Back then the Pi Model B shipped with only 256MB of RAM and a 700MHz single core processor. Just over one year ago the was unleashed on the world. This board sported 1GB of RAM and a 900MHz quad-coreprocessor — quite the upgrade from the original single core, 700MHz system! In my opinion, the Raspberry Pi 2 is what made computer vision possible on the Pi platform at least from a Python + OpenCV perspective. In fact, the Raspberry Pi 2 had such a meaningful impact on the computer vision space, that I even took the time to make a all code examples in compatible with the Pi. Personally, I was hoping for a bit more RAM perhaps in the range of 1. But upgrading to a 64-bit processor with 33% increased performance is well worth it. Assumptions In this tutorial, I am going to assume that you already own a with. The goal of this tutorial is to thus guide you step-by-step through the compile and installation process. That said, the Pi 3 is substantially faster than the Pi 2, so the time it takes to compile OpenCV has decreased dramatically. Step 1: Expand filesystem Are you using a brand new install of Raspbian Jessie? However, even with my filesystem expanded, I have already used 48% of my 8GB card! Note: As future versions of openCV are released, you can replace 3. The full URL of the OpenCV 3. Step 4: Python 2. Installing these packages is not a requirement and you can absolutely get OpenCV installed without them, but that said, I highly recommend you install them as other PyImageSearch tutorials in the future will also leverage Python virtual environments. It also keeps your global site - packages neat, tidy, and free from clutter. If you would like a full explanation on why Python virtual environments are good practice, absolutely. Any Python packages in the global site - packages directory will not be available to the cv virtual environment. Similarly, any Python packages installed in site - packages of cv will not be available to the global install of Python. The mkvirtualenv command is meant to be executed only once: to actually create the virtual environment. To fix this, simply execute the source and workon commands mentioned above. Step 5: Compile and Install OpenCV We are now ready to compile and install OpenCV! Timing: 1m 57s Now, before we move on to the actual compilation step, make sure you examine the output of CMake! Start by scrolling down the section titled Python 2 and Python 3. If you are compiling OpenCV 3 for Python 2. Notice how the Interpreter points to our python2. The numpy variable also points to the NumPy installation in the cv environment. Again, the Interpreter points to our python3. If this is the case, access the cv virtual environment using workon cv and re-run the cmake command outlined above. That extra 300MHz makes a big difference! The - j4 command controls the number of cores to leverage when compiling OpenCV 3. The Raspberry Pi 3 has four cores, thus we supply a value of 4 to allow OpenCV to compile faster. However, due to race conditions, there are times when make errors out when using multiple cores. You can verify this using the ls command: - rw - r -- r -- 1 root staff 1895772 Mar 20 20 : 00 cv2. If you do not find the cv2. Our final step is to the OpenCV bindings into our cv virtual environment for Python 2. Make sure OpenCV has been properly installed on your system before blowing away these directories. A mistake here could cost you hoursin compile time. Troubleshooting and FAQ Q. You can check this by running pip freeze and then examining the output, ensuring you see occurrences of both virtualenv and virtualenvwrapper. After I open a new terminal, logout, or reboot my Pi, I cannot execute mkvirtualenv or workon. See reason 3 from the previous question. When I 1 open up a Python shell that imports OpenCV or 2 execute a Python script that calls OpenCV, I get an error: ImportError : No module named cv2. Unfortunately, this error is extremely hard to diagnose, mainly because there are multiple issues that could be causing the problem. To start, make sure you are in the cv virtual environment by using workon cv. If the workon command fails, then see the first question in this FAQ. Make sure that your sym-link to the cv2. This tutorial details the exact steps you need to take to 1 capture photos from the camera module and 2 access the raw video stream. My book not only covers the basics of computer vision and image processing, but also teaches you how to solve real world computer vision problems including face detection in images and video streams, object tracking in video, and handwriting recognition. All code examples covered in the book are guaranteed to run on the Raspberry Pi 2 and Pi 3 as well! Most programs will also run on the B+ and Zero models, but might be a bit slow due to the limited computing power of the B+ and Zero. Summary In this blog post, we learned how to install OpenCV 3 with either Python 2. If you are running a different version of Raspbian such as Raspbian Wheezy or want to install a different version of OpenCV such as OpenCV 2. Sure, I can look into doing some benchmark posts. But keep in mind that the major difference between the Pi 2 and Pi 3 at least in terms of speed is that the Pi 3 is 300Mhz faster than the Pi 2. Hi Adrian, I have a few question 1. By definition, 64-bit value will require more memory than a 32-bit. However, the benefit is more precision. Hi Adrian Your post is invaluable — thank you. I could not have installed OpenCV on my Raspberry Pi 3 without your post. I did encounter one problem as I followed it through. I got a certificate error for the command wget which I worked around easily using wget —no-check-certificate kind regards George What a difference in timings between the PI models. I dusted off my B+ a few days ago and after adding a snazzy new 32GB SSD and Jessie I decided to compile OpenCV. When I started with running guvcview on my RPi3, it gives me a discouraging 2fps with 480 x 320 resolution, yet to see what I can get with opencv. If anyone did a similar project already and can give some pointers, it would be highly appreciated. Adrian, First a thanks…awesome install instructions. I used pip to install it and it appears to run…i. Hi Tony — thanks for picking up a copy of Practical Python and OpenCV. In other words, I developed an opencv app that runs on RaspberryPi and I found a client for it. Apparently now I cant access opencv from outside that virtualenv so I need to compile it again, this time outside Are you using the Raspberry Pi camera module? Or a USB webcam? You might also be interested in where I demonstrate how to access the picamera module and cv2. VideoCapture using the same function. When I try to use cv2. SURF I get an error that there is no such module. Am I missing something? I am currently using opencv 2. Please allow me to echo what others have said — THANK YOU for this fine tutorial! How I was dreading the process of installing CV; yet that worry was ill placed. Your tutorial worked perfectly and the entire process was dare I say it? The clarity of these instructions certainly lends confidence to the quality of your book. I installed this on my pi 3 twice. NumPy was already in Jessie. Hello Adrian, I am having the same problem as Charles. Unfortunate, all this is new to me and I could not really understand how Charles solved the problem nor your response. I followed all the steps and checked the output on each step. I also tried doing the symbolic link again and got a message that the link already exists. I am really stuck. Any further pointer you can provide is much appreciated. If the sym-link already exists, you can simply delete it and re-create it. If not, there was likely an error in your compilation OR a problem with the CMake configuration and the Python bindings were never compiled. Hi Adrian, As requested, i made a try on Jessie Lite. It runs like a charm by following your tutorial very well and sufficiently documented step by step. Instructables says that for a Pi model b the original it should take 10hrs. Could the kernel I am using be nit-so-good? Or maybe I ran out of RAM and it is now performing the switching operations? I have 256mb allocated to the GPU in my current setup Thanks for the tutorial! Otherwise very easy to follow. Funny thing about your RC post and Cat detection posts the other day: I would like to do exactly that, have a cheap rc toy to interact with my cats! Shoot, sorry, I should add that this is an RPI 3 Model b. It should definitely not take 12 hours to compile OpenCV on the Raspberry Pi 3. In fact, it should take less than 2 hours. I think there might be an issue with the multi-processing compile and somewhere a race-condition has been caused, making the compile infinitely spin. I am continually hitting an error just before I run the ¨make -j4¨. I have tried deleting the build directory and re-running cmake multiple times. Any suggests as to what I might be doing wrong wo
