Firstly, please open this README document using your own web browser: https://github.com/telescopeuser/GCP-SamGu

Video lecture:

https://youtu.be/Bh443uea-U4

Lecture notes:

Notes\Notes_Image_Analysis.pdf

Lab python notebook:

Lab\Lab_Image_Analysis.ipynb

< Using Deep Learning and Transfer Learning to Conduct Customized Image Analysis >

by: Sam Gu [ Data Science Trainer ]

May 2017

1. Lecture: Agenda

Refer to lecture notes: Notes/Notes_Image_Analysis.pdf

2. Lab: Hands-on Datalab Workshop on GCP

Refer to lab workshop: Lab/Lab_Image_Analysis.ipynb

Credit: This python notebook was adapted based on: https://www.kernix.com/blog/image-classification-with-a-pre-trained-deep-neural-network_p11

Image Analysis Lab

Detect Normal or Abnormal Industrial Valves, Using Transfer Learning Technology upon Google's Pre-Trained Deep Neural Network

The use case here is to use drone to provide regular surveillance on remote or dangerous areas, capturing image of industrial equipment like valves, then send the image back for automatic malfunction diagnosis, using machine intelligence. This improves safety and efficiency compared to current human-involved processes, without large investment on wired sensor infrastructure. The core part of this solution involves advanced image analysis in real world.

In this lab, you will carry out a transfer learning example based on Google Inception-v3 image recognition neural network.

Normal Valves:

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Abormal Valves:

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In this Lab, you will learn:

3. Environment Setup for: Hands-on Datalab Workshop on GCP

• Login Google Cloud Platform to start Datalab.

• Create a new notebook to download this lab by running command:

!git clone https://github.com/telescopeuser/GCP-SamGu.git

• Go to folder GCP-SamGu/Lab/, then open notebook Lab_Image_Analysis.ipynb to follow.

Reference:

• Google Cloud Platform Free Registration: https://cloud.google.com/free/
• Google Datalab Quick Start: https://cloud.google.com/datalab/docs/quickstarts

Google Deep Neural Network: Inception-v3:

4. Congratulations! You are now equipped with practical skills to carry out deep leaning image analysis in real world!

You have learnt:

• Deep Learning Basics for Image Analysis
• Real World Image Analysis Needs
• Idea of Transfer Learning
• Architecture of Transfer Learning
• Hands-on Datalab Workshop on GCP

5. [ Optional ]

Export deep features as CSV file, to further analyze in Orange3 tool