Today, DALL-E is introducing Outpainting -- a new feature that helps users extend their creativity by continuing an image beyond its original borders. With Outpainting, users can generate large-scale images in any aspect ratio while maintaining the context of the original image. This capability is made possible by DALL-E's Edit feature, which enables changes within a generated or uploaded image. So whether you want to add visual elements in the same style or take a story in new directions, DALL-E makes it easy! Outpainting is a powerful tool that can be used for a variety of purposes.

It is recommended to run the notebook on a local server for better interactive control. This project mainly works as a proof of concept. In that case, the UI design is relatively weak, and the quality of results is not guaranteed. You may need to do prompt engineering or change the size of the selection box to get better outpainting results. Pull requests are welcome for better UI control, ideas to achieve better results, or any other improvements.

OpenAI has added a new "outpainting" function to its text-to-image AI model DALL-E that lets the system generate new visuals that expand the borders of any given picture. In the example above, you can see how DALL-E, with the help of human prompting, "imagines" what's outside the frame of Johannes Vermeer's portrait "Girl with a Pearl Earring." Note, how, even from the limited information provided by the portrait, the system is able to match Vermeer's style, mimicking the shadows and highlights of the original. In the timelapse below, you can also see how the artist responsible, August Kamp, had to expand the image in small sections at a time, often redoing DALL-E's generations in order to get the outcome she wanted. Not seen in this video but definitely worth highlighting, is the fact that the system is not generating these extensions just by itself.

OpenAI has added a new "outpointing" function to its text-to-image AI model DALL-E that lets the system generate new visuals that expand the borders of any given picture. In the example above, you can see how DALL-E, with the help of human prompting, "imagines" what's outside the frame of Johannes Vermeer's portrait "Girl with a Pearl Earring." Note, how, even from the limited information provided by the portrait, the system is able to match Vermeer's style, mimicking the shadows and highlights of the original. In the timelapse below, you can also see how the artist responsible, August Kamp, had to expand the image in small sections at a time, often redoing DALL-E's generations in order to get the outcome she wanted. Not seen in this video but definitely worth highlighting, is the fact that the system is not generating these extensions just by itself.

An AI artist can now provide a glimpse of what the background settings of famous paintings and photos may have looked like. OpenAI, a San Francisco-based company, has created a new tool called'Outpainting' for its text-to-image AI system, DALL-E. Outpainting allows the system to imagine what's outside the frame of famous paintings such as Girl with The Pearl Earring, Mona Lisa and Dogs Playing Poker. As users have shown, it can do this with any kind of image, such as the man on the Quaker Oats logo and the cover of the Beatles album'Abbey Road'. DALL-E relies on artificial neural networks (ANNs), which simulate the way the brain works in order to learn and create an image from text.

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