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mobilenet_v3.yml
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mobilenet_v3.yml
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Collections:
- Metadata:
Training Data:
- Cityscapes
Name: mobilenet_v3
Models:
- Config: configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py
In Collection: mobilenet_v3
Metadata:
backbone: M-V3-D8
crop size: (512,1024)
inference time (ms/im):
- backend: PyTorch
batch size: 1
hardware: V100
mode: FP32
resolution: (512,1024)
value: 65.7
lr schd: 320000
memory (GB): 8.9
Name: lraspp_m-v3-d8_512x1024_320k_cityscapes
Results:
Dataset: Cityscapes
Metrics:
mIoU: 69.54
mIoU(ms+flip): 70.89
Task: Semantic Segmentation
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
- Config: configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py
In Collection: mobilenet_v3
Metadata:
backbone: M-V3-D8 (scratch)
crop size: (512,1024)
inference time (ms/im):
- backend: PyTorch
batch size: 1
hardware: V100
mode: FP32
resolution: (512,1024)
value: 67.7
lr schd: 320000
memory (GB): 8.9
Name: lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes
Results:
Dataset: Cityscapes
Metrics:
mIoU: 67.87
mIoU(ms+flip): 69.78
Task: Semantic Segmentation
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
- Config: configs/mobilenet_v3/lraspp_m-v3s-d8_512x1024_320k_cityscapes.py
In Collection: mobilenet_v3
Metadata:
backbone: M-V3s-D8
crop size: (512,1024)
inference time (ms/im):
- backend: PyTorch
batch size: 1
hardware: V100
mode: FP32
resolution: (512,1024)
value: 42.3
lr schd: 320000
memory (GB): 5.3
Name: lraspp_m-v3s-d8_512x1024_320k_cityscapes
Results:
Dataset: Cityscapes
Metrics:
mIoU: 64.11
mIoU(ms+flip): 66.42
Task: Semantic Segmentation
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
- Config: configs/mobilenet_v3/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py
In Collection: mobilenet_v3
Metadata:
backbone: M-V3s-D8 (scratch)
crop size: (512,1024)
inference time (ms/im):
- backend: PyTorch
batch size: 1
hardware: V100
mode: FP32
resolution: (512,1024)
value: 40.82
lr schd: 320000
memory (GB): 5.3
Name: lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes
Results:
Dataset: Cityscapes
Metrics:
mIoU: 62.74
mIoU(ms+flip): 65.01
Task: Semantic Segmentation
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