PMC-VQA

Medical image understanding toolkit

A medical visual question-answering dataset and toolkit for training models to understand medical images and instructions.

PMC-VQA is a large-scale medical visual question-answering dataset, which contains 227k VQA pairs of 149k images that cover various modalities or diseases.

GitHub

180 stars
3 watching
11 forks
Language: Python
last commit: almost 2 years ago

Related projects:

RepositoryDescriptionStars
cadene/vqa.pytorchA PyTorch implementation of visual question answering with multimodal representation learning718
zcyang/imageqa-sanThis project provides code for training image question answering models using stacked attention networks and convolutional neural networks.108
milvlg/prophetAn implementation of a two-stage framework designed to prompt large language models with answer heuristics for knowledge-based visual question answering tasks.270
gt-vision-lab/vqa_lstm_cnnA Visual Question Answering model using a deeper LSTM and normalized CNN architecture.377
akirafukui/vqa-mcbA software framework for training and deploying multimodal visual question answering models using compact bilinear pooling.222
hengyuan-hu/bottom-up-attention-vqaAn implementation of a VQA system using bottom-up attention, aiming to improve the efficiency and speed of visual question answering tasks.755
jnhwkim/nips-mrn-vqaThis project presents a neural network model designed to answer visual questions by combining question and image features in a residual learning framework.39
jayleicn/tvqaPyTorch implementation of video question answering system based on TVQA dataset172
mlpc-ucsd/blivaA multimodal LLM designed to handle text-rich visual questions270
open-mmlab/mmactionAn open-source toolbox for action understanding from video data using PyTorch.1,863
viame/viameA comprehensive computer vision toolkit with tools and algorithms for video and image analytics in multiple environments.291
guoyang9/unk-vqaA VQA dataset with unanswerable questions designed to test the limits of large models' knowledge and reasoning abilities.3
danmcduff/iphys-toolboxProvides standardized implementations of algorithms for non-contact physiological measurement using image analysis techniques.193
hms-dbmi/vivA toolkit for interactive visualization of high-resolution bioimaging data.290
hyeonwoonoh/vqa-transfer-externaldataTools and scripts for training and evaluating a visual question answering model using transfer learning from an external data source.20