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 ...

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 ...

In this tutorial, we are going to use OpenCV and Python to automatically read and grade bubble test sheets. This is a beginner tutorial, so we will start the project from scratch while discussing each step.

In this tutorial, we will see how to detect 68 facial landmarks in an image using Python, OpenCV, and the Dlib library.

In this tutorial, we will use deep learning to build a more robust smile detector than the one we built in the previous tutorial where we used a Haar cascade smile detector. We will use the SMILES dataset to train our convolutional neural network...