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https://github.com/danielathome19/classification-model-builder

Assists in the creation of convolutional neural network models for image classification. Models are generated with the Keras library, wrapped from Python in C# to allow use between languages.
https://github.com/danielathome19/classification-model-builder

classification classification-model cnn cnn-keras convolutional-neural-network convolutional-neural-networks csharp interop interoperability keras machine-learning machine-learning-model machine-learning-model-builder ml model-builder neural-network nn python tensorflow trainer

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Assists in the creation of convolutional neural network models for image classification. Models are generated with the Keras library, wrapped from Python in C# to allow use between languages.

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# About
This program assists in the creation of convolutional neural network models for image classification. Models are generated with the Keras library, wrapped from Python in C# to allow use between languages.

# Usage
Load a set of images into the program to be used in classification training. Once the model is built and training is complete, the weights can be saved as a Keras weights file (h5) and be used in either Python or C# (Keras.NET) applications.

You'll need the following NuGet packages installed along with .NET Framework 5.0:
* Keras.NET
* TensorFlow.NET
* Newtonsoft.Json
* Numpy.Bare
* NumSharp.Bitmap
* Python.Included (3.7.3.13)
* SharpLearning.Common.Interfaces
* SharpLearning.Containers
* SharpLearning.CrossValidation
* SharpLearning.Metrics

[Here's a guide on how to install NuGet packages in Visual Studio](https://docs.microsoft.com/en-us/nuget/quickstart/install-and-use-a-package-in-visual-studio)

Here's what the program looks like:
![Demo screenshot](https://github.com/danielathome19/Classification-Model-Builder/blob/master/ClassificationModelBuilder/Demo.jpg?raw=true)

# Bugs/Features
Bugs are tracked using the GitHub Issue Tracker.

Please use the issue tracker for the following purpose:
* To raise a bug request; do include specific details and label it appropriately.
* To suggest any improvements in existing features.
* To suggest new features or structures or applications.