In this tutorial, I'll show you how to use the YOLO model, and specifically YOLOv3, to detect objects in images and real-time videos using Python and OpenCV. YOLO (You Only Look Once) is a single stage object detector, meaning it makes predictions ...

In this tutorial, we will use the YOLO object detection algorithm to detect objects in images and videos. Object detection is a computer vision task that involves identifying and localizing objects in an image or video. It is a challenging task that ...

In this tutorial, we are going to see how to use the bitwise operations AND, OR, XOR, and NOT. Bitwise operations are used in image processing to extract a Region of Interest (ROI) from an image.

In this tutorial, we will learn how to use OpenCV to remove background from videos using a technique named background subtraction. Background subtraction is a common technique used in computer vision to detect moving objects in a video.

Image thresholding is one of the most basic types of image segmentation. It consists of converting an image (a grayscale image) into a binary image (black and white image). In simple thresholding, we manually set a threshold value T and compare ...

In this tutorial, we will see how to perform face recognition using the Dlib library and deep learning. The OpenCV library will be used for performing some simple image processing tasks such as converting the image to grayscale, resizing it, and so on.

In this tutorial, we will see how to detect objects using deep learning and OpenCV.  Object detection is the process of locating objects with bounding boxes in an image or a video. It is one of the most important tasks in computer vision, and it ...

In this tutorial, I will show you how to train a YOLOv4 object detector on a custom dataset using OpenCV and Python. Once our model is trained, we will be able to use it to detect the objects of interest in new images. We will do this by exporting ...