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Greenstand/treetracker-machine-learning

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Goals

This repository contains code for Greenstand's image analysis processes. Here are a few broad goals we are currently working on or hope to achieve in the future:

  • duplicate image detection
  • tree growth/update tracking
  • image quality analysis (visibility)
  • automated species tagging
  • automated plant disease identification

As we gain access to more images, solving these challenges allows Greenstand to better understand the value of each tree capture submitted on the Treetracker app.

Find out more about Greenstand at https://greenstand.org/home, or contact Shubhom (shubhom.bhattacharya@greenstand.org) for questions or concerns.

Operations

Progress on our work is tracked in the Projects section of the repository; if contributing, please add new projects or add notes to existing ones. Best practice is to fork the repository if working locally and merge to master at the completion of a task, especially if collaborating with other devs. However, we often use Google Colab or AWS notebook instances instead for working with .ipynb notebooks on the cloud. If that's the case for your work, please upload the notebook after finishing so others can access in the future. Lastly, if bugs in code or processes are found, please open an issue and/or notify someone via Slack.