models/research/slim/nets/nasnet at master · tensorflow/models · GitHub

  • This directory contains the code for the NASNet-A model from the paper Learning Transferable Architectures for Scalable Image Recognition by Zoph et al.
  • One of the models is the NASNet-A built for CIFAR-10 and the other two are variants of NASNet-A trained on ImageNet, which are listed below.
  • Two NASNet-A checkpoints are available that have been trained on the ILSVRC-2012-CLS image classification dataset.
  • More information on integrating NASNet Models into your project can be found at the TF-Slim Image Classification Library.
  • To get started running models on-device go to TensorFlow Mobile.

models – Models and examples built with TensorFlow

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Fix nasnet image classification and object detection by moving the option to turn ON or OFF batch norm training into it’s own arg_scope used only by detection

This directory contains the code for the NASNet-A model from the paper Learning Transferable Architectures for Scalable Image Recognition by Zoph et al. In nasnet.py there are three different configurations of NASNet-A that are implementented. One of the models is the NASNet-A built for CIFAR-10 and the other two are variants of NASNet-A trained on ImageNet, which are listed below.

Two NASNet-A checkpoints are available that have been trained on the ILSVRC-2012-CLS image classification dataset. Accuracies were computed by evaluating using a single image crop.

Here is an example of how to download the NASNet-A_Mobile_224 checkpoint. The way to download the NASNet-A_Large_331 is the same.

More information on integrating NASNet Models into your project can be found at the TF-Slim Image Classification Library.

To get started running models on-device go to TensorFlow Mobile.

Run eval with the NASNet-A mobile ImageNet model

Run eval with the NASNet-A large ImageNet model

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models/research/slim/nets/nasnet at master · tensorflow/models · GitHub