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- [ 2.3 Intel CPU 端知识蒸馏模型] ( #SSLD_intel_cpu )
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- [ 三、CNN 系列模型] ( #CNN_based )
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- [ 3.1 服务器端模型] ( #CNN_server )
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- - [ PP-HGNet 系列] ( #PPHGNet )
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+ - [ PP-HGNet & PP-HGNetV2 系列] ( #PPHGNet )
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- [ ResNet 系列] ( #ResNet )
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- [ ResNeXt 系列] ( #ResNeXt )
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- [ Res2Net 系列] ( #Res2Net )
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<a name =" PPHGNet " ></a >
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- ## PP-HGNet 系列
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+ ## PP-HGNet & PP-HGNetV2 系列
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- PP-HGNet 系列模型的精度、速度指标如下表所示,更多关于该系列的模型介绍可以参考:[ PP-HGNet 系列模型文档] ( PP-HGNet.md ) 。
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+ PP-HGNet & PP-HGNetV2 系列模型的精度、速度指标如下表所示,更多关于该系列的模型介绍可以参考:[ PP-HGNet 系列模型文档] ( PP-HGNet.md ) 、 [ PP-HGNetV2 系列模型文档 ] ( PP-HGNetV2 .md) 。
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| 模型 | Top-1 Acc | Top-5 Acc | time(ms)<br >bs=1 | time(ms)<br >bs=4 | time(ms)<br />bs=8 | FLOPs(G) | Params(M) | 预训练模型下载地址 | inference模型下载地址 |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
@@ -148,6 +148,16 @@ PP-HGNet 系列模型的精度、速度指标如下表所示,更多关于该
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| PPHGNet_small_ssld | 0.8382 | 0.9681 | 2.46 | 5.12 | 8.77 | 8.53 | 24.38 | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_small_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_small_ssld_infer.tar ) |
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| PPHGNet_base_ssld | 0.8500 | 0.9735 | 5.97 | - | - | 25.14 | 71.62 | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_base_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_base_ssld_infer.tar ) |
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+ | 模型 | Top-1 Acc | Top-5 Acc | time(ms)<br >bs=1 | time(ms)<br >bs=4 | time(ms)<br />bs=8 | FLOPs(G) | Params(M) | stage-1预训练模型下载地址 | stage-2预训练模型下载地址 | inference模型下载地址(stage-2) |
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+ | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
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+ | PPHGNetV2_B0 | 0.7777 | 0.9391 | 0.52 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNet_tiny_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNet_tiny_infer.tar ) |
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+ | PPHGNetV2_B1 | 0.7918 | 0.9457 | 0.58 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B1_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B1_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B1_ssld_infer.tar ) |
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+ | PPHGNetV2_B2 | 0.8174 | 0.9588 | 0.95 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B2_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B2_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B2_ssld_infer.tar ) |
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+ | PPHGNetV2_B3 | 0.8298 | 0.9643 | 1.18 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B3_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B3_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B3_ssld_infer.tar ) |
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+ | PPHGNetV2_B4 | 0.8357 | 0.9672 | 1.46 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B4_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B4_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B4_ssld_infer.tar ) |
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+ | PPHGNetV2_B5 | 0.8475 | 0.9732 | 2.84 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B5_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B5_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B5_ssld_infer.tar ) |
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+ | PPHGNetV2_B6 | 0.8630 | 0.9784 | 5.29 | - | - | - | - | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B6_ssld_stage1_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPHGNetV2_B6_ssld_pretrained.pdparams ) | [ 下载链接] ( https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/PPHGNetV2_B6_ssld_infer.tar ) |
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<a name =" ResNet " ></a >
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## ResNet 系列 <sup >[[ 1] ( #ref1 )] </sup >
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