提交 4bb42e25 编写于 作者: C cuicheng01 提交者: qingqing01

Add distilled ResNet50_vd in image classification models. (#2528)

上级 bcad7800
......@@ -156,8 +156,7 @@ python infer.py \
## Supported models and performances
Available top-1/top-5 validation accuracy on ImageNet 2012 are listed in table. Pretrained models can be downloaded by clicking related model names.
Available top-1/top-5 validation accuracy on ImageNet 2012 are listed in table. Pretrained models can be downloaded by clicking related model names.Among them, ResNet50_vd_v2 is the distilled version of ResNet50_vd.
- Released models: specify parameter names
|model | top-1/top-5 accuracy(CV2) |
......@@ -174,6 +173,7 @@ Available top-1/top-5 validation accuracy on ImageNet 2012 are listed in table.
|[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.tar) | 76.50%/93.00% |
|[ResNet50_vc](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vc_pretrained.tar) |78.35%/94.03% |
|[ResNet50_vd](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 79.12%/94.44% |
|[ResNet50_vd_v2](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_v2_pretrained.tar) | 79.84%/94.93% |
|[ResNet101](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar) | 77.56%/93.64% |
|[ResNet101_vd](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_pretrained.tar) | 79.44%/94.47% |
|[ResNet152](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet152_pretrained.tar) | 78.26%/93.96% |
......
......@@ -143,7 +143,7 @@ python infer.py \
## 已有模型及其性能
表格中列出了在```models```目录下支持的图像分类模型,并且给出了已完成训练的模型在ImageNet-2012验证集合上的top-1/top-5精度,
可以通过点击相应模型的名称下载相应预训练模型。
可以通过点击相应模型的名称下载相应预训练模型。其中ResNet50_vd_v2是ResNet50_vd的蒸馏版本。
- Released models: specify parameter names
......@@ -161,6 +161,7 @@ python infer.py \
|[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.tar) | 76.50%/93.00% |
|[ResNet50_vc](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vc_pretrained.tar) |78.35%/94.03% |
|[ResNet50_vd](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_pretrained.tar) | 79.12%/94.44% |
|[ResNet50_vd_v2](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_vd_v2_pretrained.tar) | 79.84%/94.93% |
|[ResNet101](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_pretrained.tar) | 77.56%/93.64% |
|[ResNet101_vd](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet101_vd_pretrained.tar) | 79.44%/94.47% |
|[ResNet152](https://paddle-imagenet-models-name.bj.bcebos.com/ResNet152_pretrained.tar) | 78.26%/93.96% |
......
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