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Official Code for "TallyQA: Answering Complex Counting Questions" published at AAAI 2018

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Official Code for TallyQA dataset published in AAAI 2018

For doing simple vs complex classification we used simpcomp.py file. You can load your dataset accordinlgy. TallyQA already has a field issimple that says whether the question is simple or complex so you don't need to run that file. For example,

 {'answer': 4,
  'data_source': 'imported_genome',
  'image': 'VG_100K_2/2410408.jpg',
  'image_id': 92410408,
  'issimple': False, ## this entry here
  'question': 'How many headlights does the black bus have?',
  'question_id': 30095774}

The main paper uses the RN_BG_OG_embd model with the reported hyper-parameters in this repo. There are other types of Relational Models avaialabe in the repo which we tried for our project.

To Run the code as: python main.py --model RN_OG_embd

Don't forget to edit config.py to point to appropriate locations for files and features. Please, feel free to ask if you have any other questions.

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Official Code for "TallyQA: Answering Complex Counting Questions" published at AAAI 2018

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