In many uses of multispectral satellite imagery, clouds obscure what we really care about - for example, tracking wildfires, mapping deforestation, or monitoring crop health. Being able to more accurately remove clouds from satellite images filters out interference, unlocking the potential of a vast range of use cases. With this goal in mind, this training dataset was generated as part of crowdsourcing competition.
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Download VSCode : https://code.visualstudio.com/download
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Download micromamba : https://mamba.readthedocs.io/en/latest/micromamba-installation.html
- Note : The project dependencies are in conda format so it also works with conda but micromamba is faster and the selected tool for the team.
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Create an environment and download the project dependencies.
micromamba create --name gif-7005-project --file environment.yml --yes
- This command will create a micromamba/conda environment with the name
gif-7005-projectand download all the dependencies using theenvironment.ymlfile from this repository.
- This command will create a micromamba/conda environment with the name
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In a terminal, locate the path of your environment.
micromamba env list
- Copy the path of the environment you just created.
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Open VSCode.
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Open the command palette (Ctrl + Shift + P).
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Type
Select interpreterand select the Python option. -
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Click on "Enter interpreter path..."
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Copy & paste the path of your environment to the textbox in VSCode.
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Press enter to confirm the path in VSCode.
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Open the
code/src/verify_setup.ipynbnotebook and click on "Select Kernel" -
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Click on "Python Environments..."
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Select your micromamba environment (here
gif-7005-project) -
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Run the notebook cell to confirm that your setup is correct.
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