Skip to content

ramank1137/Scrubland-Field-Delineation

Repository files navigation

Scrubland Field Delineation

This repository is designed to run inside a Docker container. It requires Docker Engine and nvidia-container-toolkit as prerequisites for building the container or pulling it from Docker Hub. Follow the instructions below to install the required dependencies.

Prerequisites

  1. Install Docker Engine from here
  2. Install nvidia-container-toolkit from here

Building Docker Image

After this, the docker image can be built by executing following command inside this github repo folder Scrubland-Field-Delineation

sudo docker build --progress=plain -t <image-name> .

Use the following command to disable progress display.

sudo docker build -t <image-name> .

Pulling Docker Image

Instructions to pull docker image comming soon...

Starting Docker container

To start docker container please run the following command.

sudo docker run --shm-size=60gb --gpus all --init -it -v $(pwd):/app <image-name> bash

Running Script

Inside the container, the required environment is pre-activated for convenience. The script.py is the one that needs to be executed to obtaine vector boundaries of fields, plantation and scrubland. Before running the script, download the model (india_Airbus_SPOT_model.params) from here and place it inside Scrubland-Field-Delineation folder. After this you can run the script using the following command.

python script.py

When a new container is started for the first time, this will prompt a link for authenticating into Google Earth Engine. Click the link or copy-paste it into a browser, then log in using a Google account associated with Google Earth Engine. After authentication, you will receive an access key, which should be pasted into the Docker container to complete the authentication process. Once authenticated, the script will process the specified Region of Interest(ROI) and generate vector boundaries for farms, plantations, and scrubland.

You can set the ROI inside the script.py after ee.Initialize in __main__ block. A boilerplate code for running on a rectangular region instead of any polygon ROI is also provided after the ROI declaration which commented out for ease of testing. Also set the name of the directory which will be used to download images, store predictions and store vector boundaries.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published