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Metashape Azure

Installing

# cmd

conda create --name sfm python=3.8 -y
conda activate sfm

pip install "git+https://github.com/Jordan-Pierce/Metashape-Azure.git"

If you are also running Metashape locally, you will need to run the install.py script as well:

# cmd

python install.py

This will add dependencies to the Metashape python environment. Finally, to run the application, use the following command:

# cmd

metashape-azure-mls

Updating

# cmd

conda activate sfm

pip install -U "git+https://github.com/Jordan-Pierce/Metashape-Azure.git"

Running the Application

Metashape-Azure-MLS

  1. Open Azure Machine Learning Studio in Microsoft Edge and login
  2. Navigate to your workspace
  3. Copy the following credentials from the top-right of the page:
    • Subscription ID
    • Resource Group
    • Workspace Name
  4. Enter credentials in the application:
    • Use "Save Credentials" to store for future use
    • Click "Authenticate"
  5. Select your compute cluster from the dropdown
  6. Configure project paths:
    • Input Path: Azure URI to image folder
    • Output Path: Azure URI for project destination
    • Project Name: Unique name for your project

      Note: {output path}/{project name} must not already exist

  7. Select desired SfM parameters
  8. Click "Run on Azure" to start processing

Notes

  • Azure Machine Learning Studio and Authentication must be done in Microsoft Edge
  • You must be connected to the network (i.e., VPN) to access the Azure services.

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Fork of repo for running Agisoft Metashape in Azure via GUI

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  • Python 98.4%
  • Dockerfile 1.6%