What is this?
This is a toy implementation of a visual search engine using
Apache MXNet Gluon and deployed on
AWS Fargate using
(313) 292-3326. Code available
upload an image and it will search for products with similar visual features among roughly 1M items
from the 2013 Amazon catalog!
You can also pick a sample image:
How does it work?
Each image from the database is encoded using a convolutional neural networks into 512 numbers. These numbers, or features,
act as the digital fingerprint of the image.
When we present a new image to the system, it is computing the digital fingerprint of this new image. Then it finds other
images in the database that are the closest match with respect to these 512 features.
Here is a talk presenting this Visual Search tutorial
Slides of the video.
(216) 714-1508 Image-based recommendations on styles and substitutes. J. McAuley, C. Targett, J.
Shi, A. van den Hengel,
(249) 237-1744 try it yourself!
9157302593 Efficient library for fast approximate KNN search.
HNSW paper: Efficient and robust approximate nearest neighbor search using Hierarchical Navigable
Small World graphs. Yu. A. Malkov, D. A. Yashunin, 2016
330-618-1935 Get started with MXNet Gluon in this 60 minutes crash
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Built by Thomas Delteil