johnarevalo/gmu-mmimdb

Source code for training Gated Multimodal Units on MM-IMDb dataset

Source code for Gated Multimodal Units for Information Fusion.

Dependencies

• Theano
• Fuel
• Blocks

Make dataset

You can download the ready-to-use Fuel format version: multimodal_imdb.hdf5 (archive.org mirror) and metadata.npy (archive.org mirror).

Alternatively, you can build it manually:

• Get the following files and uncompress it in the root folder of this project:

  • MM-IMDb dataset (archive.org mirror)
  • word2vec pretrained model
  • vgg pretrained model
  • class names: synsets_words.txt

• Create the list.txt file:

  ls dataset/*.json > list.txt
  

• Run the make script:

  python3 make_dataset.py gmu.json
  

Getting more movies

You can extend the dataset by adding more IMDb IDs to the links.csv file and run get_data.py script to crawl other movies.

Train and eval the model

Generate random configurations:

python3 generators/gmu.py gmu.json

Train the model and then report performance in test set (e.g. best conf for GMU model #23):

python3 run.py json/gmu_23.json