Image classification is used to solve several Computer Vision problems; right from medical diagnoses, to surveillance systems, on to monitoring agricultural farms. There are innumerable...
In this post, we will learn about Video Classification. We will go over a number of approaches to make a video classifier for Human Activity Recognition. Basically, you will learn video...
In this tutorial you’ll learn how to do Real-Time Selfie Segmentation using Mediapipe in Python and then build the following 4 applications. Background Removal/Replacement
Background Blur
Background Desaturation
Convert Image to Transparent PNG
https://www.youtube.com/watch?v=aySurynUNAw In this tutorial, we’ll learn how to do real-time 3D pose detection using the mediapipe library in python. After that, we'll calculate angles between body...
In this post, you’ll learn in-depth about the five of the most easiest and effective face detection options available in python, along with the pros and cons of each one of them. You will become capable of obtaining the required balance in accuracy, speed, and efficiency in any given scenario.
In this post, you’ll learn to implement human activity recognition on videos using a Convolutional Neural Network combined with a Long-Short Term Memory Network, we’ll be using two different architectures that you will create in TensorFlow We will also cover some theory about other approaches that can also be used to classify the videos.
In this tutorial you’ll learn how to do Real-Time Selfie Segmentation using Mediapipe in Python and then build the following 4 applications. Background Removal/Replacement
Background Blur
Background Desaturation
Convert Image to Transparent PNG
In last Week’s tutorial, we learned how to work with real-time pose detection and created a pose classification system. In this week’s tutorial, we’ll learn to play a popular game called “Subway Surfers”
In this tutorial, we’ll learn how to do real-time 3D hands landmarks detection using the Mediapipe library in python. After that, we’ll learn to perform hands type classification (i.e. is it a left or right hand) and then draw the bounding boxes around the hands by retrieving the required coordinates from the detected landmarks.
