jsfeat | JavaScript Computer Vision library | Computer Vision library

 by   inspirit JavaScript Version: 0.0.8 License: MIT

kandi X-RAY | jsfeat Summary

kandi X-RAY | jsfeat Summary

jsfeat is a JavaScript library typically used in Artificial Intelligence, Computer Vision, OpenCV applications. jsfeat has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

JavaScript Computer Vision library.
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            kandi-support Support

              jsfeat has a medium active ecosystem.
              It has 2711 star(s) with 386 fork(s). There are 141 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 42 open issues and 38 have been closed. On average issues are closed in 135 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of jsfeat is 0.0.8

            kandi-Quality Quality

              jsfeat has 0 bugs and 0 code smells.

            kandi-Security Security

              jsfeat has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              jsfeat code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              jsfeat is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              jsfeat releases are available to install and integrate.
              jsfeat saves you 12 person hours of effort in developing the same functionality from scratch.
              It has 35 lines of code, 0 functions and 19 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed jsfeat and discovered the below as its top functions. This is intended to give you an instant insight into jsfeat implemented functionality, and help decide if they suit your requirements.
            • data object constructor
            • Constructs a new matrix
            • Creates a new keypoint object .
            • Creates a new Racacamolocation object
            • Creates a new node of the pool .
            • Constructs a THREE . OrthographicJSON
            • table structure
            • Constructs a layer .
            • Equivalent to affine2
            • Pads .
            Get all kandi verified functions for this library.

            jsfeat Key Features

            No Key Features are available at this moment for jsfeat.

            jsfeat Examples and Code Snippets

            No Code Snippets are available at this moment for jsfeat.

            Community Discussions

            QUESTION

            ransac with homography vs 8/5 point algorithms
            Asked 2017-Nov-29 at 21:20

            Im beginning to learn computer vision and I'm confused on the difference between the two.

            I know that the 8 point algorithm is used to compute the fundamental matrix and the 5 point algorithm is used to compute the essential matrix. Both of which can be used to determine the relative camera pose.

            I also found that the relative camera pose can be determined using ransac with homography https://inspirit.github.io/jsfeat/#multiview in the ransac method

            Is there a difference between using ransac with homography as opposed to using the algorithms?

            ...

            ANSWER

            Answered 2017-Nov-29 at 21:20

            First of all, note that you still need RANSAC with the 8-point or 5-point algorithms, since in practice outliers are to be expected in the matching process.

            I think the main downside of pose from homography is that the point matches you use need to be coplanar. Additionaly, if I'm not mistaken, in a scene with more than one plane, you might get different homographies depending on which planes you select in the scene. That is why applying a homography to correct perspective adds distortion to some other parts of the image (see the example in this video). So in complex scenes (e.g. urban environements) where matching is more difficult, I'd use one of the 8-point or the 5-point algorithms.

            Note that you can also recover the relative pose directly (up to scale, obviously), and compute the essential from that (see this paper). It's easier than computing the fundamental/essential and then extracting relative pose.

            Source https://stackoverflow.com/questions/47557409

            QUESTION

            Transform a 3X3 transform matrix to 4X4 matrix for css transform matrix3d
            Asked 2017-Sep-05 at 11:45

            I have a 3X3 transform matrix that's the output of a homography transform.

            I want to rotate and stretch a div according to this matrix but it looks like css transform either receives a 4X4 matrix or a 2X3 matrix.

            I tried to convert the 3X3 matrix by adding zeros and a one like here but it looks completley wrong (it's either making the div rotated by 90 degrees or if I do a transpose, too small).

            How can I transform that 3X3 matrix such that css' transform will work correctly?

            ...

            ANSWER

            Answered 2017-Sep-05 at 11:45

            Here some thougths that will propably help you:

            There are a few possibilities concerning the matrix you recive:

            The matrix is a 2D transformation matrix: In this case the matrix extension you do wil fail, because the matrix layout will look like this:

            Source https://stackoverflow.com/questions/46038052

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

            Vulnerabilities

            No vulnerabilities reported

            Install jsfeat

            You can download it from GitHub.

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            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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