Build real-world computer vision applications and develop cool demos using OpenCV for Python, About This Book, Learn how to apply complex visual effects to images using geometric transformations and image filtersExtract features from an image and use them to develop advanced applicationsBuild algorithms to help you understand the image content and perform visual searches, Who This Book Is For, This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV-Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on., What You Will Learn, Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like imageDetect and track various body parts such as the face, nose, eyes, ears, and mouthStitch multiple images of a scene together to create a panoramic imageMake an object disappear from an imageIdentify different shapes, segment an image, and track an object in a live videoRecognize an object in an image and build a visual search engineReconstruct a 3D map from imagesBuild an augmented reality application, In Detail, Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we are getting more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Web developers can develop complex applications without having to reinvent the wheel., This book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off with applying geometric transformations to images. We then discuss affine and projective transformations and see how we can use them to apply cool geometric effects to photos. We will then cover techniques used for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications., This book will also provide clear examples written in Python to build OpenCV applications. The book starts off with simple beginner's level tasks such as basic processing and handling images, image mapping, and detecting images. It also covers popular OpenCV libraries with the help of examples., The book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation., Style and approach, This is a conversational-style book filled with hands-on examples that are really easy to understand. Each topic is explained very clearly and is followed by a programmatic implementation so that the concept is solidified. Each topic contributes to something bigger in the following chapters, which helps you understand how to piece things together to build something big and complex.

本文为大家分享了使用opencv处理两张图片帧差的具体代码，供大家参考，具体内容如下 这个程序是两张图片做帧差，用C++实现的，把不同的地方用框框起来，仔细读一下程序，应该还是蛮简单的哈哈，opencv处理图片的基础。 opencv配置不用我说了吧，源码cmake编译，然后导入vs即可。 #include #include using namespace std; using namespace cv; int main() { Mat currentframe, previousframe; Mat img1, img2,

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