Memory (GB): 5.77
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 73.07
mIoU(ms+flip): 75.13
Config: configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes_20210902_045942-b979777b.pth