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This project forked from jazzsaxmafia /show_and_tell.tensorflow
License: BSD 2-Clause "Simplified" License
Jupyter Notebook 98.19%
Python 1.81%
show_and_tell.tensorflow's Introduction
Tensorflow implementation of "Show and Tell" http://arxiv.org/abs/1411.4555
Borrowed some code and ideas from Andrej Karpathy's NeuralTalk.
You need flickr30k data (images and annotations)
make_flickr_dataset.py : Extracting feats of flickr30k images, and save them in './data/feats.npy'
model.py : TensorFlow Version
Flickr30k Dataset Download
Extract VGG Featues of Flicker30k images (make_flickr_dataset.py)
Train: run train() in model.py
Test: run test() or test_tf() in model.py
parameters: VGG FC7 feature of test image, trained model path
Once you download Tensorflow VGG Net (one of the links below), you don't need Caffe when testing.
Downloading data/trained model
Extraced FC7 data: download
This is used in train() function in model.py. You can skip feature extraction part by using this.
Pretrained model download
This is used in test() and test_tf() in model.py. If you do not have time for training, or if you just want to check out captioning, download and test the model.
Tensorflow VGG net download
This file is used in test_tf() in model.py
Along with the files above, you might want to download flickr30k annotation data from link
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