A simple implementation of neural image caption generator
Please note that the code in this repo is for use in talks/workshops. There is a lot of room for improvement (in terms of both accuracy and efficiency) so that these aspects can be discussed during the sessions.
You may refer to Tensorflow's im2text Model for a stable and accurate implementation.
- This downloads Flick8K dataset
- The VGG16 model would be downloaded automatically when the model is trained for the first time and would be cached on the disk.
- Alternatively, run
python3 vgg16.py. It would download the VGG16 model, produce the embeddings for a test image and compare with a pre-computed embedding.
mode_list=["train", "test", "debug"]