In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset.

Related tags

Text Data & NLPMedVQA
Overview

Med-VQA

In this repository we have tested 3 VQA models on the ImageCLEF-2019 dataset. Two of these are made on top of Facebook AI Reasearch's Multi-Modal Framework (MMF).

Model Name Accuracy Number of Epochs
Hierarchical Question-Image Co-attention 48.32% 42
MMF Transformer 51.76% 30
MMBT 86.78% 30

Test them for yourself !

Download the dataset from here and place it in a directory named /dataset/med-vqa-data/ in the directory where this repository is cloned.

MMF Transformer:

mmf_run config=projects/hateful_memes/configs/mmf_transformer/defaults.yaml     model=mmf_transformer     dataset=hateful_memes training.checkpoint_interval=100 training.max_updates=3000

MMBT :

mmf_run config=projects/hateful_memes/configs/mmbt/defaults.yaml     model=mmbt     dataset=hateful_memes training.checkpoint_interval=100 training.max_updates=3000

Heirarchical Question-Image Co-attention:

cd hierarchical \ 
python main.py
Owner
Kshitij Ambilduke
Kshitij Ambilduke
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