Image-OutPainting

Why we included this project

Image outpainting is the trickier cousin of inpainting: instead of filling a hole, you extend the canvas past the original edges. This Keras reimplementation of Stanford's 'Painting Outside the Box' paper turns that idea into a concrete starting point. The model is a GAN that invents plausible scenery left and right of a 256x256 crop, with pragmatic tweaks like an identity loss to keep generated content consistent with the source and extra convolution layers to handle the fixed resolution. The repo includes a script to turn the provided beach dataset into NumPy batches, and a pretrained checkpoint lets you skip training and jump straight to inference. For researchers or developers wanting a compact, readable single-task model to dissect, this is easier to work through than a big production framework, though you'll likely need to adapt it for polished, general-purpose use.