arcface | ArcSoft face recognition SDK for windows java | Computer Vision library

 by   jastar-wang Java Version: v2.1.0 License: MIT

kandi X-RAY | arcface Summary

kandi X-RAY | arcface Summary

arcface is a Java library typically used in Artificial Intelligence, Computer Vision applications. arcface has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has high support. You can download it from GitHub.

ArcSoft face recognition SDK for windows java. Including SDK v1.1 to v2.0

            kandi-support Support

              arcface has a highly active ecosystem.
              It has 24 star(s) with 13 fork(s). There are 2 watchers for this library.
              It had no major release in the last 12 months.
              arcface has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of arcface is v2.1.0

            kandi-Quality Quality

              arcface has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              arcface 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

              arcface releases are available to install and integrate.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              arcface saves you 343 person hours of effort in developing the same functionality from scratch.
              It has 822 lines of code, 72 functions and 22 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed arcface and discovered the below as its top functions. This is intended to give you an instant insight into arcface implemented functionality, and help decide if they suit your requirements.
            • Load an AsvlScreen
            • Convert RGB RGB color to ITU color
            • Get I420 from BufferedImage
            • Generate a 2 - color RGB color for BRA
            • Gets all faces
            • Parse the data structures
            • Get the face configurations
            • Get the face coordinates
            • Get the pitchs values
            • Uninit ASF
            • Create a deep copy of this FaceFeature
            • Get the roll numbers
            • Get the statuses
            • Dumps this feature
            • Returns the field order
            • Get field order
            • Get gender
            • Gets the field order
            • Get YAWAY value
            • Get face3Dangle
            • Get age info
            • Compare two features
            • Extract face info
            • Gets the genders
            • Gets age
            • Convert an image to a buffered image
            Get all kandi verified functions for this library.

            arcface Key Features

            No Key Features are available at this moment for arcface.

            arcface Examples and Code Snippets

            Javadot img1Lines of Code : 1dot img1License : Permissive (MIT)
            copy iconCopy
            git clone

            Community Discussions


            issue with arcface ( 0 accuracy)
            Asked 2022-Mar-07 at 03:30

            Hello guys I've joined a university-level image recognition competition.

            • In the test, they will give two images (people face) and my model need to detect pair of the image is the same person or not

            • My model is resnet18 with IR block and SE block. and it will use Arcface loss.

            • I can use only the MS1M dataset with a total of 86876 classes

            The problem is that loss is getting better, but accuracy is 0 and not changing.

            Here's part of code I'm working on.




            Answered 2022-Mar-07 at 03:30

            You can try to use a smaller m in ArcFace, even a minus value.



            Tensorflow dataset with multiple inputs and target
            Asked 2021-May-21 at 16:12

            I am trying to implement a model with the ArcFace Layer:

            to this extend I created a like so:



            Answered 2021-May-21 at 15:02

            I think you should do it like this:



            import error of ArcFace using python in jupyternotebbok
            Asked 2020-Dec-15 at 08:41

            When I am importing the package ArcFace.



            Answered 2020-Sep-11 at 08:54

            This is part of project keras-arcface but it is not part of keras so you have to install/copy it separatelly.

            If you put it in your project in subfolder arcface then it should work.



            Why loaded Pytorch model's loss highly increased?
            Asked 2020-Oct-27 at 17:03

            I'm trying to train Arcface with reference to.

            As far as I know, Arcface requires more than 200 training epochs on CASIA-webface with a large batch size.

            Within 100 epochs of training, I stopped the training for a while because I was needed to use GPU for other tasks. And the checkpoints of the model(Resnet) and margin are saved. Before it was stopped, its loss recorded a value between 0.3~1.0, and training accuracy was mount to 80~95%.

            When I resume the Arcface training by loading the checkpoint files using load_sate, it seems normal when the first batch is processed. But suddenly the loss increased sharply and the accuracy became very low.

            Its loss suddenly became increased. How did this happen? I had no other way so anyway continued the training, but I don't think the loss is decreasing well even though it is a trained model over 100 epochs...

            When I searched for similar issues, they told the problem was that the optimizer was not saved (Because the reference github page didn't save the optimizer, so did I. Is it true?

            My losses after loading



            Answered 2020-Oct-27 at 17:03

            if you see this line! you are Decaying the learning rate of each parameter group by gamma. This has altered your learning rate as you had reached 100th epoch. and moreover you had not saved your optimizer state while saving your model.
            This made your code to start with the starting lr i.e 0.1 after resuming your training. And this spiked your loss again.

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


            No vulnerabilities reported

            Install arcface

            You can download it from GitHub.
            You can use arcface 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 arcface 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 For Gradle installation, please refer .


            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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