Open CV is hands down the most popular and widely used Python library for vision tasks such as image processing and object and face detection. It is extremely fast and efficient since it is originally written in C++. 2. Sci-Kit Image The conversation over Python image processing libraries is incomplete without Sci-Kit Image. To resize an image, you can use the resize () method of openCV. In the resize method, you can either specify the values of x and y axis or the number of rows and columns which tells the size of the image. Import and read the image: import cv2 img = cv2.imread ("pyimg.jpg") Now using the resize method with axis values: seem to "know" where the faces are in an image? Facebook has implemented facial recognition algorithms into their website, meaning that they cannot only find faces in an image, they can also identify whose face it is as well! Facial recognition is an application of computer vision in the real world. 1 We listed the uses of openCV Projects are: Security systems. Motion structure in movies. Robotics and safety monitoring. Automatic driver assistance system. Search and retrieval of video or image. We implement universal toolbox in openCV for research and development in computer vision. Module 1: Getting Started with Images. Module 2: Basic Image Manipulation. Module 3: Image Annotation. Module 4: Image Enhancement. Module 5: Accessing the Camera. Module 6: Read and Write Videos. Module 7: Image Filtering and Edge Detection. Module 8: Image Features and Image Alignment. Module 9: Image Stitching and Creating Panoramas. OpenCV - Open Source Computer Vision. It is one of the most widely used tools for computer vision and image processing tasks. It is used in various applications such as face detection, video capturing, tracking moving objects, object disclosure, nowadays in Covid applications such as face mask detection, social distancing, and many more. In this tutorial, you will learn how you can process images in Python using the OpenCV library. OpenCV is a free open source library used in real-time image processing. It's used to process images, videos, and even live streams, but in this tutorial, we will process images only as a first step. Before getting started, let's install OpenCV. OpenCV can take advantage of multicore processing and features GPU acceleration for real-time operation. Download chapter PDF OpenCV means Open Source Computer Vision Library. It is an open source computer vision library and it has bindings for C++, Python, and Java. Click for more details. 13. Virtual Drums with OpenCV. The idea of this project is to come up with a virtual drum that is played with a stick in the open air. The stick is to be colored such that when it is in a specific position a drum sound is played. The color is used to help know the position of the stick. OpenCV is a flexible library for computer vision and image processing. The open source project, HDR2EXR, built by developer Kasper Oelemans, combines 33 still 360 degree images into a single EXR file. That file is then used to provide lighting for 3D assets. In the Blender modelling example above by Alexandre Dizeux, the light and reflection Image processing projects ensure various novel theory, architecture for formation algorithm, processing, capture, communication and display images or other multimedia signal. We offer image processing projects for student based on mathematical and statistical repre