OpenCV

A couple of days ago, artificial intelligence researchers at Meta said that they have made significant progress in building computer vision models, a new AI architecture that can learn about the world from visual cues instead of logic and data, to help them mimic how humans learn about the world and accelerate their training. This emerging field of AI is known as computer vision and it derives meaningful information from digital images, videos, and other visual inputs. And whether you are already working in this field or…

Learn how to create bounding boxes for your imagesPhoto by Héctor J. Rivas on UnsplashOne of the common tasks in deep learning is object detection, a process in which you locate specific objects in a given image. An example of object detection is detecting cars in an image, where you could tally the total number of cars detected in an image. This might be useful in cases where you need to analyze the traffic flow at a specific junction.In order to train a deep learning model to detect specific objects, you need to supply…

Easiest Guideline on Blending and Pasting Image for Computer VisionKaptai Lake in Bangladesh (Image By Author)MotivationIn the modern world, there are thousands of tools by which we can easily perform edit, resize, alter, add different effects, etc. operations on an image. But we hardly care about how it works in the backend. This article will discuss one of the important image processing techniques called blending and pasting images. This knowledge is essential both for image processing and computer vision. Though the…

Image by Siegfried Frech from PixabayPython Watermarking Made Easy: A Comprehensive Comparison of OpenCV, PIL, and filestoolsWatermarking images is an essential task for photographers, artists, and anyone who wants to protect their visual content from unauthorized use. In the Python world, there are many libraries that allow you to add watermarks to your images. In this article, we will compare three popular Python ways for watermarking images: OpenCV, PIL (Python Imaging Library), and filestools. For the last one you…

Start Your Coding for Computer vision with PythonPhoto by Dan Smedley on UnsplashMotivationWe, human beings, perceive the environment and surroundings with our vision system. The human eye, brain, and limbs work together to perceive the environment and act accordingly. An intelligent system can perform those tasks which require some level of intelligence if done by a human. So, for performing intelligent tasks computer/machine needs a vision system. The camera and image are fed to the computer. Computer vision and Image…

Rapid development in machine learning and AI technologies have made significant progress in computer vision for object detection and recognition. Yet creating a system that can recognize humor and amusement in people is still a challenging problem for programmers, since comedy and entertainment are subjective and based on personal tastes and cultural context. Thus, it is tricky creating a system that can precisely determine what individuals find amusing or enjoyable. However, computer vision in facial recognition and…

Photo by Elijah Hiett on UnsplashUsing Canny Edge Detection EfficientlyEdge detection is very common and widely used image processing necessary for many different computer vision applications like data extraction, image segmentation, and in more granular level feature extraction, and pattern recognition. It reduces the level of noise and the number of details in an image but preserves the structure of the image.Canny edge detection in Python is one of the most popular edge detection methods in computer vision. These are…

In this article, we will try to create a slow-motion video using OpenCV( Open Source Computer Vision) library in Python. OpenCV ( is an open-source computer vision and machine learning software library. Now a video is basically a set of moving pictures moving at a rate of about 24 frames per second. If this frame rate is decreased then we get a slow-motion video and that is what we are intended to do. To capture a video we need to create a VideoCapture object. Then we will create a VideoWriter object for writing the…

Super-resolution (SR) implies the conversion of an image from a lower resolution (LR) to images with a higher resolution (HR). It makes wide use of augmentation. It forms the basis of most computer vision and image processing models. However, with the advancements in deep learning technologies, deep learning-based super resolutions have gained the utmost importance. Almost all the deep learning models would make great use of super-resolution. Since Super Resolution mainly uses augmentations of data points, it is also…

Photo by Lysander Yuen on UnsplashSimple, Otsu, and Adaptive Thresholding Implementation with ExamplesOne of the most commonly used segmentation techniques is thresholding. It is widely used in computer vision and is very useful to separate the object that we are interested in from the background. This article will focus on the thresholding techniques in OpenCV.There are three different types of thresholding. We will know how they work at a high level and basically focus on how to use them in OpenCV with examples.What is…