mirror of https://github.com/open-mmlab/mmocr.git
42 lines
1.3 KiB
YAML
42 lines
1.3 KiB
YAML
Collections:
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- Name: PANet
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Metadata:
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Training Data: ICDAR2015 SCUT-CTW1500
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Training Techniques:
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- Adam
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Training Resources: 1x NVIDIA A100-SXM4-80GB
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Architecture:
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- ResNet
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- FPEM_FFM
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Paper:
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URL: https://arxiv.org/pdf/1803.01534.pdf
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Title: 'Path Aggregation Network for Instance Segmentation'
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README: configs/textdet/panet/README.md
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Models:
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- Name: panet_resnet18_fpem-ffm_600e_ctw1500
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Alias: PANet_CTW
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In Collection: PANet
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Config: configs/textdet/panet/panet_resnet18_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: Text Detection
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Dataset: CTW1500
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Metrics:
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hmean-iou: 0.7770
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Weights: https://download.openmmlab.com/mmocr/textdet/panet/panet_resnet18_fpem-ffm_600e_ctw1500/panet_resnet18_fpem-ffm_600e_ctw1500_20220826_144818-980f32d0.pth
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- Name: panet_resnet18_fpem-ffm_600e_icdar2015
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Alias: PANet_IC15
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In Collection: PANet
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Config: configs/textdet/panet/panet_resnet18_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: Text Detection
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Dataset: ICDAR2015
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Metrics:
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hmean-iou: 0.7848
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Weights: https://download.openmmlab.com/mmocr/textdet/panet/panet_resnet18_fpem-ffm_600e_icdar2015/panet_resnet18_fpem-ffm_600e_icdar2015_20220826_144817-be2acdb4.pth
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