Azure/pixel_level_land_classification 📦

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

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jomit/AITrials

Machine Learning sample code and walkthroughs

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Smarker/pybatchai

A Python CLI for Batch AI

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Smarker/travis-deploy-sample

sample travis configuration that references a script to upload a directory to azure blob storage

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Smarker/batchai-workshop

Workshop to run YOLOv3 object detection with Azure BatchAI

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Smarker/character-detection

Language: Python - Size: 68.8 MB - Last synced at: about 1 year ago - Pushed at: about 7 years ago - Stars: 0 - Forks: 0