Computer vision is one of the fields of artificial intelligence. The way machine learning is used to make systems smart enough to solve business problems by finding meaningful relationships from data, similarly, computer vision is used to make systems smart enough to see just like humans by finding meaningful information from images, videos and other visual sources of data. If you start to learn computer vision after learning machine learning, it will be beneficial to you as there are many common Python libraries for machine learning and computer vision. So if you want to know about the best Python libraries for computer vision, this article is for you. In this article, I’m going to introduce you to some of the best Python libraries for computer vision that you should learn while learning computer vision.
Best Python Libraries for Computer Vision
TensorFlow and PyTorch:
Most of the time, we have to build neural network architectures while working on computer vision tasks. Tensorflow is one of the best libraries for working with neural network architectures, so the first Python library that I will recommend you learn for computer vision is Tensorflow. If you are starting computer vision after machine learning, you must have already used TensorFlow. You can also learn PyTorch instead of Tensorflow for computer vision, as these two libraries will provide you with almost the same functionality for computer vision.
OpenCV is one of the most popular computer vision libraries. You will need it wherever you need to use a camera for your computer vision task. Besides the camera, it offers many image processing functions, which will be very useful for you when creating a computer vision application. It can also be used with libraries such as Tensorflow and PyTorch. For example, train a convolutional neural network for face mask detection using Tensorflow, and use this CNN with OpenCV to detect face masks in real-time.
Yolov5 is a pre-trained model for object detection available as a Python library. It is one of the most powerful models for object detection that you can use in any computer vision task where you want to detect the object in an image. Just like Tensorflow and PyTorch, it can also be used with OpenCV to detect objects in real-time using a camera.
Cvlib is one of the most simple libraries for computer vision. To install and use Cvlib, you must have OpenCV and TensorFlow installed on your system. Some of the popular applications where Cvlib can be used are:
- Face Detection
- Object Detection
- Gender Detection
So these were some of the best Python libraries that you should learn for computer vision.
Computer vision is one of the fields of artificial intelligence. If you start to learn computer vision after learning machine learning, it will be beneficial to you as there are many common libraries for machine learning and computer vision. Tensorflow, PyTorch, OpenCV, Yolo, and Cvlib are some of the best libraries that you should learn for computer vision. I hope you liked this article on the best Python libraries for computer vision. Feel free to ask your valuable questions in the comments section below.