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 ...

Image blurring is an important preprocessing step in computer vision. It is used to reduce noise and unnecessary detail in an image.

In this tutorial, we are going to see how to detect faces with OpenCV and Haar cascade then we will use image blurring to only blur the part of the face on the image. Face detection is a computer vision technology that consists of detecting ...

Morphological operations are some transformations applied to grayscale or binary images. Morphological operations apply a structuring element to add or remove some pixels from the boundaries of objects in an input image.

In this tutorial, we will see how to create a blink detector/counter using Dlib, Python, and OpenCV. We will first use the face detector from Dlib to detect faces in a video. Then we will use the shape predictor from Dlib to determine the location ...