Zero-sample image retrieval method and device based on hash coding and graph attention mechanism

The invention relates to a zero-sample image retrieval method and device based on hash coding and a graph attention mechanism. The method comprises the following steps: constructing a hash network anda relationship network; training the hash network and the relational network based on the classification loss of the soft margin; inputting each image in the database into the trained hash network toobtain a corresponding image hash code; and inputting the to-be-queried image into the trained hash network to generate a hash code, calculating the distance between the hash code and the hash code of each image in the database, and returning a query result meeting the requirement according to the distance. According to the method and device, semantic and visual information can be considered at the same time, the similarity relation between classes is fully mined, knowledge migration is better achieved, hash learning is conducted based on classification losses of soft margins, overfitting learning of visible classes c