This library is used to classify images. Such neural networks are trained on ImageNet for ILSVRC and they can identify the objects from its 1000 classification. The AI Library r1.1 integrated Resnet18, Resnet50, Inception_v1, Inception_v2, Inception_v3, Inception_v4, Vgg, mobilenet_v1, mobilenet_v2 and Squeezenet into our library. The input is a picture with an object and the output is the top-K most probable category.
Figure 1. Classification Example
The following table shows the classification model supported by the AI Library.
| No | Model Name | Framework |
|---|---|---|
| 1 | inception_resnet_v2_tf | Tensorflow |
| 2 | inception_v1_tf | |
| 3 | inception_v3_tf | |
| 4 | inception_v4_2016_09_09_tf | |
| 5 | mobilenet_v1_0_25_128_tf | |
| 6 | mobilenet_v1_0_5_160_tf | |
| 7 | mobilenet_v1_1_0_224_tf | |
| 8 | mobilenet_v2_1_0_224_tf | |
| 9 | mobilenet_v2_1_4_224_tf | |
| 10 | resnet_v1_101_tf | |
| 11 | resnet_v1_152_tf | |
| 12 | resnet_v1_50_tf | |
| 13 | vgg_16_tf | |
| 14 | vgg_19_tf | |
| 15 | resnet50 | Caffe |
| 16 | resnet18 | |
| 17 | inception_v1 | |
| 18 | inception_v2 | |
| 19 | inception_v3 | |
| 20 | inception_v4 | |
| 21 | mobilenet_v2 | |
| 22 | squeezenet |