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Keras预训练模型
==============
在 ImageNet 上预训练过的用于图像分类的模型：
模型概览
| 模型 |
大小 |
Top-1 准确率 |
Top-5 准确率 |
参数数量 |
深度 |
| Xception |
88 MB |
0.790 |
0.945 |
22,910,480 |
126 |
| VGG16 |
528 MB |
0.713 |
0.901 |
138,357,544 |
23 |
| VGG19 |
549 MB |
0.713 |
0.900 |
143,667,240 |
26 |
| ResNet50 |
98 MB |
0.749 |
0.921 |
25,636,712 |
- |
| ResNet101 |
171 MB |
0.764 |
0.928 |
44,707,176 |
- |
| ResNet152 |
232 MB |
0.766 |
0.931 |
60,419,944 |
- |
| ResNet50V2 |
98 MB |
0.760 |
0.930 |
25,613,800 |
- |
| ResNet101V2 |
171 MB |
0.772 |
0.938 |
44,675,560 |
- |
| ResNet152V2 |
232 MB |
0.780 |
0.942 |
60,380,648 |
- |
| ResNeXt50 |
96 MB |
0.777 |
0.938 |
25,097,128 |
- |
| ResNeXt101 |
170 MB |
0.787 |
0.943 |
44,315,560 |
- |
| InceptionV3 |
92 MB |
0.779 |
0.937 |
23,851,784 |
159 |
| InceptionResNetV2 |
215 MB |
0.803 |
0.953 |
55,873,736 |
572 |
| MobileNet |
16 MB |
0.704 |
0.895 |
4,253,864 |
88 |
| MobileNetV2 |
14 MB |
0.713 |
0.901 |
3,538,984 |
88 |
| DenseNet121 |
33 MB |
0.750 |
0.923 |
8,062,504 |
121 |
| DenseNet169 |
57 MB |
0.762 |
0.932 |
14,307,880 |
169 |
| DenseNet201 |
80 MB |
0.773 |
0.936 |
20,242,984 |
201 |
| NASNetMobile |
23 MB |
0.744 |
0.919 |
5,326,716 |
- |
| NASNetLarge |
343 MB |
0.825 |
0.960 |
88,949,818 |
- |
Top-1 准确率和 Top-5 准确率都是在 ImageNet 验证集上的结果。