Image-Classification

Application of Convolutional Neural Networks (ConvNet) for image classification allowing the detection of inappropriate images. This program classifies images using a Convolutional Neural Network (CNN). The images are preprocessed and normalized then used to train a CNN consisting of convolutional, max pooling, dropout, fully connected, and output layers.

In this project there is no training and the parameters are loaded from an existing model

Install

• Python 3.7
  • I recommend installing Anaconda as it is alreay set up for machine learning
  • If unfamiliar with the command line there are graphical installs for macOS, Windows, and Linux
• TensorFlow

How to use it

• If not using Anaconda
  • Open Command line: Start menu -> Run and type cmd
• If using Anaconda
  • Open Command line: Start menu -> Anaconda Prompt
• Go to the folder where the script is downloaded using 'cd'
• Type: >python ./CNN.py url

Example

Let's try this image

URL is 'http://img.over-blog-kiwi.com/1/10/82/36/20180701/ob_b0af62_galerie-images-droles-insolites-et-s.jpg'

Command Line

>python CNN.py http://img.over-blog-kiwi.com/1/10/82/36/20180701/ob_b0af62_galerie-images-droles-insolites-et-s.jpg

Output