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MyRealTimeImageProcessing | real time image processing in Android using OpenCV | Computer Vision library

 by   ikkiChung Java Version: Current License: No License

 by   ikkiChung Java Version: Current License: No License

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kandi X-RAY | MyRealTimeImageProcessing Summary

MyRealTimeImageProcessing is a Java library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. MyRealTimeImageProcessing has no bugs, it has no vulnerabilities and it has low support. However MyRealTimeImageProcessing build file is not available. You can download it from GitHub.
Example of how to do real time image processing in Android using OpenCV. This article teaches how to pass camera preview frame to android-opencv on the fly.<br> http://ibuzzlog.blogspot.tw/2012/08/how-to-do-real-time-image-processing-in.html.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • MyRealTimeImageProcessing has a low active ecosystem.
  • It has 79 star(s) with 47 fork(s). There are 7 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 1 open issues and 1 have been closed. On average issues are closed in 28 days. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of MyRealTimeImageProcessing is current.
This Library - Support
Best in #Computer Vision
Average in #Computer Vision
This Library - Support
Best in #Computer Vision
Average in #Computer Vision

quality kandi Quality

  • MyRealTimeImageProcessing has 0 bugs and 0 code smells.
This Library - Quality
Best in #Computer Vision
Average in #Computer Vision
This Library - Quality
Best in #Computer Vision
Average in #Computer Vision

securitySecurity

  • MyRealTimeImageProcessing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • MyRealTimeImageProcessing code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
This Library - Security
Best in #Computer Vision
Average in #Computer Vision
This Library - Security
Best in #Computer Vision
Average in #Computer Vision

license License

  • MyRealTimeImageProcessing does not have a standard license declared.
  • Check the repository for any license declaration and review the terms closely.
  • Without a license, all rights are reserved, and you cannot use the library in your applications.
This Library - License
Best in #Computer Vision
Average in #Computer Vision
This Library - License
Best in #Computer Vision
Average in #Computer Vision

buildReuse

  • MyRealTimeImageProcessing releases are not available. You will need to build from source code and install.
  • MyRealTimeImageProcessing has no build file. You will be need to create the build yourself to build the component from source.
  • MyRealTimeImageProcessing saves you 67 person hours of effort in developing the same functionality from scratch.
  • It has 174 lines of code, 9 functions and 5 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
This Library - Reuse
Best in #Computer Vision
Average in #Computer Vision
This Library - Reuse
Best in #Computer Vision
Average in #Computer Vision
Top functions reviewed by kandi - BETA

kandi has reviewed MyRealTimeImageProcessing and discovered the below as its top functions. This is intended to give you an instant insight into MyRealTimeImageProcessing implemented functionality, and help decide if they suit your requirements.

  • Initializes the camera view .
    • Notify the preview of the surface .
      • Called when camera is changed .
        • Capture image data .
          • Called when a surface is destroyed .
            • Override onPause .

              Get all kandi verified functions for this library.

              Get all kandi verified functions for this library.

              MyRealTimeImageProcessing Key Features

              Example of how to do real time image processing in Android using OpenCV

              MyRealTimeImageProcessing Examples and Code Snippets

              See all related Code Snippets

              Android OpenCV convertTo() from CV_32FC4 to CV_8UC4

              copy iconCopydownload iconDownload
              Mat mFrame(height, width, CV_32FC4, (unsigned char *)pNV21FrameData);
              
              for(int y = 0 ; y < height ; y++){
                  for(int x = 0 ; x < width ; x++){
                      Vec4f BGRA = mFrame.at<Vec4f>(y,x);
                      // BGRA Pixel Manipulations
                      mFrame.at<Vec4f>(y,x) = BGRA;
                  }
              }
              
              Mat mResult;
              mFrame.convertTo(mResult, CV_8UC4, 1.0/255.0);
              

              See all related Code Snippets

              Community Discussions

              Trending Discussions on MyRealTimeImageProcessing
              • Android OpenCV convertTo() from CV_32FC4 to CV_8UC4
              Trending Discussions on MyRealTimeImageProcessing

              QUESTION

              Android OpenCV convertTo() from CV_32FC4 to CV_8UC4

              Asked 2017-Nov-08 at 15:55

              I'm just new to Android & OpenCV and currently I'm using this project for real-time image processing. I am using the native code cpp from the project to implement the algorithm that I need which involves mathematical operations with float numbers applying modifications for the RGB channels for each pixel. Therefore I think it's just appropriate to use CV_32FC4 for the first matrix. Adjustments I did in the cpp:

              Mat mFrame(height, width, CV_32FC4, (unsigned char *)pNV21FrameData);
              Mat mResult(height, width, CV_8UC4, (unsigned char *)poutPixels);
              
              for(int y = 0 ; y < height ; y++){
                  for(int x = 0 ; x < width ; x++){
                      Vec3b BGR = mFrame.at<Vec3b>(Point(x,y));
                      // BGR Pixel Manipulations
                      mFrame.at<Vec3b>(Point(x,y)) =  BGR;
                  }
              }
              
              mFrame.convertTo(mResult, CV_8UC4, 1/255.0);
              

              After implementing the algorithm, I'll need to convert the matrix to BGRA since it is the requirement so I'll used CV_8UC4. But when I run the program there is a problem with the display: link for actual image

              Output Image

              The white objects in the right side seems to be multiple instances of ruined version of what is displayed. There's nothing like that with the original code that is Canny Edge Detection so I suppose it's not a problem with my device. What could possibly be the problem?

              ANSWER

              Answered 2017-Nov-08 at 15:55
              • You're working on a 4 channel float matrix, so you should access it with Vec4f.
              • You don't need to initialize the output matrix from a OpenCV function in general. So just use Mat mResult; and cvtColor will take care of creating it correctly.
              • You don't need to access a pixel with Point, simply pass the rows and cols coordinates.

              So the code becomes:

              Mat mFrame(height, width, CV_32FC4, (unsigned char *)pNV21FrameData);
              
              for(int y = 0 ; y < height ; y++){
                  for(int x = 0 ; x < width ; x++){
                      Vec4f BGRA = mFrame.at<Vec4f>(y,x);
                      // BGRA Pixel Manipulations
                      mFrame.at<Vec4f>(y,x) = BGRA;
                  }
              }
              
              Mat mResult;
              mFrame.convertTo(mResult, CV_8UC4, 1.0/255.0);
              

              Source https://stackoverflow.com/questions/47183534

              Community Discussions, Code Snippets contain sources that include Stack Exchange Network

              Vulnerabilities

              No vulnerabilities reported

              Install MyRealTimeImageProcessing

              You can download it from GitHub.
              You can use MyRealTimeImageProcessing like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the MyRealTimeImageProcessing component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

              Support

              For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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