![]() In this post, we are sharing Docker image for OpenCV 3.4.3, and the recently released OpenCV 3.4.4 and OpenCV 4.0. In addition to OpenCV, the image also has dlib and a Facial Landmark Detection example code. Every day we receive a few emails and comments on our posts about OpenCV and Dlib installation. Even with the detailed and tested instructions, sometimes it is tough for people to get a system up and running. So, we have been thinking of providing a solution for people who have struggled with installation issues. One way to solve this problem is to provide a Virtual Machine (VM) with all the libraries installed. A huge downside of using a VM is the large file people need to download. Sometimes it can be 10s of GBs. A smarter and newer way to solve this problem is to provide a Docker image. Typically a Docker image size is much smaller than a VM. Our Docker image, for example, is just 1 GB in size (compressed size). In addition, it starts much faster than a VM and typically runs applications much faster compared to a VM. Docker is just one of those minimal things that can make your life exceedingly simple. Notepad for mac web design. Another great feature of Brackets is Extract which lets you automatically get color, font, gradient, and measurement information from a Photoshop Document file. When you are using the Live Preview feature, Brackets will open a Chrome window which will automatically reflect any changes to CSS and HTML of your code. It’s a great way to visualize your code. The Live Preview feature allows a developer to instantly see the changes he is making to his code. Probably the best feature of Brackets is Live Preview. Docker run -it --privileged --pid=host debian nsenter -t 1 -m -u -n -i sh. To enter the docker VM on my Mac. Once in the VM, you can use tools like ‘top’ to watch the processes running in the VM. The VM is a stripped down version of Alpine Linux so you can even install any debugging tools you want using the Alpine package manager. Also, as we’ll see, the same docker image can be used on Windows, Ubuntu and MacOS. If you are stuck with OpenCV installation or if you want to try out the new OpenCV-3.4.4 and OpenCV-4.0 ( released on 20th November 2018 ), without actually installing it on your system, this docker image is the perfect match for you. This post is split into five sections • Section 1: How to install Docker on Linux, MacOS and Windows. • Section 2: How to use Docker image for OpenCV. This image also comes with dlib pre-installed. • Section 3: How to run Facial Landmark Detection demo code on Docker Image • Section 4: How to make changes to a Docker image. Docker Installation In this section, we will learn how to install Docker on Ubuntu, MacOS, and Windows. The docker image has been updated to enable X11-Forwarding and now also contain an example to test installation. Use docker pull to get the latest image. To use the docker image, use the following instructions: docker pull spmallick/opencv-docker:opencv Once, the image is downloaded, we can start it using the following command docker run --device=/dev/video0:/dev/video0 -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -p 5000:5000 -p 8888:8888 -it spmallick/opencv-docker:opencv /bin/bash Let’s take a moment to examine this command in detail: • –device=/dev/video0:/dev/video0 allows use of webcam • -v /tmp/.X11-unix:/tmp/.X11-unix helps in X11 forwarding so that we can use functions like cv::imshow. • -e is used to pass an environment variable. • -it starts an interactive session • -p sets up a port forward. This flag maps the container’s port to a port on the host system. • /bin/bash runs.bashrc file on startup The image has OpenCV 3.4.3 installed in /usr/local, OpenCV 3.4.4 in ~/installation/OpenCV-3.4.4 and OpenCV 4.0.0 in ~/installation/OpenCV-master. By default, whatever changes you make in your docker image are NOT saved. To commit changes made to the docker image, we need to follow the steps below. We will refer to the image of the terminal below as an example • Find the Container ID: The easiest way to find it out is to note the text following in your docker container. Besides being portable, it has the power to take on many recording projects you throw at it. It may be good for writers or web users on the go but not for a music producer. For that, you’ll need a desktop machine, which we’ll get into later. Which macbook is the best. On the other hand, Macbook Pros are fair for music production. I’m not talking about big film scoring projects. For example, in the image above, the docker container ID is 56a07cf4614c. Also, note that Container ID will vary every time you use docker run to create a new container. • Make a change: In the example above, we create a simple file HelloUser.sh that outputs some text when run from the command line. • Exit: Once the changes have been made, we need to exit the container using exit command.
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АвторНапишите что-нибудь о себе. Не надо ничего особенного, просто общие данные. Архивы
Март 2019
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