项目来源：GitHub - Jumpin2/HGA: Reasoning with Heterogeneous Graph Alignment for Video Question AnsweringReasoning with Heterogeneous Graph Alignment for Video Question Answering - GitHub - Jumpin2/HGA: Reasoning with Heterogeneous Graph Alignment for Video Question Answeringhttps://github.com/Jumpin2/HGA
Pytorch code of Reasoning with Heterogeneous Graph Alignment for Video Question Answering.
RequirementsPython 3.6
Pytorch 1.1
datasets：
「dataset」https://www.aliyundrive.com/s/mLg6FxZj1Q1 点击链接保存，或者复制本段内容，打开「阿里云盘」APP ，无需下载极速在线查看，视频原画倍速播放。
feats：HGA中的feat数据-深度学习文档类资源-CSDN下载
Vocabulary：
python3的，HGA中的feat数据-深度学习文档类资源-CSDN下载
Pre-trained Model
count：HGA中的feat数据-深度学习文档类资源-CSDN下载
Testmain.py替换count模型名，运行
python main.py --test --task Count --num_workers 2 --batch_size 64
Trainpython main.py --tount --num_workers 2 --batch_size 64 --lr 0.0001 --model 7 --dropout 0.3 --change_lr none --ablation none --save
