June 12, 2019

With the following recipe you can easily create a conda environment with the following installed:

The recipe is tested on Windows 10.

Step 1: Install the prerequisites

Make sure conda is accessible on path by opening the anaconda prompt or your favorite terminal and type:

conda --version

Your NVidia Graphics Driver installed

Step 2: Creating the conda environment

In the same terminal, type the following commands:

conda create -n kerascv python = 3.7 anaconda activate kerascv

This will already add the anaconda packages.

conda install -c anaconda tensorflow-gpu conda install -c conda-forge keras

Add opencv for python. I found no good conda package, so I usually use pip.

pip install opencv-python

For more information about conda environments, refer to the Anaconda Docs

Step 3: Using JupyterLab

JupyterLab is the next-generation web-based user interface for Project Jupyter.

If you are like me and like to use the newest tools you can try jupyter lab. In case you closely followed step 1 and step 2 of this recipe you will already have it installed.

JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors terminals, and custom components in a flexible, integrated, and extensible manner.

I like to add support for ipython widgets to make my notebooks more interactive. To activate the jupyterlab extension, Nodejs is required. Luckily, Nodejs can be installed using conda as well. Usually, I install it into my base environment:

activate base conda install nodejs

Now, the following steps are required to install and activate the extension: