Visual Search engine with MXNet Gluon and HNSW

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In this talk I introduce a project I worked on, creating a Visual Search engine for 1M Amazon product using MXNet Gluon and the K-Nearest Neighbor search library HNSW. For implementation details, check this repository: https://github.com/ThomasDelteil/VisualSearch_MXNet Video available here: https://www.youtube.com/watch?v=9a8MAtfFVwI Demo website available here: https://thomasdelteil.github.io/VisualSearch_MXNet/

Données & analyses

Thomas Delteil @tdelteil
Visual Search powered by
MXNet Gluon
Applied Scientist | AWS Deep Engine

• Angel.co: 74 visual search startups
• Syte.ai: raised $8M
• Slyce.it
“By 2020, more than half of all mobile
searches will be voice or visual
searches.”
IPG Media Lab
4
Growing Market

6
Index images to lower-dimensional representation
Images: 224x224x3 dimensions 512 dimensions “finger-print”pre-trained CNN (resnet18)
index

7
New Image Query
224x224x3 dimensions 512 dimensions “finger-print”pre-trained CNN (resnet18) k-Nearest Neighbor (k=3)

Demo
8
https://thomasdelteil.github.io/VisualSearch_MXNet/

Notebook
9
https://github.com/ThomasDelteil/VisualSearch_MXNet

Demo Resource
• Python Notebook
• Apache MXNet
• KNN Search: Hierarchical Navigable Small Worlds (hnsw)
• Dataset:
• 8M Amazon products (2013)
• Image-based recommendations on styles and substitutes
J. McAuley, C. Targett, J. Shi, A. van den Hengel
SIGIR, 2015
10

- Develop model using a Jupyter notebook
- Train model on GPU instance
- Package model behind web API in a Docker container, e.g using MXNet Model Server
- Upload container to container registry
- Deploy container to an elastic container service / FARGATE task
- Enjoy quick and linear scaling
- Put the API behind a load balancer with SSL termination
- Enjoy 
Workflow and Operationalization
Elastic
Container
Service
GPU instance Container
Registry
Auto-scaling Load BalancerContainer
HTTPS request
HTTPS response
{
“prediction” : {
{
“item1”:
…
}
}

Thanks!
Feedback, follow-up and questions:
tdelteil@amazon.com
github.com/thomasdelteil
12

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Visual Search engine with MXNet Gluon and HNSW

1. Thomas Delteil @tdelteil Visual Search powered by MXNet Gluon Applied Scientist | AWS Deep Engine

2. 2AMAZON CONFIDENTIAL

3. 3

4. • Angel.co: 74 visual search startups • Syte.ai: raised $8M • Slyce.it “By 2020, more than half of all mobile searches will be voice or visual searches.” IPG Media Lab 4 Growing Market

5. How does it work? 5

6. 6 Index images to lower-dimensional representation Images: 224x224x3 dimensions 512 dimensions “finger-print”pre-trained CNN (resnet18) index

7. 7 New Image Query 224x224x3 dimensions 512 dimensions “finger-print”pre-trained CNN (resnet18) k-Nearest Neighbor (k=3)

8. Demo 8 https://thomasdelteil.github.io/VisualSearch_MXNet/

9. Notebook 9 https://github.com/ThomasDelteil/VisualSearch_MXNet

10. Demo Resource • Python Notebook • Apache MXNet • KNN Search: Hierarchical Navigable Small Worlds (hnsw) • Dataset: • 8M Amazon products (2013) • Image-based recommendations on styles and substitutes J. McAuley, C. Targett, J. Shi, A. van den Hengel SIGIR, 2015 10

11. - Develop model using a Jupyter notebook - Train model on GPU instance - Package model behind web API in a Docker container, e.g using MXNet Model Server - Upload container to container registry - Deploy container to an elastic container service / FARGATE task - Enjoy quick and linear scaling - Put the API behind a load balancer with SSL termination - Enjoy  Workflow and Operationalization Elastic Container Service GPU instance Container Registry Auto-scaling Load BalancerContainer HTTPS request HTTPS response { “prediction” : { { “item1”: … } }

12. Thanks! Feedback, follow-up and questions: tdelteil@amazon.com github.com/thomasdelteil 12

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