Pytorch implementation of three Multiple Instance Learning or Multi-classification papers
Pytorch implementation of three Multiple Instance Learning or Multi-classification papers, the performace of the visual_concept method is the best.
三种多示例学习方法实现,用于图像的多标签,其中 visual_concept效果最好
We will not provide the original dataset, but you can build it using your own dataset. Among them, resized2014 is image dataset, img_tag.txt is the mapping dict file of image to tags, having that, you can generate the zh_vocab.pkl vocabulary file using https://github.com/Epiphqny/Multiple-instance-learning/blob/master/data_process/build_vocab.py
img_tag.txt(with number id represent different image name):
1\tab girl,bottle,car
2\tab boy
3\tab child,bike
...
zh_vocab.pkl:
self.idx2word={1:girl,2:bottle,3:boy,4:car...}
self.word2idx={girl:1,bottle:2,boy:3,car:4...}
Just an example, the realization may have some variation, the lines in the text file are in json format.