Slide 1

Slide 1 text

1 Live-coding Demo to Implement an Image Search Engine from Scratch CVPR 2020 Tutorial on Image Retrieval in the Wild Yusuke Matsui The University of Tokyo

Slide 2

Slide 2 text

2 Implement an Image Search Engine from Scratch ➢ Search by deep-feature ➢ Web-interface ➢ Pure Python Demo: http://www.simple-image-search.xyz/

Slide 3

Slide 3 text

3 ➢ A variety of open-source libraries are available, making it easy to implement and deploy an image-processing system ➢ Demo to implement a content-based image search engine ➢ Only 24 lines (html) + 43 lines (python), w/o comments Implement an Image Search Engine from Scratch Code: https://github.com/matsui528/sis Demo on AWS EC2: http://www.simple-image-search.xyz/ +

Slide 4

Slide 4 text

4 offline online 0.21 0.43 0.02 0.59 offline.py Feature Extractor (Keras, VGG16) 0.17 0.84 0.22 0.86 … server.py Feature Extractor Web Server (Flask) 0.42 0.73 0.31 0.07 0.21 0.43 0.02 0.59 0.17 0.84 0.22 0.86 … Browser Search . ├── feature_extractor.py ├── offline.py ├── server.py ├── static │ ├── feature │ │ ├── img01.npy │ │ └── img02.npy │ ├── img │ │ ├── img01.jpg │ │ └── img02.jpg │ └── uploaded │ └── query01.jpg └── templates └── index.html img feature

Slide 5

Slide 5 text

5 Let’s start!