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WiDS Datathon 2019
Vani Mandava
Director, Data Science,
Microsoft Research
@vanimt
• Oil Palm is the tree that produces palm oil
• Mostly grown in Africa and South and Central
America
• Deforested land to grow by 53 million hectares
by 2050
• Important to understand where these oil palm
plantations are
• High resolution satellite images combined with
computer vision algorithms can help
80% decline in orangutan population in Borneo
How to map these
plantations?
Datathon Challenge
Planet and Figure Eight in collaboration with
West Big Data hub and WiDS Datathon committee
created a dataset of hi-res satellite imagery
Problem:
Develop a model to detect whether oil palm
plantations are present or not
Dataset on Kaggle
• Supervised Learning
problem
• 15K images in training
set
• 4K images in test set
One approach
Microsoft Custom Vision
• Azure hosted free platform service to build computer vision
model
• Great learning tool for beginners
• Uses AlexNet based Convolutional Neural Networks
Custom vision
• Custom Vision Service (UI or API)
• UI – upload, train and test your model using the UI
• API – use the Azure Python SDK to train and test the model in Python
• Hybrid – Train the model using Custom vision UI and export to your
favorite model such as Tensorflow to run Android apps with the model
Train and Test using custom
vision UI
Download
Kaggle
images locally
Manually uploaded images for training
Test
Python SDK
Steps
1. Install the Custom Vision SDK for Python
2. Get the training and prediction keys
3. Get the training images
4. Upload and tag images (hasoilpalm, nooilpalm)
5. Train the classifier
6. Get and use the default prediction endpoint
Upload and tag all images
Verify training with subset of images
Prediction
output
Hybrid approach
Train in Custom Vision UI and export the model to Tensorflow
creates .pb file
Good luck!
Vani Mandava
Microsoft Research
@vanimt
I’ll buy lunch for the first team who gets to .98+ AUC using Microsoft Custom
vision
(restaurant of your choice!)

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Wids datathon slides_vanim

  • 1. WiDS Datathon 2019 Vani Mandava Director, Data Science, Microsoft Research @vanimt
  • 2. • Oil Palm is the tree that produces palm oil • Mostly grown in Africa and South and Central America • Deforested land to grow by 53 million hectares by 2050 • Important to understand where these oil palm plantations are • High resolution satellite images combined with computer vision algorithms can help
  • 3. 80% decline in orangutan population in Borneo
  • 4. How to map these plantations?
  • 5. Datathon Challenge Planet and Figure Eight in collaboration with West Big Data hub and WiDS Datathon committee created a dataset of hi-res satellite imagery Problem: Develop a model to detect whether oil palm plantations are present or not
  • 6. Dataset on Kaggle • Supervised Learning problem • 15K images in training set • 4K images in test set
  • 8. Microsoft Custom Vision • Azure hosted free platform service to build computer vision model • Great learning tool for beginners • Uses AlexNet based Convolutional Neural Networks
  • 9.
  • 10. Custom vision • Custom Vision Service (UI or API) • UI – upload, train and test your model using the UI • API – use the Azure Python SDK to train and test the model in Python • Hybrid – Train the model using Custom vision UI and export to your favorite model such as Tensorflow to run Android apps with the model
  • 11. Train and Test using custom vision UI
  • 13. Manually uploaded images for training
  • 14.
  • 15. Test
  • 17. Steps 1. Install the Custom Vision SDK for Python 2. Get the training and prediction keys 3. Get the training images 4. Upload and tag images (hasoilpalm, nooilpalm) 5. Train the classifier 6. Get and use the default prediction endpoint
  • 18. Upload and tag all images
  • 19. Verify training with subset of images
  • 21. Hybrid approach Train in Custom Vision UI and export the model to Tensorflow
  • 23.
  • 24.
  • 25.
  • 26. Good luck! Vani Mandava Microsoft Research @vanimt I’ll buy lunch for the first team who gets to .98+ AUC using Microsoft Custom vision (restaurant of your choice!)