Highlight: This post can come as a very interesting and surprising one. You will see how we can apply a machine learning algorithm on the pixel intensity color with a so-called K-means clustering algorithm. In this way, we would be able to create a compressed version of our image that will have much fewer colors. The picture will be preserved in a lower color resolution, whereas the number of pixels will remain the same. This…
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Highlight: Hello and welcome to the sixth part of our OpenCV with Python post series. In this post we will cover some basic image arithmetic. You will learn how to perform some elementary arithmetic operations on images like addition and subtraction. In addition we will talk about logical bitwise operations (AND, OR, XOR, NOT). Also, we will see how we can implement these operations in some practical tasks in Python. For example, we will explain…
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Highlight: In the previous post we talked how we can manipulate pixels and images in Python using the OpenCV library. Now, it’s time to focus our attention to videos. In this post, you will learn some basic operations which are necessary for building your computer vision applications. First, we will explain how you can load camera frames and video files. Second, you will see how you can read, display and save videos using OpenCV. Third,…
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A team of Computer vision researchers at Leia Inc. have released a large-scale database of 49,368 (~50k) stereoscopic image pairs collected from the popular Lightfield social media app Holopix™. This is the largest dataset of stereoscopic image pairs ever released publicly that contain in-the-wild scenarios captured from mobile phones. For context, the second-largest dataset in this category consists of only 1024 stereoscopic image pairs, almost 50 times less! The dataset is available for download immediately…
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