mlnet | Deep Multi-Level Network | Machine Learning library

 by   marcellacornia Python Version: Current License: MIT

X-RayKey FeaturesCode SnippetsCommunity Discussions(4)VulnerabilitiesInstallSupport

kandi X-RAY | mlnet Summary

kandi X-RAY | mlnet Summary

mlnet is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. mlnet has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However mlnet build file is not available. You can download it from GitHub.

A Deep Multi-Level Network for Saliency Prediction. ICPR 2016
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            kandi-support Support

              mlnet has a low active ecosystem.
              It has 75 star(s) with 35 fork(s). There are 7 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 6 open issues and 20 have been closed. On average issues are closed in 73 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of mlnet is current.

            kandi-Quality Quality

              mlnet has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              mlnet 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

              mlnet releases are not available. You will need to build from source code and install.
              mlnet 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.
              mlnet saves you 95 person hours of effort in developing the same functionality from scratch.
              It has 242 lines of code, 14 functions and 5 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed mlnet and discovered the below as its top functions. This is intended to give you an instant insight into mlnet implemented functionality, and help decide if they suit your requirements.
            • Generator for training images
            • Add padding to an image
            • Preprocess images
            • Preprocess map files
            • Generate a CNN model
            • Get weights from vGG16 layer
            • Generate test images
            Get all kandi verified functions for this library.

            mlnet Key Features

            No Key Features are available at this moment for mlnet.

            mlnet Examples and Code Snippets

            No Code Snippets are available at this moment for mlnet.

            Community Discussions

            Trending Discussions on mlnet

            Error In Blazor When Getting Stream of ML NET Model zip file
            Azure (C#) System.IO.FileNotFoundException: Could not find file
            AUC is not definied[sic] when there is no positive class in the data
            Why does this ML.NET code fail to predict the correct output?

            QUESTION

            Error In Blazor When Getting Stream of ML NET Model zip file
            Asked 2020-Sep-11 at 13:14

            I have a problem with Blazor. I tried to do what's said in the documentation about loading existing model from remote source. (https://docs.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/save-load-machine-learning-models-ml-net)

            This is what I came up with:

            ...

            ANSWER

            Answered 2020-Sep-11 at 13:14

            If this is a Blazor WASM application then unfortunately ML NET is incompatible. ML NET requires a x86 which doesn't exist in WebAssembly. Therefore you must process your ML Model on the server and send the results to the client over HTTP.

            Source https://stackoverflow.com/questions/63847453

            QUESTION

            Azure (C#) System.IO.FileNotFoundException: Could not find file
            Asked 2020-Jul-18 at 12:04

            I've created a ML model with Visual Studio. I uploaded the web app to Azure with Visual Studio too. However, when I fill the fields for my ML model and click "run" on the website, I get this error which I copied directly from Azure App Service Editor.

            I only get this error while trying to run the ML model on Azure website, if I run the web app on my computer I have no errors at all.

            Thank you :)

            ...

            ANSWER

            Answered 2020-Jul-18 at 04:18

            you are trying to load file MLModel.zip from C:\Users\X\X\X\fileML.Model. Now that's your local computer path. That path not exists into Azure Web App.

            There are 2 ways you can do if you really want to store in local directory:

            1. HOMe environment variable in your Azure Web App that resolves to the equivalent of inetpub for your site. Your app data folder is located at %HOME%\site\wwwroot\AppData.

              TEMP environment both on Azure Web Apps and on your local machine.

            Source https://stackoverflow.com/questions/62963737

            QUESTION

            AUC is not definied[sic] when there is no positive class in the data
            Asked 2019-Oct-29 at 14:19

            I am facing the following issue when attempting to train a model:

            ...

            ANSWER

            Answered 2019-Jul-17 at 20:50

            How are you loading data, this could look like your label column is empty so maybe data is not loaded correctly. If using built in mlContext.Data.LoadFromTextFile remember that it defaults to TSV so you will have to specify seperator yourself in its configuration like this:

            Source https://stackoverflow.com/questions/56913804

            QUESTION

            Why does this ML.NET code fail to predict the correct output?
            Asked 2018-Dec-01 at 17:22

            I'm an ML.NET newbie and want to learn more about ML.NET by solving the XOR problem. This is what I've come up with so far, but the output always appears to be the same (zero), regardless of input.

            No doubt I've made a rookie mistake, but what?

            ...

            ANSWER

            Answered 2018-Dec-01 at 17:22

            Your Prediction object is retrieving the original Label column, instead of the output of the regressor.

            Modify the code to be:

            Source https://stackoverflow.com/questions/53472759

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

            Vulnerabilities

            No vulnerabilities reported

            Install mlnet

            You can download it from GitHub.
            You can use mlnet like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For more datails about our research please visit our page. If you have any general doubt about our work, please use the public issues section on this github repo. Alternatively, drop us an e-mail at mailto:marcella.cornia@unimore.it or mailto:lorenzo.baraldi@unimore.it.
            Find more information at:

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