InstructIR accepts images and human-written instructions as input, performing integrated image restoration through a single neural model. It has achieved state-of-the-art results across multiple restoration tasks, including image denoising, rain removal, defogging, deblurring, and low-light image enhancement. 🚀 Get started with the demonstration tutorial. Visit our GitHub for more information. Disclaimer: Please note that this is not a product, and you may notice certain limitations. This demonstration requires input of images with certain degradations (blur, noise, rain, low light, fog) and a prompt indicating the operation to be performed. The application may crash if input high-resolution images (2K, 4K) are used due to GPU memory limitations. The model is primarily trained on synthetic data, which may result in suboptimal performance on real-world complex images. However, it performs surprisingly well on real-world foggy and low-light images. You can also try general image enhancement prompts (e.g., 'polish this image', 'enhance color') to see how it improves color clarity.