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OpenCV Introduction for 2.5D raster map processing

This repository is testing for Python 3.5+ although should still work for 2.7+.

To download files open terminal and browse to the folder you want to store the data using the cd command.

Clone the repository by typing:

git clone https://github.com/3Dimaging-ucl/ucl_cege0092

Next move into the folder and open jupyter notebook with:

cd ucl_cegeg075
jupyter notebook

Finally, open the file opencv_practical.ipynb. It is important you run jupyter notebook whilst in the ucl_cege075 directory as otherwise the file paths will not work correctly.

Running on GitHub Codespace

This repository has a .devcontainer subdirectory and a requirenments.txt which contain the cofigutration for a development conatiner in Codespace. To create a Codespace from the Repository click the Code button, then click the Codespaces tab.

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Running on Google Colab

This notebook can be run on google colab with a few minor alterations to avoid the need for setting up a local python environment. First navigate to Google Colab. If you have not already, you will need to create a google account.

On the top bar navigate to GITHUB and enter the organization Upload GitHub Repo3Dimaging-ucl. Open the file opencv_practical.ipynbunder theucl_cege0092` respository.

Next, run the following code cell at the top of the notebook:

!git clone https://github.com/3Dimaging-ucl/ucl_cege0092 data

Open the files tab (small arrow below CO logo in top left) and click refresh if you do not see the folder data. These are all the files required for the practical.

To enable the new file structure to work, you will need to append the string data/ infront of any file paths. For example, file = 'images/aerial_small.tif' becomes file = 'data/images/aerial_small.tif'.

The rest of the practical will now work as normal.

Installing OpenCV on your own machine

Below are my recommendations for install OpenCV on your own machine. However, you should not attempt these if you already have a working python environment on your machine. Either remove your current installation, or use google to find the appropriate way to install OpenCV.

Mac

The easiest way to install OpenCV on a mac is through a package manager. There are two popular package managers for mac HomeBrew and MacPorts. Here we will show you how to install the required dependencies using HomeBrew.

If you have never done any programming on your mac you may need to first install xcode from the app store: The open terminal and type:

sudo xcode-select --install
sudo xcodebuild -license

To install HomeBrew open your terminal and enter:

/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

Add HomeBrew to your path (here I use nano but you can use which ever command line text editor you like):

nano ~/.bash_profile

Append this text to the end of your file and save:

export PATH=/usr/local/bin:$PATH

To refesh your profile type:

source ~/.bash_profile

Next install a local version of python:

brew update
brew install python

Then we will install pip a python specific package installer:

curl -O http://python-distribute.org/distribute_setup.py
python distribute_setup.py
curl -O https://raw.github.com/pypa/pip/master/contrib/get-pip.py
python get-pip.py

Once we have pip we can install the required dependencies:

pip install jupyter numpy opencv-python matplotlib

To be able to clone the content from github as described above type:

brew install git

Windows

To install with windows and to programme in general with python on a windows machine I would recommend using Anaconda. Follow the link and click the Anaconda Installer for Windows link. Then follow all the necessary steps.

Once Anaconda is installed you can open the anaconda prompt that will now be in your start menu. pip comes installed with Anaconda so you can go ahead and install the dependencies:

pip install jupyter numpy opencv-python matplotlib

Finally, to install git to allow us to clone the content:

conda install git

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OpenCV introduction and 2.5D image processing.

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