Instructpix2Pix

What is Instructpix2Pix?

Who created Instructpix2Pix?

The creator of InstructPix2Pix is Tim Brooks, in collaboration with Aleksander Holynski and Alexei A. Efros. Tim Brooks is funded by an NSF Graduate Research Fellowship, with additional funding from SAP and a gift from Google. InstructPix2Pix is a model developed by these creators for editing images based on written instructions, demonstrating rapid and effective editing results for various input images and textual instructions.

What is Instructpix2Pix used for?

• Editing images from human instructions
• Generating training data for image editing
• Quick image editing without fine-tuning or inversion
• Performing edits in a matter of seconds
• Transforming images based on written instructions
• Producing diverse image edits for the same input
• Compounded edits with recurrent application of different instructions
• Reflecting biases from data and models it is based on
• Isolating specified objects in images
• Editing real images and user-written instructions
• Transforming a single image in various ways
• Editing iconic artworks into different mediums
• Changing time of day in cityscape photographs
• Performing edits rapidly on images in seconds
• Generating multiple possible image edits for the same input
• Compounded edits by applying the model recurrently with different instructions
• Reflecting biases from the data and models it is based upon
• Failure cases such as inability to perform viewpoint changes
• Undesired excessive changes to images
• Difficulty in isolating specified objects
• Editing images based on human instructions
• Transforming images into various artistic mediums
• Editing photographs to show different times of day
• Creating various edits for the same input image and instruction by varying latent noise
• Performing compounded edits by applying the model recurrently with different instructions
• Failure cases where the model struggles with viewpoint changes, excessive changes, isolating objects, and reorganizing objects
• Transforming iconic images like the Beatles Abbey Road album cover
• Artistic transformations of famous artworks like Leonardo da Vinci's Mona Lisa and Van Gogh's Self-Portrait
• Changing the time of day in landscape photos
• Editing famous paintings like Vermeer's Girl with a Pearl Earring and Van Gogh's Self-Portrait with a Straw Hat
• Moving subjects to new settings
• Producing multiple edits of the same image based on varying latent noise
• Reflecting biases from the data and models like correlations between profession and gender
• Identifying failure cases such as difficulty in performing viewpoint changes or isolating specified objects
• Editing images based on written instructions
• Generating a large dataset of image editing examples
• Performing edits in the forward pass without fine-tuning or inversion
• Quickly editing images in seconds
• Editing a wide range of input photos and textual instructions
• Editing cityscape photos to show different times of day
• Producing many possible image edits by varying latent noise
• Realistic editing of images up to 768-width resolution
• Modifying photos rapidly in a matter of seconds
• Producing multiple possible image edits for the same input image and instruction by varying latent noise
• Failed cases such as inability to perform viewpoint changes or isolate specific objects

Who is Instructpix2Pix for?

• Photo Editors
• Graphic designers
• Digital artists
• Artists
• Content creators
• Photographers
• Image Editors

How to use Instructpix2Pix?

To use InstructPix2Pix, follow these steps:

1. Input Image and Instruction: Provide an input image and a written instruction that specifies the desired edits.

2. Model Execution: The model, InstructPix2Pix, will utilize a conditional diffusion approach to edit the image based on the given instruction.

3. Training Data: The model is trained on a dataset created by combining a language model (GPT-3) with a text-to-image model (Stable Diffusion), resulting in a large set of image editing examples.

4. Generalization: At inference time, InstructPix2Pix generalizes to real images and user-written instructions, producing edits rapidly within seconds without the need for fine-tuning or inversion.

5. Editing Results: The model showcases effective editing outcomes across various input images and textual instructions, demonstrating its flexibility and capability in image editing tasks.

Overall, InstructPix2Pix offers a user-friendly approach to editing images based on specific written instructions, providing a quick and efficient way to transform images according to desired criteria.