| #The MIT License (MIT) | |
| # | |
| #Copyright (c) 2015 Andre Queiroz | |
| # | |
| #Permission is hereby granted, free of charge, to any person obtaining a copy | |
| #of this software and associated documentation files (the "Software"), to deal | |
| #in the Software without restriction, including without limitation the rights | |
| #to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| #copies of the Software, and to permit persons to whom the Software is | |
| #furnished to do so, subject to the following conditions: |
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| """ | |
| Example TensorFlow script for finetuning a VGG model on your own data. | |
| Uses tf.contrib.data module which is in release v1.2 | |
| Based on PyTorch example from Justin Johnson | |
| (https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c) | |
| Required packages: tensorflow (v1.2) | |
| Download the weights trained on ImageNet for VGG: | |
| ``` | |
| wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz |