Closed crowoy closed 6 years ago
@crowoy You have functions for that. In the prepare_dataset.py
, you can use the functions load_encoding_model()
and get_encoding(model, image_path)
to get the encoded vector of an image. Once you have the vector, just tweak the test_model.py or use function in it to get the predictions for the image.
How do you go about generating captions on images of your choice?
The testing code seems to reply on the pre-generated
encoded_images.py
file, which only contains encodings for Flickr8k images in this case. Theprepare_dataset.py
file does not seem easy to adapt to encode images of your choice intoencoded_images.py
.Any help would be appreciated.