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edit image captioning code

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yunjey
2017-05-29 15:07:40 +09:00
parent 286f7b7589
commit ab5ac31dae
3 changed files with 5 additions and 4 deletions
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2
tutorials/03-advanced/image_captioning/README.md
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@ -56,4 +56,4 @@ $ python sample.py --image='png/example.png'
<br> <br>
## Pretrained model ## Pretrained model
If you do not want to train the model from scratch, you can use a pretrained model. I have provided the pretrained model as a zip file. You can download the file [here](https://www.dropbox.com/s/bmo30z81a4v7m0r/pretrained_model.zip?dl=0) and extract it to `./models/` directory using `unzip pretrained_model.zip`. If you do not want to train the model from scratch, you can use a pretrained model. I have provided the pretrained model as a zip file. You can download the pretrained model [here](https://www.dropbox.com/s/ne0ixz5d58ccbbz/pretrained_model.zip?dl=0) and vocabulary file [here](https://www.dropbox.com/s/26adb7y9m98uisa/vocap.zip?dl=0). Note that you should extract pretrained_model.zip to `./models/` and vocab.pkl to `./data/`.

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tutorials/03-advanced/image_captioning/build_vocab.py
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@ -59,7 +59,7 @@ def main(args):
threshold=args.threshold) threshold=args.threshold)
vocab_path = args.vocab_path vocab_path = args.vocab_path
with open(vocab_path, 'wb') as f: with open(vocab_path, 'wb') as f:
pickle.dump(vocab, f, pickle.HIGHEST_PROTOCOL) pickle.dump(vocab, f)
print("Total vocabulary size: %d" %len(vocab)) print("Total vocabulary size: %d" %len(vocab))
print("Saved the vocabulary wrapper to '%s'" %vocab_path) print("Saved the vocabulary wrapper to '%s'" %vocab_path)
@ -67,7 +67,7 @@ def main(args):
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('--caption_path', type=str, parser.add_argument('--caption_path', type=str,
default='./data/annotations/captions_train2014.json', default='/usr/share/mscoco/annotations/captions_train2014.json',
help='path for train annotation file') help='path for train annotation file')
parser.add_argument('--vocab_path', type=str, default='./data/vocab.pkl', parser.add_argument('--vocab_path', type=str, default='./data/vocab.pkl',
help='path for saving vocabulary wrapper') help='path for saving vocabulary wrapper')

1
tutorials/03-advanced/image_captioning/sample.py
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@ -72,6 +72,7 @@ def main(args):
# Print out image and generated caption. # Print out image and generated caption.
print (sentence) print (sentence)
image = Image.open(args.image)
plt.imshow(np.asarray(image)) plt.imshow(np.asarray(image))
if __name__ == '__main__': if __name__ == '__main__':