Can stable diffusion upscale images?

Stable Diffusion is a powerful text-to-image diffusion model that is capable of generating high-quality images from text prompts. However, one limitation of Stable Diffusion is its inability to upscale images. While it can generate new image content based on a text prompt and blend it with existing image context, it cannot increase the size or resolution of an image.

In fact, Stable Diffusion is generally not recommended for upscaling images unless they are relatively small, with a maximum size of around 1000x1000 pixels. For larger images, it is generally better to use a dedicated upscaling tool such as ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks).

ESRGAN is a deep learning-based image upscaling method that uses a generative adversarial network (GAN) to increase the size and resolution of an image while preserving its details and textures. ESRGAN works by training a neural network on a large dataset of low-resolution images and their corresponding high-resolution versions. Once trained, the network can take a low-resolution image as input and generate a high-resolution version of the same image.

One advantage of using ESRGAN for upscaling images is that it is purpose-built for this task and has been shown to produce high-quality results. In contrast, Stable Diffusion is primarily designed for text-to-image generation and does not have the same level of expertise in upscaling.

Another advantage of using ESRGAN is that it can be fine-tuned on specific types of images, such as photographs or paintings, to produce even better results. This can be particularly useful for professional image editing tasks where the quality of the final output is critical.

In conclusion, while Stable Diffusion is a powerful text-to-image diffusion model that can generate high-quality images based on text prompts, it is not well-suited for upscaling images. For upscaling tasks, it is generally better to use a dedicated tool such as ESRGAN, which is purpose-built for this task and has been shown to produce high-quality results.