#High Resolution

LaMa's robust inpainting technology enables high-resolution image processing using Fourier convolutions, excelling in complex scenarios. Originally trained at 256x256, it scales effectively to 2k resolution. The project supports development across various environments and integrates with platforms like Huggingface Spaces, with resources enabling diverse use cases.

This project details a framework for detecting salient objects in high-resolution images, overcoming challenges with pixel-level annotations. Using an inverse saliency pyramid reconstruction network, it integrates image pyramid structures with blending methods to enhance prediction accuracy without high-resolution datasets. It exceeds state-of-the-art results in several benchmarks, improving boundary accuracy and detection metrics. The work includes practical demos and tools for web and command-line use, broadening its application in various real-world contexts.

UltraPixel advances high-resolution image synthesis, facilitating the creation of detailed and high-quality images across multiple resolutions. Recent updates improve compatibility with PyTorch and Torchvision, optimizing generation speed on RTX 4090 GPUs. It offers text-guided and personalized image generation through a user-friendly Gradio interface and employs advanced pre-trained models. Memory-efficient techniques support resolutions up to 4K.