mirror of
https://github.com/open-mmlab/mmpretrain.git
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c98dc4555c
* 添加vig源文件 * 某些模块修改到mmcls风格 * 修改到mmcls风格 * 修改 * 添加VIG模型及源文件 * update model file * update model file and config * change class name and some variable name * change class name and some variable name * update * update * change nn.BatchNorm to mmcv.cnn.build_norm_layer * update * change nn.Seq to mmcls * change backbone to stage_blocks * add vig_head * update * update config file * update * add readme and metafile * update model-index.yml * update model file * rename config file and add docstring * variable rename * update readme and metafile * update readme * update * Update VIG backbone implementation and docs. * Fix configs. Co-authored-by: mzr1996 <mzr1996@163.com>
135 lines
5.1 KiB
YAML
135 lines
5.1 KiB
YAML
Collections:
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- Name: VIG
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Metadata:
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Training Data: ImageNet-1k
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Architecture:
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- Vision GNN
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Paper:
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Title: 'Vision GNN: An Image is Worth Graph of Nodes'
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URL: https://arxiv.org/abs/2206.00272
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README: configs/vig/README.md
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Code:
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URL: null
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Version: null
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Models:
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- Name: vig-tiny_3rdparty_in1k
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Metadata:
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FLOPs: 1309000000
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Parameters: 7185000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 74.40
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Top 5 Accuracy: 92.34
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/vig-tiny_3rdparty_in1k_20230117-6414c684.pth
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Config: configs/vig/vig-tiny_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/vig/vig_ti_74.5.pth
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: vig-small_3rdparty_in1k
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Metadata:
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FLOPs: 4535000000
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Parameters: 22748000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 80.61
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Top 5 Accuracy: 95.28
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/vig-small_3rdparty_in1k_20230117-5338bf3b.pth
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Config: configs/vig/vig-small_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/vig/vig_s_80.6.pth
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: vig-base_3rdparty_in1k
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Metadata:
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FLOPs: 17681000000
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Parameters: 20685000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 82.62
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Top 5 Accuracy: 96.04
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/vig-base_3rdparty_in1k_20230117-92f6f12f.pth
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Config: configs/vig/vig-base_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/vig/vig_b_82.6.pth
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: pvig-tiny_3rdparty_in1k
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Metadata:
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FLOPs: 1714000000
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Parameters: 9458000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 78.38
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Top 5 Accuracy: 94.38
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/pvig-tiny_3rdparty_in1k_20230117-eb77347d.pth
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Config: configs/vig/pvig-tiny_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/pyramid-vig/pvig_ti_78.5.pth.tar
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: pvig-small_3rdparty_in1k
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Metadata:
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FLOPs: 4572000000
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Parameters: 29024000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 82.00
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Top 5 Accuracy: 95.97
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/pvig-small_3rdparty_in1k_20230117-9433dc96.pth
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Config: configs/vig/pvig-small_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/pyramid-vig/pvig_s_82.1.pth.tar
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: pvig-medium_3rdparty_in1k
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Metadata:
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FLOPs: 8886000000
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Parameters: 51682000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 83.12
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Top 5 Accuracy: 96.35
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/pvig-medium_3rdparty_in1k_20230117-21057a6d.pth
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Config: configs/vig/pvig-medium_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/pyramid-vig/pvig_m_83.1.pth.tar
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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- Name: pvig-base_3rdparty_in1k
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Metadata:
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FLOPs: 16861000000
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Parameters: 95213000
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Training Data: ImageNet-1k
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In Collection: VIG
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Results:
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- Dataset: ImageNet-1k
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Metrics:
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Top 1 Accuracy: 83.59
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Top 5 Accuracy: 96.52
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Task: Image Classification
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Weights: https://download.openmmlab.com/mmclassification/v0/vig/pvig-base_3rdparty_in1k_20230117-dbab3c85.pth
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Config: configs/vig/pvig-base_8xb128_in1k.py
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Converted From:
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Weights: https://github.com/huawei-noah/Efficient-AI-Backbones/releases/download/pyramid-vig/pvig_b_83.66.pth.tar
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Code: https://github.com/huawei-noah/Efficient-AI-Backbones/tree/master/vig_pytorch
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