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This almost always begins with a conversion to grayscale, but it can also be a color filter, gradient, or a combination of these. Next, a lot of image and video analysis boils down to simplifying the source as much as possible. ALTERNATIVE TO OPENCV FOR MAC CODESome things, like directional tracking, is going to require a succession of images (frames), but something like facial detection, or object recognition can be done with almost the exact same code on images and video. Thus, image recognition and video analysis use identical methods for the most part. At the core, however, they are static frames, just like images. With the way just about every video camera records today, recordings are actually frames, displayed one after another, 30-60+ times a second. Ready? Let's dive off the deep-end!įirst, we should understand a few basic assumptions and paradigms when it comes to image and video analysis. If you get no errors, then you are ready to go. Make sure your installations were successful by running Python, and doing: import cv2 ALTERNATIVE TO OPENCV FOR MAC FULLWe will wind up using the full installation of OpenCV later in this series, so you can feel free to get it if you like, but these 3 modules will keep us busy for a while! ![]() There are some operations for OpenCV that you will not be able to do without a full installation of OpenCV (about 3GB in size), but you can actually do quite a bit with the fairly minimal installation of python-OpenCV. Finally, we are using the python-specific bindings for OpenCV called python-OpenCV. Numpy is used for all things "numbers and Python." We are mainly making use of Numpy's array functionality. We will show a couple of examples using it here. Matplotlib is an optional choice for displaying frames from video or images. ![]() ALTERNATIVE TO OPENCV FOR MAC INSTALLPip3 install matplotlib or apt-get install python3-matplotlib. You may need to apt-get install python3-pip. Pip3 install numpy or apt-get install python3-numpy. Not familiar with using pip? See the Pip installation tutorial for help. Download the appropriate wheel (.whl) file, and install using pip. Python-OpenCV - There are alternative methods, but this is the easiest. You will need two main libraries, with an optional third: python-OpenCV, Numpy, and Matplotlib. Getting started with OpenCV's Python bindings is actually much easier than many people make it out to be initially. We will be working through many Python examples here. OpenCV is used for all sorts of image and video analysis, like facial recognition and detection, license plate reading, photo editing, advanced robotic vision, optical character recognition, and a whole lot more. Welcome to a tutorial series, covering OpenCV, which is an image and video processing library with bindings in C++, C, Python, and Java. ![]()
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