基于python+opencv实现国内车牌识别系统源码(带GUI界面+PPT报告+项目说明)数字图像处理课设.zip 数字图像处理课程设计作业 Python3+OpenCV 使用tkinter搭建界面 tmp/文件夹是数字图像处理过程 chepai/文件夹是车牌图片 pic/文件夹是程序界面图 PPT答辩报告 Python opencv 车牌识别 【备注】主要针对正在做毕设的同学和需要项目实战的深度学习cv图像识别模式识别方向学习者。 也可作为课程设计、期末大作业。包含:项目源码\项目操作说明等,该项目可直接作为毕设使用。 也可以用来学习、参考、借鉴。
gituhub 地址:https://github.com/PaddlePaddle/PaddleOCR新機器視覺最前沿的機器視覺與計算機視覺技術206篇原創內
2023-03-10 11:51:20 6.26MB git intellij idea opencv
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Cmake3.10编译好的vs2015 X64Release和vs2015 X64Debug下的Opencv3.4+Opencv_contrib3.4文件,已经再次测试可以运行。
2023-03-10 01:11:10 51.05MB Opencv3.4
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使用Mediapipe检测人脸关键点,结合opencv实现人脸特效
2023-03-09 19:16:16 7.38MB opencv mediapipe
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基本环境: Android studio3.6 NDK:r15c(尽量使用该版本) Opencv3.4.1 android sdk 操作: (1)新建工程,选择Empty Activity,工程名为op (2)File->New->Import Module,然后选择自己的java-opencv的相对应路径,比如,D:\Android\OpenCV-android-sdk\sdk\java (3)修改openCVlibrary341下面的build.gradle中的,compileSdkVersion,buildToolsVersion,minSdkVersion,targetSdkVersi
2023-03-09 16:35:10 117KB api c id
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opencv4.54.4+opencv_contrib-4.x完整源码包,带xfeatures2d组件 opencv4.5.4缺少文件如ffmpeg.dll组件完整包,可编译,不再缺组件了,翻墙好不容易下载下来的(另外,目录下的downloads复制到build的目录下) cmake不再发现红色的错误缺少组件的提示
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主要为大家详细介绍了OpenCV实现简单摄像头视频监控程序,具有一定的参考价值,感兴趣的小伙伴们可以参考一下
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原来是csdn上下载的,代码参数和结构不好,修改了一下,也备注了主要关键处,方便大家使用。双边滤波比较简单。我的平台是vs2013,opencv配置是 2.4.9实现原理是C++,基本的图像读取操作复制等还是用的opencv库函数。
2023-03-08 15:28:15 23.63MB 双边滤波
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双目视觉StereoBM算法OpenCV源代码注释
2023-03-07 16:55:38 6.71MB StereoBM OpenCV源码
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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.
2023-03-06 23:39:38 13.27MB opencv python example
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