f910caf229
* FastFCN first commit * FastFCN first commit * Fixing lint error * Fixing lint error * use for loop on JPU * Use For Loop * Refactor FastFCN * FastFCN * FastFCN * temp * Uploading models & logs (4x4) * Fixing typos * fix typos * rename config * change README.md * use _delete_=True * change configs * change start_level to 0 * change start_level to 0 * jpu * add unittest for start_level!=0
127 lines
4.4 KiB
YAML
127 lines
4.4 KiB
YAML
Collections:
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- Name: fastfcn
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Metadata:
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Training Data:
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- Cityscapes
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Paper:
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URL: https://arxiv.org/abs/1903.11816
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Title: 'FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation'
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README: configs/fastfcn/README.md
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Code:
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URL: https://github.com/open-mmlab/mmsegmentation/blob/v0.18.0/mmseg/models/necks/jpu.py#L12
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Version: v0.18.0
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Converted From:
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Code: https://github.com/wuhuikai/FastFCN
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Models:
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- Name: fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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inference time (ms/im):
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- value: 378.79
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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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memory (GB): 5.67
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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: 79.12
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mIoU(ms+flip): 80.58
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_aspp_512x1024_80k_cityscapes_20210928_053722-5d1a2648.pth
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- Name: fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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memory (GB): 9.79
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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: 79.52
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mIoU(ms+flip): 80.91
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_aspp_4x4_512x1024_80k_cityscapes_20210924_214357-72220849.pth
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- Name: fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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inference time (ms/im):
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- value: 227.27
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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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memory (GB): 5.67
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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: 79.26
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mIoU(ms+flip): 80.86
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn/fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_psp_512x1024_80k_cityscapes_20210928_053722-57749bed.pth
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- Name: fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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memory (GB): 9.94
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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: 78.76
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mIoU(ms+flip): 80.03
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_psp_4x4_512x1024_80k_cityscapes_20210925_061841-77e87b0a.pth
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- Name: fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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inference time (ms/im):
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- value: 209.64
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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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memory (GB): 8.15
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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: 77.97
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mIoU(ms+flip): 79.92
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_enc_512x1024_80k_cityscapes_20210928_030036-78da5046.pth
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- Name: fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes
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In Collection: fastfcn
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Metadata:
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backbone: R-50-D32
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crop size: (512,1024)
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lr schd: 80000
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memory (GB): 15.45
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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: 78.6
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mIoU(ms+flip): 80.25
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Config: configs/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes.py
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fastfcn/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes/fastfcn_r50-d32_jpu_enc_4x4_512x1024_80k_cityscapes_20210926_093217-e1eb6dbb.pth
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