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cs205final's Introduction

Large Scale Computer Vision for Flood Disaster Management

CS 205 Final Project (Spring 2021)

Contributors: Michael Butler, Preston Ching, M. Elaine Cunha

Website

https://msbutler.github.io/cs205final.github.io/

Directory

  • Train/: folder with subdirectories for labeled and unlabeled training data
  • Figures/: folder containing results from performance tests
  • Presentation/: folder containing slides from final presentation
  • _old/: folder containing out-of-date versions of files
  • architecture.py: defines CNN architecture
  • config.py: configures data parameters (i.e., image resize dimensions)
  • run.py: trains one instance of the supervised or semisupervised model
  • semisupervised.py: specifies training methodology for the semisupervised model
  • supervised.py: specifies training methodology for the fully supervised model
  • strong_scaling.py: script for running strong scaling performance tests (see Replication.md for instructions)
  • weak_scaling.py: script for running weak scaling performance tests (see Replication.md for instructions)
  • utils.py: contains functions for image analysis and developing training/testing sets

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