a95f6d8173
* dice loss * format code, add docstring and calculate denominator without valid_mask * minor change * restore * add metafile * add manifest.in and add config at setup.py * add requirements * modify manifest * modify manifest * Update MANIFEST.in * add metafile * add metadata * fix typo * Update metafile.yml * Update metafile.yml * minor change * Update metafile.yml * add subfix * fix mmshow * add more metafile * add config to model_zoo * fix bug * Update mminstall.txt * [fix] Add models * [Fix] Add collections * [fix] Modify collection name * [Fix] Set datasets to unet metafile * [Fix] Modify collection names * complement inference time
344 lines
11 KiB
YAML
344 lines
11 KiB
YAML
Collections:
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- Name: OCRNet
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Metadata:
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Training Data:
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- Cityscapes
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- Pascal VOC 2012 + Aug
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- ADE20K
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Models:
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- Name: ocrnet_hr18s_512x1024_40k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 10.45
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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: 74.30
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x1024_40k_cityscapes/ocrnet_hr18s_512x1024_40k_cityscapes_20200601_033304-fa2436c2.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x1024_40k_cityscapes.py
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- Name: ocrnet_hr18_512x1024_40k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 7.50
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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: 77.72
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x1024_40k_cityscapes/ocrnet_hr18_512x1024_40k_cityscapes_20200601_033320-401c5bdd.pth
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Config: configs/ocrnet/ocrnet_hr18_512x1024_40k_cityscapes.py
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- Name: ocrnet_hr48_512x1024_40k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 4.22
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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: 80.58
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x1024_40k_cityscapes/ocrnet_hr48_512x1024_40k_cityscapes_20200601_033336-55b32491.pth
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Config: configs/ocrnet/ocrnet_hr48_512x1024_40k_cityscapes.py
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- Name: ocrnet_hr18s_512x1024_80k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 10.45
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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: 77.16
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x1024_80k_cityscapes/ocrnet_hr18s_512x1024_80k_cityscapes_20200601_222735-55979e63.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x1024_80k_cityscapes.py
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- Name: ocrnet_hr18_512x1024_80k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 7.50
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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: 78.57
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x1024_80k_cityscapes/ocrnet_hr18_512x1024_80k_cityscapes_20200614_230521-c2e1dd4a.pth
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Config: configs/ocrnet/ocrnet_hr18_512x1024_80k_cityscapes.py
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- Name: ocrnet_hr48_512x1024_80k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 4.22
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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: 80.70
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x1024_80k_cityscapes/ocrnet_hr48_512x1024_80k_cityscapes_20200601_222752-9076bcdf.pth
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Config: configs/ocrnet/ocrnet_hr48_512x1024_80k_cityscapes.py
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- Name: ocrnet_hr18s_512x1024_160k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 10.45
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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: 78.45
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x1024_160k_cityscapes/ocrnet_hr18s_512x1024_160k_cityscapes_20200602_191005-f4a7af28.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x1024_160k_cityscapes.py
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- Name: ocrnet_hr18_512x1024_160k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 7.50
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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: 79.47
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x1024_160k_cityscapes/ocrnet_hr18_512x1024_160k_cityscapes_20200602_191001-b9172d0c.pth
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Config: configs/ocrnet/ocrnet_hr18_512x1024_160k_cityscapes.py
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- Name: ocrnet_hr48_512x1024_160k_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 4.22
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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: 81.35
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x1024_160k_cityscapes/ocrnet_hr48_512x1024_160k_cityscapes_20200602_191037-dfbf1b0c.pth
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Config: configs/ocrnet/ocrnet_hr48_512x1024_160k_cityscapes.py
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- Name: ocrnet_r101-d8_512x1024_40k_b8_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): None
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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:
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Weights: https://github.com/open-mmlab/mmsegmentation/blob/master/configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py
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Config: configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b8_cityscapes.py
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- Name: ocrnet_r101-d8_512x1024_40k_b16_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 8.8
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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: 3.02
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_r101-d8_512x1024_40k_b8_cityscapes/ocrnet_r101-d8_512x1024_40k_b8_cityscapes-02ac0f13.pth
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Config: configs/ocrnet/ocrnet_r101-d8_512x1024_40k_b16_cityscapes.py
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- Name: ocrnet_r101-d8_512x1024_80k_b16_cityscapes
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In Collection: OCRNet
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Metadata:
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inference time (fps): 8.8
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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: 3.02
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_r101-d8_512x1024_40k_b16_cityscapes/ocrnet_r101-d8_512x1024_40k_b16_cityscapes-db500f80.pth
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Config: configs/ocrnet/ocrnet_r101-d8_512x1024_80k_b16_cityscapes.py
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- Name: ocrnet_hr18s_512x512_80k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 28.98
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 35.06
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x512_80k_ade20k/ocrnet_hr18s_512x512_80k_ade20k_20200615_055600-e80b62af.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x512_80k_ade20k.py
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- Name: ocrnet_hr18_512x512_80k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 18.93
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 37.79
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x512_80k_ade20k/ocrnet_hr18_512x512_80k_ade20k_20200615_053157-d173d83b.pth
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Config: configs/ocrnet/ocrnet_hr18_512x512_80k_ade20k.py
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- Name: ocrnet_hr48_512x512_80k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 16.99
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 43.00
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x512_80k_ade20k/ocrnet_hr48_512x512_80k_ade20k_20200615_021518-d168c2d1.pth
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Config: configs/ocrnet/ocrnet_hr48_512x512_80k_ade20k.py
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- Name: ocrnet_hr18s_512x512_160k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 28.98
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 37.19
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x512_160k_ade20k/ocrnet_hr18s_512x512_160k_ade20k_20200615_184505-8e913058.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x512_160k_ade20k.py
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- Name: ocrnet_hr18_512x512_160k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 18.93
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 39.32
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x512_160k_ade20k/ocrnet_hr18_512x512_160k_ade20k_20200615_200940-d8fcd9d1.pth
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Config: configs/ocrnet/ocrnet_hr18_512x512_160k_ade20k.py
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- Name: ocrnet_hr48_512x512_160k_ade20k
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In Collection: OCRNet
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Metadata:
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inference time (fps): 16.99
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Results:
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- Task: Semantic Segmentation
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Dataset: ADE20K
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Metrics:
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mIoU: 43.25
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x512_160k_ade20k/ocrnet_hr48_512x512_160k_ade20k_20200615_184705-a073726d.pth
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Config: configs/ocrnet/ocrnet_hr48_512x512_160k_ade20k.py
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- Name: ocrnet_hr18s_512x512_20k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 31.55
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 71.70
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x512_20k_voc12aug/ocrnet_hr18s_512x512_20k_voc12aug_20200617_233913-02b04fcb.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x512_20k_voc12aug.py
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- Name: ocrnet_hr18_512x512_20k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 19.91
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 74.75
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x512_20k_voc12aug/ocrnet_hr18_512x512_20k_voc12aug_20200617_233932-8954cbb7.pth
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Config: configs/ocrnet/ocrnet_hr18_512x512_20k_voc12aug.py
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- Name: ocrnet_hr48_512x512_20k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 17.83
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 77.72
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x512_20k_voc12aug/ocrnet_hr48_512x512_20k_voc12aug_20200617_233932-9e82080a.pth
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Config: configs/ocrnet/ocrnet_hr48_512x512_20k_voc12aug.py
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- Name: ocrnet_hr18s_512x512_40k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 31.55
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 72.76
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18s_512x512_40k_voc12aug/ocrnet_hr18s_512x512_40k_voc12aug_20200614_002025-42b587ac.pth
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Config: configs/ocrnet/ocrnet_hr18s_512x512_40k_voc12aug.py
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- Name: ocrnet_hr18_512x512_40k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 19.91
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 74.98
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr18_512x512_40k_voc12aug/ocrnet_hr18_512x512_40k_voc12aug_20200614_015958-714302be.pth
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Config: configs/ocrnet/ocrnet_hr18_512x512_40k_voc12aug.py
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- Name: ocrnet_hr48_512x512_40k_voc12aug
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In Collection: OCRNet
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Metadata:
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inference time (fps): 17.83
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Results:
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- Task: Semantic Segmentation
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Dataset: Pascal VOC 2012 + Aug
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Metrics:
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mIoU: 77.14
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Weights: https://download.openmmlab.com/mmsegmentation/v0.5/ocrnet/ocrnet_hr48_512x512_40k_voc12aug/ocrnet_hr48_512x512_40k_voc12aug_20200614_015958-255bc5ce.pth
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Config: configs/ocrnet/ocrnet_hr48_512x512_40k_voc12aug.py
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