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AndroidFastImageProcessing | image processing on android devices | Computer Vision library

 by   chrisbatt Java Version: Current License: MIT

 by   chrisbatt Java Version: Current License: MIT

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kandi X-RAY | AndroidFastImageProcessing Summary

AndroidFastImageProcessing is a Java library typically used in Artificial Intelligence, Computer Vision applications. AndroidFastImageProcessing has no vulnerabilities, it has a Permissive License and it has low support. However AndroidFastImageProcessing has 22254 bugs and it build file is not available. You can download it from GitHub.
The whole library is written targeted to android 2.2 (API 8) and no 3rd party libraries with the exception the video input and output and Camera input. The video and camera input require android 4+ (API 14+) because it uses SurfaceTexture. The video output takes advantage of JavaCV to record the video. From my tests, the video recording is not working on android 4+ devices but is working on android 2.2. Basic setup for a simple filter pipeline. More examples can be found in "/examples".
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • AndroidFastImageProcessing has a low active ecosystem.
  • It has 277 star(s) with 113 fork(s). There are 27 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 22 open issues and 9 have been closed. On average issues are closed in 10 days. There are 3 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of AndroidFastImageProcessing 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

  • AndroidFastImageProcessing has 22254 bugs (0 blocker, 0 critical, 10447 major, 11807 minor) and 32429 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

  • AndroidFastImageProcessing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • AndroidFastImageProcessing code analysis shows 0 unresolved vulnerabilities.
  • There are 20 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

  • AndroidFastImageProcessing is licensed under the MIT License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
This Library - License
Best in #Computer Vision
Average in #Computer Vision
This Library - License
Best in #Computer Vision
Average in #Computer Vision

buildReuse

  • AndroidFastImageProcessing releases are not available. You will need to build from source code and install.
  • AndroidFastImageProcessing has no build file. You will be need to create the build yourself to build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • AndroidFastImageProcessing saves you 66719 person hours of effort in developing the same functionality from scratch.
  • It has 75239 lines of code, 459 functions and 512 files.
  • It has low 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 AndroidFastImageProcessing and discovered the below as its top functions. This is intended to give you an instant insight into AndroidFastImageProcessing implemented functionality, and help decide if they suit your requirements.

  • Initializes the window .
    • Get the second derivative .
      • Load a bitmap from a bitmap
        • Initialize with OpenGL Context
          • Initialize the FBO
            • Get the fragment shader to be used for the current shader .
              • Loads orthographic matrix .
                • Creates the filter body .
                  • Destroy the program .
                    • Called when a new texture is ready .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      AndroidFastImageProcessing Key Features

                      Checkout or download the framework

                      Import the framework into current eclipse workspace

                      Added the framework to project as an android library dependance Right click project → Build Path → Configure Build Path ![Alt text](/doc/setup/step1.png) In the list on the left, select "android" → under library, click "add" → in the popup, select "FastImageProcessing" ![Alt text](/doc/setup/step2.png)

                      default

                      copy iconCopydownload iconDownload
                      public class ImageProcessingActivity extends Activity {
                        private FastImageProcessingView view;
                      	private FastImageProcessingPipeline pipeline;
                      	private ImageResourceInput imageIn;
                      	private GenericFilter generic;
                      	private ScreenEndpoint screen;
                      
                      
                      	@Override
                      	protected void onCreate(Bundle savedInstanceState) {
                      		super.onCreate(savedInstanceState);
                      		view = new FastImageProcessingView(this);
                      		pipeline = new FastImageProcessingPipeline();
                      		view.setPipeline(pipeline);
                      		setContentView(view);
                      		imageIn = new ImageResourceInput(view, this, R.drawable.wakeboard);
                      		generic = new GenericFilter();
                      		screen = new ScreenEndpoint(pipeline);
                      		imageIn.addTarget(generic);
                      		generic.addTarget(screen);
                      		pipeline.addRootRenderer(imageIn);
                      		pipeline.startRendering();
                      	}
                      }

                      Community Discussions

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                      Trending Discussions on Computer Vision

                      QUESTION

                      Image similarity in swift

                      Asked 2022-Mar-25 at 11:42

                      The swift vision similarity feature is able to assign a number to the variance between 2 images. Where 0 variance between the images, means the images are the same. As the number increases this that there is more and more variance between the images.

                      What I am trying to do is turn this into a percentage of similarity. So one image is for example 80% similar to the other image. Any ideas how I could arrange the logic to accomplish this:

                      import UIKit
                      import Vision
                      func featureprintObservationForImage(atURL url: URL) -> VNFeaturePrintObservation? {
                      let requestHandler = VNImageRequestHandler(url: url, options: [:])
                      let request = VNGenerateImageFeaturePrintRequest()
                      do {
                        try requestHandler.perform([request])
                        return request.results?.first as? VNFeaturePrintObservation
                      } catch {
                        print("Vision error: \(error)")
                        return nil
                      }
                        }
                       let apple1 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple1", withExtension: "jpg")!)
                      let apple2 = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"apple2", withExtension: "jpg")!)
                      let pear = featureprintObservationForImage(atURL: Bundle.main.url(forResource:"pear", withExtension: "jpg")!)
                      var distance = Float(0)
                      try apple1!.computeDistance(&distance, to: apple2!)
                      var distance2 = Float(0)
                      try apple1!.computeDistance(&distance2, to: pear!)
                      

                      ANSWER

                      Answered 2022-Mar-25 at 10:26

                      It depends on how you want to scale it. If you just want the percentage you could just use Float.greatestFiniteMagnitude as the maximum value.

                      1-(distance/Float.greatestFiniteMagnitude)*100
                      

                      A better solution would probably be to set a lower ceiling and everything above that ceiling would just be 0% similarity.

                      1-(min(distance, 10)/10)*100
                      

                      Here the artificial ceiling would be 10, but it can be any arbitrary number.

                      Source https://stackoverflow.com/questions/71615277

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

                      Vulnerabilities

                      No vulnerabilities reported

                      Install AndroidFastImageProcessing

                      You can download it from GitHub.
                      You can use AndroidFastImageProcessing 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 AndroidFastImageProcessing 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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