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Asked: June 20, 20232023-06-20T12:48:23+05:30 2023-06-20T12:48:23+05:30In: Android Development

DL deployment android app

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I have a DL model related to disease prediction which uses a picture (numpy array) input and then predicts its severity I have successfully made an app for it but still have no idea how to use Heruko(or any other PaaS cloud platform) to deploy it, can anyone help me with this? My tech stack is kotlin ,tflite, flask api ,keras

androiddeep learningherokujavakeraskotlintflite
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  1. Mohammed aleem hasan
    2023-06-23T16:35:43+05:30Added an answer on June 23, 2023 at 4:35 pm

     

    To deploy your disease prediction app on Heroku (or any other platform), you can follow these general steps:

     

    Prepare your application: Ensure that your application is properly structured and includes all the necessary files, dependencies, and configurations. Make sure your model is trained and ready to be used for predictions.

     

    Create a Heroku account: If you don’t have one already, sign up for a Heroku account at https://www.heroku.com/.

     

    Install the Heroku CLI: Download and install the Heroku Command Line Interface (CLI) appropriate for your operating system. The CLI allows you to interact with Heroku from your terminal.

     

    Set up your Heroku app: Open your terminal or command prompt and log in to Heroku using the following command:

     

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    heroku login

    Enter your Heroku account credentials to log in.

     

    Create a new Heroku app: In the terminal, navigate to your project directory and use the following command to create a new Heroku app:

     

    lua

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    heroku create <app-name>

    Replace <app-name> with your desired name or leave it blank to let Heroku generate a random name for you.

     

    Specify required dependencies: Create a requirements.txt file in your project directory that lists all the dependencies your app requires. Include any libraries, frameworks, or tools that are necessary for your application to run. Make sure to include any specific versions if required.

     

    Specify your runtime environment: Create a runtime.txt file in your project directory to specify the Python version to be used by Heroku. For example, if your app requires Python 3.7, the content of runtime.txt should be:

     

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    python-3.7.12

    Set up a web server: You’ll need a web server to handle incoming requests to your application. One popular choice is Gunicorn. Create a Procfile in your project directory and specify the command to run your application. For example, if your main file is named app.py and the entry point for your application is a Flask app, your Procfile should contain:

     

    makefile

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    web: gunicorn app:app

    Initialize a Git repository: Use the following commands to initialize a Git repository, add your files, and commit them:

     

    csharp

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    git init

    git add .

    git commit -m “Initial commit”

    Deploy your app to Heroku: Push your code to Heroku using Git with the following command:

     

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    git push heroku main

    This will initiate the deployment process. Heroku will build your app, install the required dependencies, and launch it.

     

    Scale your app (optional): By default, your app is deployed on a single web dyno, which may not be sufficient for production. You can scale your app to have multiple dynos to handle increased traffic. Use the following command to scale your app:

     

    php

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    heroku ps:scale web=<number-of-dynos>

    Replace <number-of-dynos> with the desired number of dynos. For example, to have two dynos, use heroku ps:scale web=2.

     

    Visit your app: Once the deployment process is complete, Heroku will provide you with the URL for your app. You can open it in your web browser to access your application.

     

    That’s a general overview of how to deploy your app on Heroku. You may need to adjust the instructions based on the specifics of your application and the frameworks/libraries you’re using. Be sure to consult the Heroku documentatissues.a more detailed information and troubleshooting specific issues.

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