A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.

Last update: Dec 12, 2022

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Overview

Image Classification in Python

Implementing image classification in Flask using Keras.

The VGG16 is a convolution neural network model architecture that is the best classifier for images till today. This project implements the classifier through Keras. This appplication was written in Python. It also utilizes the Flask Microframework, as the server to render a template, and pass the submitted file to the prediction model. It also uses Keras modules to perform image classification.

Requirements

Python 3.5+
Pip (For installing modules)
Flask Download
Tensorflow
Keras Modules

Installation

(Plain Set Up)

Go ahead an clone this specific repository. You could do this through the command below:

> git clone https://github.com/grayoj/Python-Image-Classification.git

Then navigate to the directory. If you use VSCode, you could avoid interacting with the terminal.

Run the following commands in the directory:

> pythom -m flask run

(Full Set Up)

Go ahead an clone this specific repository. You could do this through the command below:

> git clone https://github.com/grayoj/Python-Image-Classification.git

To install Python, download here. If you already have Python 3.5 installed, you may proceed to the next steps below:

You will notice this line of code in the app.py file:

To ensure the modules would be imported on your system, into the project, run the following command:

> pip install flask

That would install flask on your local machine. Next step is to install the Keras Modules, and packages required. Run the following command:

> pip install keras

If you use Pylance, it should validate the imports above in the app.py. i.e show no errors, of modules missing. Modules being installed:

You would have to install Tensorflow as well.

> pip install tensorflow

You are set. Now let's dial in to a localhost port.

> python -m flask run

Viola, the application should load sucessfully. If there are any errors, ensure you installed the modules properly.

Http://127.0.0.1:5000

Don't worry if you notice a sudden download process. Tensorflow would begin to download dependencies for the VGG16 Covolutional Neural network model.

Prediction in action

Now, the fun part. This should have loaded open:

Let's see whether our model can predict what this animal is: The picture used is in the repository. You could use other images, and have fun.

Now let's input it

Click on predict

Our model predicted a tiger cat! Epic.

More Information

Reach out to me if you have questions or suggestions. Would love to connect.

Twitter: @geraldabuchi

Python-Image-Classification

Flask, Keras, Tensorflow, VGG16

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Comments

Add CodeQL workflow for GitHub code scanning
Hi grayoj/image-classifier!

This is a one-off automatically generated pull request from LGTM.com :robot:. You might have heard that we’ve integrated LGTM’s underlying CodeQL analysis engine natively into GitHub. The result is GitHub code scanning!

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FAQ

Click here to expand the FAQ section

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This PR is filed by the official LGTM.com GitHub App, in line with the deprecation timeline that was announced on the official GitHub Blog. The proposed GitHub Action workflow uses the official open source GitHub CodeQL Action. If you have any other questions or concerns, please join the discussion here in the official GitHub community!

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opened by lgtm-com[bot] 0

Releases(v1.0.0)

v1.0.0(Jul 25, 2022)

First release of the image-classifier.
Source code(tar.gz)
Source code(zip)

Owner

Gerald Maduabuchi

Computer Programmer. ML Enthusiast C++, Python, PHP and JavaScript

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