search in database using deep image similarity
At first we need to extract feature vector for each books in database. feature vectors will saved in a json format file. after that we can use this module to search in created database.
put all book images in databse folder.
run index.py
Put query images in queries folder and run search.py to see the results in results folder.
run server.py and use modify client.html and run it in client side.
Notice: this task use pretrained VGG-16 and when you run each of this modules for first time, the VGG-16 weights will be downloaded in .cache/torch/hub/checkpoints.