fvisionNetwork14 0.0.5

fvisionNetwork14 is an image classification CNN model that can classify the number of classes.

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:

Dataset directory

1. class A
2. class B
3. class C
4. class D
5. class E
6. class F

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

© 2022 Kalyan Mohanty

This repository is licensed under the MIT license. See LICENSE for details.