mmsegmentation/configs/mobilenet_v3/mobilenet_v3.yml

104 lines
3.4 KiB
YAML

Collections:
- Name: mobilenet_v3
Metadata:
Training Data:
- Cityscapes
Paper:
URL: https://arxiv.org/abs/1905.02244
Title: Searching for MobileNetV3
README: configs/mobilenet_v3/README.md
Code:
URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.17.0/mmseg/models/backbones/mobilenet_v3.py#L15
Version: v0.17.0
Converted From:
Code: https://github.com/tensorflow/models/tree/master/research/deeplab
Models:
- Name: lraspp_m-v3-d8_512x1024_320k_cityscapes
In Collection: mobilenet_v3
Metadata:
backbone: M-V3-D8
crop size: (512,1024)
lr schd: 320000
inference time (ms/im):
- value: 65.7
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 8.9
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 69.54
mIoU(ms+flip): 70.89
Config: configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes/lraspp_m-v3-d8_512x1024_320k_cityscapes_20201224_220337-cfe8fb07.pth
- Name: lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes
In Collection: mobilenet_v3
Metadata:
backbone: M-V3-D8 (scratch)
crop size: (512,1024)
lr schd: 320000
inference time (ms/im):
- value: 67.7
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 8.9
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 67.87
mIoU(ms+flip): 69.78
Config: configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes_20201224_220337-9f29cd72.pth
- Name: lraspp_m-v3s-d8_512x1024_320k_cityscapes
In Collection: mobilenet_v3
Metadata:
backbone: M-V3s-D8
crop size: (512,1024)
lr schd: 320000
inference time (ms/im):
- value: 42.3
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 5.3
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 64.11
mIoU(ms+flip): 66.42
Config: configs/mobilenet_v3/lraspp_m-v3s-d8_512x1024_320k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v3/lraspp_m-v3s-d8_512x1024_320k_cityscapes/lraspp_m-v3s-d8_512x1024_320k_cityscapes_20201224_223935-61565b34.pth
- Name: lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes
In Collection: mobilenet_v3
Metadata:
backbone: M-V3s-D8 (scratch)
crop size: (512,1024)
lr schd: 320000
inference time (ms/im):
- value: 40.82
hardware: V100
backend: PyTorch
batch size: 1
mode: FP32
resolution: (512,1024)
Training Memory (GB): 5.3
Results:
- Task: Semantic Segmentation
Dataset: Cityscapes
Metrics:
mIoU: 62.74
mIoU(ms+flip): 65.01
Config: configs/mobilenet_v3/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py
Weights: https://download.openmmlab.com/mmsegmentation/v0.5/mobilenet_v3/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes_20201224_223935-03daeabb.pth