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50 lines
1.4 KiB
YAML
50 lines
1.4 KiB
YAML
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- Name: PANet
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Metadata:
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Training Data: ICDARDataset
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Training Techniques:
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- Adam
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Training Resources: 8x NVIDIA V100 GPUs
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Architecture:
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- ResNet
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- FPEM_FFM
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Paper: https://arxiv.org/pdf/1803.01534.pdf
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README: configs/textdet/panet/README.md
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Models:
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- Name: panet_r18_fpem_ffm_600e_ctw1500
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In Collection: PANet
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Config: configs/textdet/panet/panet_r18_fpem_ffm_600e_ctw1500.py
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Metadata:
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Training Data: CTW1500
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Results:
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- Task: Instance Segmentation
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Dataset: CTW1500
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Metrics:
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hmean-iou: 0.806
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Weights: https://download.openmmlab.com/mmocr/textdet/panet/panet_r18_fpem_ffm_sbn_600e_ctw1500_20210219-3b3a9aa3.pth
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- Name: panet_r18_fpem_ffm_600e_icdar2015
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In Collection: PANet
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Config: configs/textdet/panet/panet_r18_fpem_ffm_600e_icdar2015.py
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Metadata:
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Training Data: ICDAR2015
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Results:
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- Task: Instance Segmentation
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Dataset: ICDAR2015
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Metrics:
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hmean-iou: 0.791
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Weights: https://download.openmmlab.com/mmocr/textdet/panet/panet_r18_fpem_ffm_sbn_600e_icdar2015_20210219-42dbe46a.pth
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- Name: panet_r50_fpem_ffm_600e_icdar2017
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In Collection: PANet
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Config: configs/textdet/panet/panet_r50_fpem_ffm_600e_icdar2017.py
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Metadata:
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Training Data: ICDAR2017
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Results:
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- Task: Instance Segmentation
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Dataset: ICDAR2017
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Metrics:
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hmean-iou:
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Weights:
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