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...

In this tutorial, we are going to implement a smile detector algorithm using OpenCV and a pre-trained Haar cascade. Smile detention is a subset of facial recognition technology and can be used for different purposes such as for ensuring that people ...

There are two major problems when training neural networks: overfitting and underfitting. Overfitting is a problem that can occur when the model is too sensitive to the training data. The model will then fail to generalize and perform well on new data...

Training a deep neural network can take hours or even days to complete. It is not practical to train such a neural network every time you want to make predictions. In this case, you can save and then later reload your model.