Files Model weights - vgg16_weights.npz TensorFlow model - vgg16.py Class names - imagenet_classes.py Example input - laska.png To test run it, download all files to the same folder and run python vgg16.py Introduction VGG is a convolutional neural network model proposed by K. Simonyan and A. Zisserman from the University of Oxford in the paper “Very Deep Convolutional Networks for Large-Scale Image Recognition” . The model achieves 92.
Introduction The problem of classification consists in assigning an observation to the category it belongs. That means, for instance, taking a picture of a handwritten digit and correctly classifying which digit (0-9) it is, matching pictures of faces to whom they belong or classifying the sentiment in a text. In general, when dealing with classification we use supervised learning (when we have an annotated training set from which we can learn our model - as we did up until this point).