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Description: 好多opencv的应用程序界面中在MFC中显示图像，但是我发现这些显示功能大部分用到了一个叫CvvImage的类，最近使用opencv2.3.1，发现找不到这个类了。 没有具体研究过opencv ,但是opencv在MFC中显示图像需要用的一个叫做CvvImage的类的DrawToHDC()的函数，但是我在2.3.1下却怎么也没有找到这个类，和这个函数。在2.3.1的文档下没有关于这个的任何资料，不知道是不是新版本的opencv去掉了这个类，或者用其他的方式实现了。所以我需要用以前的方式实现这个类。在网上找了一些资料。发现这个问题可以这样处理。 我们可以自己建立一个CvvImage.h和一个CvvImage.cpp的文件，添加到工程中。这样我们在工程中包含上这个CvvImage.h的头文件，就可以正常的按照以前的方式使用CvvImage类将图像绘制到MFC控件中了-Many opencv application interface in the MFC display images, but I found that most of these display features used in a class called CvvImage, the recent use of opencv2.3.1, found that the class can not find. There is no specific study of the opencv, but opencv in the MFC to display the image needs to be used in a class called DrawToHDC () function, but I did not find the kind of 2.3.1 under the CvvImage, and this function. There is no information about this in the 2.3.1 document, and it is not known whether the new version of OpenCV has removed this class, or has been implemented in other ways. So I need to use the old way of this class. On the Internet for some information. Found the problem can be handled in this way. We can create a CvvImage.h and a CvvImage.cpp file, added to the project. So we in the project includes the CvvImage.h header file, you can normally use the CvvImage class in accordance with the previous way draws the image to the MFC control.
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Size: 3072 |
Author: hongh |
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Description: 编程实现颜色标量量化。输入为24位彩色图像，将RGB分量分别保持头3位、头3位、头2位的值不变，其余各位变为10000、10000和100000，观察处理后的图像的颜色失真情况。注意OpenCV中的RGB分量的存储顺序为BGR。-Programming color scalar quantization. Enter the 24-bit color images, the RGB components respectively held the first three, the first three, the first two of the same values, the rest of you into 10000,10000 and 100000 observe the color image post-processing distortion. Note OpenCV RGB components stored in the order of BGR.
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Author: 高俊秋 |
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Description: 基于opencv的去噪算法比较以及霍夫变换，另外有3篇有关去噪以及图像识别类的相关文献-Compare opencv based de-noising algorithm and Hough transform, and a further three relevant literature on denoising and image recognition class
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Size: 14721024 |
Author: jerry |
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Description: Kinect和OpenCV实现简单的点云三角化，用最小二乘法计算法线，并实时显示获得的模型。建立在OpenFrameworks框架上，编译需要安装OpenFrameworks并放到myApps目录里，还需要Kinect SDK 1.7和OpenCV 2.4.3。-Kinect and OpenCV to achieve a simple point cloud triangulation, using the least square method to calculate the normal, and real-time display of the model. Built on the OpenFrameworks framework, the compiler needs to install OpenFrameworks and put it into the myApps directory, but also requires SDK Kinect 1.7 and 2.4.3 OpenCV.
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Size: 14336 |
Author: a88273 |
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Description: 1.本程序主要处理BMP位图。
2.为了方便读者学习，程序各步骤都被拆分开实现了，通过点击相应按钮可以看到每个步骤处理的结果。
3.如果是进行人脸识别，需要先打开一幅位图依次进行“人脸检测与定位”操作和“人脸特征标注”操作，然后再打开需要比较的第二幅位图，也是依次进行所有操作，最后进行识别以区分先后两个人脸。-opencv Face recognition
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Size: 14800896 |
Author: 刘广熠 |
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Description: 视频抓取图像帧
VS2010解决方案按OpenCV相关配置
1.读入视频文件
将视频加载至内存，文件名需按正确路径添加
2.逐帧读取文件
将视频逐帧读取，并每帧读取成图片保存
3.帧图像保存
帧图像名包括图像名和序号-Video capture image frames
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Size: 23553024 |
Author: zhangxiaoping |
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Description: 使用opencv V2.3.9，实现对视频文件的切割。将切割后的视频文件保存为bmp文件，保存在文件夹下面。-Use Opencv V2.3.9 to split the video file into pictures.And the splitted picture s format is bmp.The files will be saved in folder
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Size: 2638848 |
Author: 刚之旅 |
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Description: 基于opencv的手势识别
1、hog : hog特征提取
2、hogTainer ： 样本训练，利用了SVM方式
3、gestureRecognition ： 手势识别，利用了训练得出的线性分类器进行识别分类
训练样本在hog文件夹中，对应gesture_a到gesture_e ，五种手势-Gesture recognition 1, hog: hog feature extraction 2, hogTainer: sample training, the use of SVM mode 3, gestureRecognition: gesture recognition using training resulting linear classifier for recognition and classification of training samples in hog folder corresponding to gesture_a gesture_e, five kinds of gestures
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Size: 13327360 |
Author: BoYK |
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Description: opencv
def random_color(random):
Return a random color
icolor = random.randint(0, 0xFFFFFF)
return cv.Scalar(icolor & 0xff, (icolor >> 8) & 0xff, (icolor >> 16) & 0xff)
if __name__ == __main__ :
# some constants
width = 1000
height = 700
window_name = Drawing Demo
number = 100
delay = 5
line_type = cv.CV_AA # change it to 8 to see non-antialiased graphics
# create the source image
image = cv.CreateImage( (width, height), 8, 3)
# create window and display the original picture in it
cv.NamedWindow(window_name, 1)
cv.SetZero(image)
cv.ShowImage(window_name, image)
# create the random number
random = Random().....To Be continued-opencv
def random_color(random):
Return a random color
icolor = random.randint(0, 0xFFFFFF)
return cv.Scalar(icolor & 0xff, (icolor >> 8) & 0xff, (icolor >> 16) & 0xff)
if __name__ == __main__ :
# some constants
width = 1000
height = 700
window_name = Drawing Demo
number = 100
delay = 5
line_type = cv.CV_AA # change it to 8 to see non-antialiased graphics
# create the source image
image = cv.CreateImage( (width, height), 8, 3)
# create window and display the original picture in it
cv.NamedWindow(window_name, 1)
cv.SetZero(image)
cv.ShowImage(window_name, image)
# create the random number
random = Random().....To Be continued
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Author: Phindx |
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Description: Python script to detect faces. It uses two haar cascade trained to recognise faces and eyes. The haar cascade are included. In uses OpenCV so it is required.
The script is written in Python 3.
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Size: 189440 |
Author: Magre94 |
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Description: 基于VS编写的3阈值OTSU图像分割算法。应用opencv。适用于图像分割入门学习。-3 threshold OTSU image segmentation algorithm based on VS. Application opencv. Suitable for image segmentation.
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Size: 7453696 |
Author: liusiyan |
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Description: zbar+openCV识别二维码,
项目在例子文件夹下面
需要额外在自己的项目修改关于openCV的有关配置，主要是库文件头文件等等
openCV版本我采用的是3.0，如果是其他版本，请自行测试
-zbar openCV zbar openCV zbar openCV zbar openCV zbar openCV vs2015
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Size: 7790592 |
Author: 张深圳 |
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Description: 需要说明的是：本文示例图中的目标状态在计算上是最快捷的，首先取数很方便，一般地查看目标在第i个位置上的值，则需要访问数组goal[i]，而这里goal[i]==i，故而无需访问数组；第二，要想知道数码n的目标位置，则需要找到goal[i]==n，然后row=i/3,col=i%3. 但是这里的话，row=n/3,col=n%3. 当我们用8位无符号整型来表示各个数码值(0~8)时，n/3和n%3操作是非常快的，比访问数组还快。
程序还提供一种玩游戏模式，即用户自己通过W,S,A,D四个键分别控制空格往上、下、左、右四个方向移动一步，功能很简单，界面部分是用OpenCV做的。界面部分和搜索部分是完全分离的，demo文件中main函数部分显示了如何将它们组合使用。(Need explanation is: This paper sample figure in the target state is the most efficient in calculation, the first number is very convenient, generally view the targets in the I position on the value, requires access to an array of goal[i], where goal[i]==i, therefore no need to access the array; second, to know the digital n the position of the target, you need to find goal[i]==n, row=i/3 and col=i%3., but here, row=n/3, col=n%3. when we use 8 bit unsigned integer to the digital value (0~8), n/3 and n%3 operations are very fast, faster than accessing array.
Program also provides a play game mode, that is, users themselves through W, S, A, D, four keys, respectively, control space, up, down, left, right four directions move a step, the function is very simple, the interface part is done with OpenCV. The interface section is completely separate from the search section, and the main function section in the demo file shows how to combine them.)
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Size: 466944 |
Author: llii
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Description: 粒子滤波跟踪，在VS2013环境下运行，opencv版本是3.0，程序可以直接运行，用时修改一下视频路径(Particle filter tracking, running in VS2013 environment, opencv version is 3, the program can be run directly, modify the video path when used)
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Size: 5391360 |
Author: hellsing
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Description: 使用opencv相关函数实现鱼眼镜头的矫正(using the opencv3.3 and its function to modify the distortion of fisheye camera.)
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Size: 32768 |
Author: Vincent...
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Description: 该资料中包含了《OpenCV By Example》中文版以及例程程序，该书的目录如下所示：
第1章 OpenCV的探险之旅;
第2章 OpenCV基础知识介绍;
第3章 图形用户界面和基本滤波;
第4章 深入研究直方图和滤波器;
第5章 自动光学检测、目标分割和检测;
第6章 学习目标分类;
第7章 识别人脸部分并覆盖面具;
第8章 视频监控、背景建模和形态学操作;
第9章 学习对象跟踪;
第10章 文本识别中的分割算法;
第11章 使用Tesseract识别文本;(The archive contains the Chinese version of "OpenCV By Example" and the example program. The contents of this book are as follows:
Chapter 1 An expedition to OpenCV;
Chapter 2 OpenCV basic knowledge introduction;
Chapter 3 Graphical user interface and basic filtering;
Chapter 4 In-depth study of histogram and filter;
Chapter 5 Automatic optical detection, object segmentation and detection;
Chapter 6 Learning object classification;
Chapter 7 Identify the face part and cover the mask.
Chapter 8 Video surveillance, background modeling and morphological operation.
Chapter 9 Learning object tracking;
Chapter 10 The segmentation algorithm in text recognition;
Chapter 11 Using Tesseract to identify the text;)
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Size: 66423808 |
Author: flypig1994 |
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Description: 1.首先从文件菜单打开程序目录下的car.avi视频,系统将显示视频的第一帧。
2.点击背景提取菜单，稍后会提取出背景并显示在打开的第二个窗口中。
3.当提取出背景后，点击检测跟踪菜单，对车辆进行检测和跟踪。
4.点击轨迹绘制菜单，绘制车辆的轨迹。
注：由于使用OpenCV打开AVI视频文件需要视频解码器，故在程序运行前请在电脑上先安装DivX类型的的视频解码器，否则将出现无法打开文件的错误。本程序使用的是OpenCV2.1版本，在没有安装此版本软件的机器上运行时需要将cv210.dll,cvaux210.dll,cvcore210.dll,highgui210.dll,ml210.dll这五个文件拷贝至*.exe可执行文件下。(First, open the CR. AVI video from the file menu and the system will display the first frame of the video.
2. Click on the Background extract menu and the background will be extracted later and displayed in the open second window.
3. When the background is extracted, click on the Test Tracking menu to test and track the vehicle.
4. Click on the trajectory drawing menu to map the trajectory of the vehicle.
Note: Since a video decoder is required to open an AVI video file using OpenCV, install a DivX-type video decoder on the computer before the program runs, otherwise an error will occur that can not open the file. The program uses OpenCV2 .1, which requires five files to be copied to *, cv210. DLL, cvaux 210. DLL, cvcore 210. DLL, highgui 210. DLL, ML 210. DLL. Exe under executable.)
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Size: 2857984 |
Author: woniu |
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Description: BMS saliency model的代码，The code has been tested on Windows system, using Matlab 2012 and OpenCV 2.40+.(The code has been tested on Windows system, using Matlab 2012 and OpenCV 2.40+.
To compile the code (only for Windows):
1. Put the extracted files in a**<root_dir>**.
2. Install OpenCV 2.40+.
3. Go to**<root_dir>/mex * and specify the relevant OpenCV paths at the
begining of the**compile.m**.
4. Run**compile.m** in Matlab.
5. Go to**<root_dir>** and run**demo.m** in Matlab.)
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Size: 844800 |
Author: 车朝晖 |
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Description: 基于树莓派B+版本的车牌识别设计，辨识部分以树莓派3B+/3B为核心处理器，基于Linux平台，通过python3.5和OpenCV来对含有车牌信息的图片，进行高斯去噪、灰度化、边缘检测、二值化、闭操作、字符分割、字符识别匹配等一系列图像处理操作最终实现车牌识别这个系统。(Based on the design of license plate recognition of raspberry pie B+version, the recognition part takes raspberry pie 3B+/3B as the core processor, and based on Linux platform, uses Python 3.5 and OpenCV to process the image containing license plate information, and carries out a series of image processing operations such as Gaussian denoising, graying, edge detection, binarization, closed operation, character segmentation, character recognition matching, etc. Finally, the system of license plate recognition is realized)
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Size: 30204928 |
Author: 山=石头 |
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Description: 基于python下的车牌识别S1IG135.【已完成】基于Python3.7+OpenCV的车牌识别系统(License plate recognition based on Python s1ig135 [completed] license plate recognition system based on Python 3.7 + opencv)
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Size: 8990720 |
Author: zhy0307 |
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