ed954fffd9
* change md2yml file * update metafile * update twins In Collection automatically * fix twins metafile * fix twins metafile * all metafile use value of Method * update collect name * update collect name * fix some typo * fix FCN D6 * change JPU to FastFCN * fix some typos in DNLNet, NonLocalNet, SETR, Segmenter, STDC, FastSCNN * fix typo in stdc * fix typo in DNLNet and UNet * fix NonLocalNet typo
90 lines
2.9 KiB
YAML
90 lines
2.9 KiB
YAML
Models:
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- Name: lraspp_m-v3-d8_512x1024_320k_cityscapes
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In Collection: LRASPP
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Metadata:
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backbone: M-V3-D8
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crop size: (512,1024)
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lr schd: 320000
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inference time (ms/im):
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- value: 65.7
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,1024)
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Training Memory (GB): 8.9
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Results:
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- Task: Semantic Segmentation
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Dataset: Cityscapes
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Metrics:
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mIoU: 69.54
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mIoU(ms+flip): 70.89
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Config: configs/mobilenet_v3/lraspp_m-v3-d8_512x1024_320k_cityscapes.py
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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
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- Name: lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes
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In Collection: LRASPP
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Metadata:
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backbone: M-V3-D8 (scratch)
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crop size: (512,1024)
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lr schd: 320000
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inference time (ms/im):
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- value: 67.7
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,1024)
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Training Memory (GB): 8.9
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Results:
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- Task: Semantic Segmentation
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Dataset: Cityscapes
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Metrics:
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mIoU: 67.87
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mIoU(ms+flip): 69.78
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Config: configs/mobilenet_v3/lraspp_m-v3-d8_scratch_512x1024_320k_cityscapes.py
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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
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- Name: lraspp_m-v3s-d8_512x1024_320k_cityscapes
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In Collection: LRASPP
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Metadata:
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backbone: M-V3s-D8
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crop size: (512,1024)
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lr schd: 320000
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inference time (ms/im):
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- value: 42.3
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,1024)
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Training Memory (GB): 5.3
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Results:
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- Task: Semantic Segmentation
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Dataset: Cityscapes
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Metrics:
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mIoU: 64.11
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mIoU(ms+flip): 66.42
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Config: configs/mobilenet_v3/lraspp_m-v3s-d8_512x1024_320k_cityscapes.py
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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
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- Name: lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes
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In Collection: LRASPP
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Metadata:
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backbone: M-V3s-D8 (scratch)
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crop size: (512,1024)
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lr schd: 320000
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inference time (ms/im):
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- value: 40.82
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hardware: V100
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backend: PyTorch
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batch size: 1
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mode: FP32
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resolution: (512,1024)
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Training Memory (GB): 5.3
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Results:
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- Task: Semantic Segmentation
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Dataset: Cityscapes
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Metrics:
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mIoU: 62.74
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mIoU(ms+flip): 65.01
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Config: configs/mobilenet_v3/lraspp_m-v3s-d8_scratch_512x1024_320k_cityscapes.py
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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
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