Download model and pickle file from following folder [it has two folders 'model' and 'pkl'] https://drive.google.com/open?id=1gLhixTjhBkpeZkJ6DsYKzMdyCVkZUrtF
Send a request in the below link to download Flickr_8k_dataset https://illinois.edu/fb/sec/1713398
You will be receiving an email to download the dataset. There are two zip file
- Flickr8k_Dataset.zip [Images] place all the images into data/images folder
- Flickr8k_text.zip [captions] place all the captions into data/caption folder
After you download all the required files, your directory structure will look like
.
├── ImageCaptioning
├── data # data directory
│ ├── images # All the images from flickr8k dataset
│ └── caption # captions from flickr8k dataset
├── pkl # Pickle Files
│ ├── details.pkl # Details pickle has max description length
│ └── features.pkl # all image feature embedding
│ └── tokenizer.pkl # tokenizer for description
│ └── description.pkl # captions for each image
└── model
│ ├── model-ep002-loss3.670-val_loss3.849.h5 # model saved after epoch 2
│ └── model-ep005-loss3.226-val_loss3.783.h5 # model saved after epoch 5
└── ipython
│ ├── ImageCaptioning.ipynb # ipython notebook
│ └── model.png # network model diagram
├── captioning.py # training module
├── gui.py # gui module
├── prepare.py # helper module
└── test_images.py # testing module
- First Run the captioning.py for training
- Run test_images.py and provide a image path to test images
- Run gui.py for real world testing
