All architectures are compatible with both TensorFlow and Theano, and upon instantiation the models will be built according to the image dimension ordering set in your Keras configuration file at ~/.keras/keras.json. For instance, if you have set image_dim_ordering=tf, then any model loaded from this repository will get built according to the TensorFlow dimension ordering convention, "Width-Height-Depth". Pre-trained weights can be automatically loaded upon instantiation (weights='imagenet' argument in model constructor for all image models, weights='msd' for the music tagging model). Weights are automatically downloaded if necessary, and cached locally in ~/.keras/models/. This repository contains code for the following Keras models, VGG16, VGG19, ResNet50, Inception v3, and CRNN for music tagging.

Features

  • Classify images
  • Extract features from images
  • Extract features from an arbitrary intermediate layer
  • The Inception v3 weights are trained by ourselves
  • Contains code for several Keras models
  • All code in this repository is under the MIT license

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MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python UML Tool, Python Machine Learning Software, Python Deep Learning Frameworks

Registered

2021-08-12