https://github.com/ry/tensorflow-vgg16

conversation of caffe vgg16 model to tensorflow
https://github.com/ry/tensorflow-vgg16

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conversation of caffe vgg16 model to tensorflow

• Host: GitHub
• URL: https://github.com/ry/tensorflow-vgg16
• Owner: ry
• Archived: true
• Created: 2015-11-14T05:32:04.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2018-12-29T23:54:24.000Z (almost 6 years ago)
• Last Synced: 2024-08-03T01:16:15.336Z (3 months ago)
• Language: Python
• Size: 244 KB
• Stars: 671
• Watchers: 25
• Forks: 286
• Open Issues: 12
• Metadata Files:
  • Readme: README.md

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README

        
# TensorFlow VGG-16 pre-trained model

VGG-16 is my favorite image classification model to run 

because of its simplicity and accuracy. The creators of this model 

published a pre-trained binary that can be used in Caffe.

https://gist.github.com/ksimonyan/211839e770f7b538e2d8#file-readme-md

MD5 (VGG_ILSVRC_16_layers.caffemodel) = 441315b0ff6932dbfde97731be7ca852

This is to convert that specific file to a TensorFlow model and check

its correctness.

Run `make` to download the original caffe model and convert it.

`tf_forward.py` has an example of how to use the generated `vgg16.tfmodel`

file.

If you don't feel like installing caffe, you can download the output here 

https://github.com/ry/tensorflow-vgg16/raw/master/vgg16-20160129.tfmodel.torrent

The input ("images") to the TF model is expected to be [batch, height, width, channel]

where height = width = 224 and channel = 3. Values should be between 0 and 1.

The output ("prob") is a 1000 dimensional class probabiity vector whose indexes

correspond to line numbers in syset.txt.