Metadata-Version: 2.1
Name: fvisionNetwork14
Version: 0.0.5
Summary: fvisionNetwork14 is an image classification CNN model that can classify the  number of classes.
Home-page: https://github.com/KalyanMohanty/fvisionNetwork14
Author: Kalyan Mohanty
Author-email: kalyanrisingstar@gmail.com
License: MIT
Description: # fvisionNetwork14
        "fvisionNetwork14" is a CNN model for image classification that can categorise "n" classes. It has been tuned to have less codes than other models with higher code complexity. The model can categorise with improved accuracy with just a few lines of code. The dataset can be immediately fed into the model using an image pre-processing module that has been built into the package. Two graphical modules are given for plotting model accuracy and loss by providing model history as input.
        
        ## Installation
        ```pip install fvisionNetwork14```
        
        ## Description
        version: 0.0.5
        
        modules:
                - image_preprocessing
                - fvNet14
                - plot_accuracy
                - plot_loss
        
         pre-requisites:
                - tensorflow 2
        
        Dependancy modules:
                - numpy
                - matplotlib
        
        ## How to use?
        e.g:
        
        <!-- TABLE OF CONTENTS -->
        <details>
          <summary>Dataset directory</summary>
          <ol>
            <li>
              <a text = "#class A">  class A</a>
            </li>
            <li>
              <a text ="#class B">  class B</a>
            </li>
            <li><a text="#class C">  class C</a></li>
            <li><a text="#class D">  class D</a></li>
            <li><a text="#class E">  class E</a></li>
            <li><a text="#class F">  class F</a></li>
          </ol>
        </details>
        
        
        ### image_preprocessing
            image_pre_processing.image_preprocessing(path, image_height = 50, image_width = 50)
        
        ### fvNet14
            model_test = fvNet14.fvNet14(image_height = 50, image_width = 50, color_channel = 3, output_layer = 10)
            history = model_test.fit(xtrain,ytrain,epochs=50,validation_data=(xtest,ytest))
        
        ## plot_accuracy
            plot_model_acuracy.plot_accuracy(history, height = 10, width = 10)
        
        ## plot_loss
            plot_model_loss.plot_loss(history, height = 10, width = 10)
        ## License
        
        Â© 2022 Kalyan Mohanty
        
        This repository is licensed under the MIT license. See LICENSE for details.
        
Keywords: fvisionNetwork14,fvNet14,image classification,deep neural network,cnn,keras model,cnn
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.8
Description-Content-Type: text/markdown
