Once this project is set up correctly you will have the option to order training data for machine learning.
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Run the application or visit https://ngis.azurewebsites.net/
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Click "Get Started".
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Choose your data sources and how you want to input coordinates. You can either draw on the map, write coordinates yourself or upload a GeoJSON file.
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Decide the data parameters for "training", "validation" and "building percentage".
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Choose which layers you would like to include and the image settings for the data you are retrieving.
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Optional: Enter an email address to get the data sent to you.
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Click "Order" and wait for your data to be downloaded.
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Download your data on the next page, or check your email for a zip file.
- In the "Application" folder of your projects create a file that you name ".env"
- Paste the following variables into the .env file 'NK_WMS_API_KEY' = "" 'AZURE_STORAGE_ACCESS_KEY' = "" 'AZURE_STORAGE_ACCOUNT_NAME' = "" 'SMTP_USER' = "" 'SMTP_PASS' = "" 'SMTP_SERVER' = "" 'SMTP_PORT' = ""
- Fill in the empty variables,
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Open Anaconda prompt and navigate to the root folder of this project.
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Paste this into anaconda prompt: conda create -n bachelor2023 python=3.7
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Paste this into anaconda prompt: conda activate bachelor2023
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Paste this into anaconda prompt: pip install -r requirements.txt
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Two of the packages would not install from the requirements.txt so you have to do it manually. Paste this in into anaconda prompt (one at a time):
conda install libgdal
conda install gdal
You will be asked to downgrade the packages (y/n), write "y".
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Paste this into anaconda prompt: uvicorn main:app --reload
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Click on the http link, and the project will open on a localhost on your computer.
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Open anaconda prompt, and navigate to the root folder of the project.
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Open the Docker program on your computer. Dont go to the next step before Docker is ready to use.
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Paste this into anaconda prompt: "docker build -t docker_env ." this will start building the Docker image.
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After the docker image is built successfully, paste this command in the anaconda prompt: "docker run -p 8000:8000 docker_env".
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Open Docker again, and click on the port number on the running contaner.
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You will now be able to use the project through Docker.