Let’s get started! Why use multiprocessing for processing a dataset of images?
And distributing the load across all cores of the processor.I’ll also discuss why immediately jumping to Big Data algorithms, tools, and paradigms (such as Hadoop and MapReduce) is the wrong decision - instead, you should parallelize across the system bus first.įrom there we’ll implement our Python and OpenCV multiprocessing functions to facilitate processing a large dataset quickly and easily.įinally, we’ll put all the pieces together and compare how long it takes to process our dataset: multi-threaded applications, including why we may choose to use multiprocessing with OpenCV to speed up the processing of a given dataset. In the first part of this tutorial, we’ll discuss single-threaded vs.
HISTOGRAM MAKER OPENMP CODE
Looking for the source code to this post? Jump Right To The Downloads Section Multiprocessing with OpenCV and Python
HISTOGRAM MAKER OPENMP HOW TO
To learn how to use multiprocessing with OpenCV and Python, just keep reading. I’ll show you in the rest of this tutorial. The image hashing post she is referring to is singled threaded, meaning that only one core of the processor is being utilized - if we switch to using multiple threads/processes we can dramatically speed up the hashing process.īut how do we actually utilize multiprocessing with OpenCV and Python? Is there anything I can do to speedup the process? I used your code to perform image hashing but it’s taking a long time to process the entire dataset. They have provided me with a dataset of ~7.5 million images. I’m trying to apply image hashing to my research project at the university. Hey Adrian, I just read your tutorial on image hashing with OpenCV and really enjoyed it. Today’s tutorial is inspired by PyImageSearch reader, Abigail.
You’ll learn how to use multiprocessing with OpenCV to parallelize feature extraction across the system bus, including all processors and cores on your computer. In this tutorial, you will learn how to use multiprocessing with OpenCV and Python to perform feature extraction. Click here to download the source code to this post
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