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README.md
environment.yml
images_adjustment.ipynb

README.md

Computer vision for images adjustment by homography - tutorial

1. Two options to launch the tutorial notebook

1.1 Create your virtual environment with environment.yml and Conda

Create your virtual environment, given the requirements reported in environment.yml:

conda env create -n adjustment_env -f environment.yml

1.2 Install manually your own virtual environment

Requirements:

  • OpenCV

    • with pip:
    pip install opencv-python
    pip install opencv-contrib-python
    • with conda: conda install -c menpo opencv
  • Numpy

    • with pip: pip install numpy
    • with conda: conda install -c anaconda numpy
  • Matplotlib

    • with pip: pip install matplotlib
    • with conda: conda install -c conda-forge matplotlib
  • iPyWidgets

    • with pip: pip install ipywidgets
    • with conda: conda install -c anaconda ipywidgets

2. Launch the notebook

Activate your virtual environment (named adjustment_env in the following code lines):

conda activate adjustment_env

Add this virtual environment to the environments list in Jupyter:

python -m ipykernel install --user --name=adjustment_env

Run Jupyter notebook:

jupyter notebook

A new page should open in your browser and list the files in your folder. The notebook images_adjustment.ipynb shoud appear in the list. Open it and, in Kernel menu, go to Change kernel and select the adjustment_env.

You can now start following the tutorial.

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