Learn about common OpenCV functions, and their applications to get you started into Computer Vision.
Computer Vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. As such many projects involve the usage of images from cameras and videos and the use of several techniques such as image processing and deep learning models.
OpenCV is a library designed to solve common computer vision problems, it’s super popular among those in the field and it’s great for learning and using in production. The library has interfaces for multiple languages, including Python, Java, and C++.
Throughout this article we will cover different (common) functions inside OpenCV, their applications, and how you can get started with each one. Even though I’ll be providing the examples in Python, the concepts and the functions will be the same for the different supported languages.
What exactly are we going to learn today?
Learn Free how to create a virtual pen and eraser with python and OpenCV with source code and complete guide. This entire application is built fundamentally on contour detection. It can be thought of as something like closed color curves on compromises that have the same color or intensity, it's like a blob. In this project we use color masking to get the binary mask of our target color pen, then we use the counter detection to find the location of this pen and the contour to find it.
Learn what is Keras and OpenCV with their applications. See Keras vs OpenCv to understand differences between OpenCv and keras for proper understanding.
Step by step instructions to bind OpenCV libraries with CUDA drivers to enable GPU processing on OpenCV codes. I am renting an EC2 instance with a p3.8xlarge instance in the AWS, which has 4 Nvidia GPUs.
OpenCV is a Python library which lets us work with images. In this course we will start with the basics of OpenCV and finally end with a project on motion detection. How do ML models recognize faces? Or learn to classify different images? Learn all this and more in this video on OpenCV.
Example of Face Detection using OpenCV in Python. We will discuss how we can apply Face Detection using OpenCV. We go straightforward with a practical reproducible example. The logic it the following: We get the image from the URL (or from the hard disk). We convert it to an numpy array and then to a grayscale.