![]() ![]() Step #4: Boot the deep learning virtual machine The entire import process should take only a few minutes. Once the dialog opens you’ll want to navigate to where the DL4CV Ubuntu VM.ova file resides on disk: Figure 6: Selecting the pre-configured Ubuntu deep learning virtual machine.įinally, you can click “Import” and allow the virtual machine to import: Figure 7: Importing the Ubuntu deep learning virtual machine may take 3-4 minutes depending on your system. ![]() : Figure 5: Importing the pre-configured Ubuntu deep learning virtual machine. Go ahead and open up the VirtualBox manager.įrom there select File => Import Appliance. Step #3: Import the deep learning virtual machine into VirtualBox This is the actual file that you will be importing into the VirtualBox manager. I have placed this file on my Desktop: Figure 4: The DL4CV Ubuntu VM.ova file. Once you have downloaded the VirtualMachine.zip file, unarchive it and you’ll find a file named DL4CV Ubuntu VM.ova. The file is approximately 4GB so depending on your internet connection this download make take some time to complete. Now that VirtualBox is installed you need to download the pre-configured Ubuntu virtual machine associated with your purchase of Deep Learning for Computer Vision with Python: Figure 3: Downloading the pre-configured Ubuntu deep learning virtual machine. To install VirtualBox, first visit the downloads page and then select the appropriate binaries for your operating system: Figure 1: VirtualBox downloads.įrom there install the software on your system following the provided instructions - I’ll be using macOS in this example, but again, these instructions will also work on Linux and Windows as well: Figure 2: Installing VirtualBox on macOS Step #2: Download your deep learning virtual machine The virtual machine that will be imported into VirtualBox is the guest machine. We call the physical hardware VirtualBox is running on your host machine. VirtualBox will run on macOS, Linux, and Windows. The first step is to download VirtualBox, a free open source platform for managing virtual machines. Access the Python development environment inside the deep learning virtual machine.Download and import your pre-configured Ubuntu deep learning virtual machine.This tutorial is broken down into three parts to make it easy to digest and understand: In the following sections I’ll show you how easy it is to import your Ubuntu deep learning virtual machine. Your purchase of Deep Learning for Computer Vision with Python includes a pre-configured Ubuntu virtual machine for deep learning. Your deep learning + Python virtual machine ![]() How to access the pre-installed deep learning libraries on the virtual machine.How to import the pre-configured Ubuntu virtual machine for deep learning.How to download and install VirtualBox for managing, creating, and importing virtual machines.In the remainder of this tutorial I’ll show you: After you purchase your copy you’ll be able to download the virtual machine and get started with deep learning immediately. This virtual machine is part of all three bundles of my book, Deep Learning for Computer Vision with Python. In order to help you jump start your deep learning + Python education, I have created an Ubuntu virtual machine with all necessary deep learning libraries you need to successful (including Keras, TensorFlow, scikit-learn, scikit-image, OpenCV, and others) pre-configured and pre-installed. Of course, configuring your own deep learning + Python + Linux development environment can be quite the tedious task, especially if you are new to Linux, a beginner at working the command line/terminal, or a novice when compiling and installing packages by hand. When it comes to working with deep learning + Python I highly recommend that you use a Linux environment.ĭeep learning tools can be more easily configured and installed on Linux, allowing you to develop and run neural networks quickly.
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