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