abapteachablemachine | basic flash card game developed in ABAP Javascript

 by   albanleong HTML Version: Current License: MIT

kandi X-RAY | abapteachablemachine Summary

kandi X-RAY | abapteachablemachine Summary

abapteachablemachine is a HTML library. abapteachablemachine has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Bringing together a 15+ year old technology platform with today's latest ML engine. A simple and basic flash card game developed in ABAP and Javascript powered by SAP NetWeaver and Teachable Machine by Google. Here's the link to a YouTube video describing the game and steps to set it up - YouTube.
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              abapteachablemachine has a low active ecosystem.
              It has 3 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of abapteachablemachine is current.

            kandi-Quality Quality

              abapteachablemachine has no bugs reported.

            kandi-Security Security

              abapteachablemachine has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

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

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              abapteachablemachine releases are not available. You will need to build from source code and install.
              Installation instructions are available. Examples and code snippets are not available.

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            abapteachablemachine Key Features

            No Key Features are available at this moment for abapteachablemachine.

            abapteachablemachine Examples and Code Snippets

            No Code Snippets are available at this moment for abapteachablemachine.

            Community Discussions

            No Community Discussions are available at this moment for abapteachablemachine.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install abapteachablemachine

            Train and test your own ML audio model on Teachable Machine - It's really FUN!
            Export the model : Either download the model (ZIP file) or get the shareable link on Teachable Machine.
            If you've downloaded the model locally, unzip your model and upload 'metadata.json', 'model.json' and 'weights.bin' to ABAP server. I have created a 'models' folder under the BSP application ZZATM.
            Run transaction ZZATMSETUP to create a new player, game and questions.
            Player name - Up to 40 characters is supported but avoid using any special characters such as &,%,*,$ etc...
            Profile picture - URL to a small avatar picture. I've included four sample images in the demo_assets folder.
            Debug - If this option is checked, during gameplay, the class labels and scores will be displayed below the screen.
            Sound settings - configure different background music during gameplay and sound effects for when getting a correct answer and when the game ends.
            Game name - Up to 40 characters is supported but avoid using any special characters such as &,%,*,$ etc...
            Game type - Only one option is available now but this gives the flexibility to create more games and route them to different pages.
            Game model - The full and complete URL (https) to the ML model that contains model.json, metadata.json and weights.bin
            Match probability - The minimum score match to consider that it's a correct answer. When the ML model is 100% sure, the score is 1.00. Recommended config could be something like 0.80 (easy difficulty - not really accurate), 0.90 (medium difficulty) or 1.00 (hard difficulty - highly accurate match). You'll just need to tweak this and it also depends on your ML model as well.
            Time to answer - The time in seconds to display the flash card image and listen for an answer. Rcommended config can be something like 10 seconds (easy difficulty) - 5 seconds (medium difficulty) or 3 seconds (hard difficulty).
            Array index - this is a little tricky - you need to match the wordLabels array in the metadata.json file of your model. Typically, "Background noise" is the first entry so you can ignore array[0], and you just need to note what the other class labels are and their array index.
            Image URL - The flash card image to display when showing this question and remember to match the array index correctly. See array index 4,5,6 and look at the matching answer - 1, 3,2 - so, don't always assume that it is in order.

            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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            CLONE
          • HTTPS

            https://github.com/albanleong/abapteachablemachine.git

          • CLI

            gh repo clone albanleong/abapteachablemachine

          • sshUrl

            git@github.com:albanleong/abapteachablemachine.git

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