Image : Image of drawing converted to the Pokemon character, Pikachu using Pix2Pix trained on Pikachu images.
Description : Image-to-image translation with conditional adversarial nets, or pix2pix, is a machine learning technique developed by Isola et al that learns how to map input images to output images.
The pix2pix model works by training on pairs of images such as building facade labels to building facades, and then attempts to generate the corresponding output image from any input image you give it.
Quickstart :
// Create a pix2pix model using a pre trained network
const pix2pix = ml5.pix2pix('models/customModel.pict', modelLoaded);
// When the model is loaded
function modelLoaded() {
console.log('Model Loaded!');
}
// Transfer using a canvas
pix2pix.transfer(canvas, (err, result) => {
console.log(result);
});
Usage :
Initialize :
const styleTransfer = ml5.pix2pix(model, ?callback);
Parameters :
* model : REQUIRED. The path for a valid model.
* callback : OPTIONAL. A function to run once the model has been loaded. If no callback is provided, it will return a promise that will be resolved once the model has loaded.
