Simple image search engine
offline.py
: This script extracts a deep-feature from each database image. Each feature is a 4096D fc6 activation from a VGG16 model with ImageNet pre-trained weights.server.py
: This script runs a web-server. You can send your query image to the server via a Flask web-interface. The server finds similar images to the query by a simple linear scan.git clone https://github.com/matsui528/sis.git
cd sis
pip install -r requirements.txt
# Put your image files (*.jpg) on static/img
# Then fc6 features are extracted and saved on static/feature
# Note that it takes time for the first time because Keras downloads the VGG weights.
python offline.py
# Now you can do the search via localhost:5000
python server.py
offline.py
and server.py
.python server.py
, you can access the server from your browser via something like http://ec2-XX-XX-XXX-XXX.us-west-2.compute.amazonaws.com:5000
@misc{sis,
author = {Yusuke Matsui},
title = {Simple Image Search Engine},
howpublished = {\url{https://github.com/matsui528/sis}}
}