image-analogies

GitHub describes it as Generate image analogies using neural matching and blending.. The repository metadata lists Python as its primary language. The metadata lists the MIT license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as Generate image analogies using neural matching and blending.. The repository metadata lists Python as its primary language. The metadata lists the MIT license. The README describes the project this way: This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch matching and blending is inspired by the method described in "Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis". Effects similar to that paper can be achieved by turning off the analogy loss (or leave it on!) --analogy-w=0 and turning on the B/B' content weighting via the --b-content-w parameter. Also, instead of using brute-force patch matching we use the PatchMatch algorithm to approximate the best patch matches. Brute-force matching can be re-enabled by setting --model=brute

The README section "README details" states: The example arch images are from the "Image Analogies" website. They have some other good examples from their own implementation which are worth a look. Their paper discusses the various applications of image analogies so you might want to take a look for inspiration.

The README section "README details" states: Installation ------------ This requires either TensorFlow or Theano. If you don't have a GPU you'll want to use TensorFlow. GPU users may find to Theano to be faster at the expense of longer startup times. Here's the Theano GPU guide.

The README section "README details" states: Here's how to configure the backend with Keras and set your default device (e.g. cpu, gpu0).

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README