今天小编就为大家分享一篇关于Opencv+Python实现图像运动模糊和高斯模糊的示例，小编觉得内容挺不错的，现在分享给大家，具有很好的参考价值，需要的朋友一起跟随小编来看看吧

透视变换(Perspective Transformation)是将图片投影到一个新的视平面(Viewing Plane)，也称作投影映射(Projective Mapping)。 如果你想对图像进行校准，那么透视变换是非常有效的变换手段。透视变换的定义为将图像投影到一个新的视平面，通常也被称之为投影映射。

【疲劳驾驶检测系统】 适用人群：本科或专科 技术路线：使用dlib、opencv和wx搭建 实现内容：头部角度，眨眼和打哈气的检测并在相应输出端进行输出提示。 实现语言：python3.7以上 编译器：pycharm2020以上 提示说明：最好直接放在d盘，这样导入好包之后可以直接运行

Cartoonify_reality 即使适当地完成图像处理的基础知识也很方便，否则将需要机器学习模型。该项目是这样的灵感之一，它仅使用核心opencv过滤器和功能将图像和视频卡通化，还使用K-means聚类算法来实现压缩图像。 这种聚类为它提供了所需的基本卡通色彩。 算法-K_Means聚类 滤镜-双边滤镜，轮廓，腐蚀，Canny（边缘检测） 先决条件 您需要什么东西来安装软件以及如何安装它们 scipy numpy cv2 入门 下载python interpeter，最好是3.0版以上的版本。 安装上面给出的前提条件库。 运行vid.py文件将您的Webcamp提要装箱。 取消注释cartoonize.py的最后两行，然后运行以对图像进行卡通化。 $vid.py $cartoonize.py 原始图片 卡通输出 建于

opencv_python-4.1.0-cp36-cp36m-win_amd64.whl下载 opencv_python-4.1.0-cp36-cp36m-win_amd64.whl下载 opencv_python-4.1.0-cp36-cp36m-win_amd64.whl下载

适用于Windows64位，对应Python 3.6版本，OpenCV为3.4.1.15版本；内含有《opencv_contrib_python-3.4.1.15-cp36-cp36m-win_amd64.whl》和《opencv_python-3.4.1.15-cp36-cp36m-win_amd64.whl》两个文件

仅有1个代码文件， 将图片拼接流程拆分成了多个函数，解耦合，可作为视频拼接的基础 包含了去噪的算法，和渐入渐入渐出加权融合的效果，均为可选 if __name__=='__main__': path1='05_L.jpg' path2='05_R.jpg' save='05_M.jpg' spliting_img_path(path1,path2,True,save) 修改路径即可 请导入相关包

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.

线结构光扫描激光条纹提取-opencv+python-附件资源

基于opencv实现多张图像的全景拼接，有效避免鬼影现象，可直接运行。