Introduction
Generating images from AI models like DALL-E, Midjourney, and Stable Diffusion has become extremely popular. These models can create amazing, photorealistic images from just a text prompt.
However, often we come across an existing image online and wonder – what was the prompt used to create this? Extracting prompts from AI images allows us to understand and replicate how they were made.
In this comprehensive guide, we will cover multiple methods to extract prompts from AI images, along with tips to recreate them.
Methods to Extract Prompts
There are a few key methods one can use to extract prompts from AI images:
- Reading metadata – Some image formats like PNG store prompt text and other info.
- Using CLIP interrogators – These tools analyze images and guess possible prompts.
- Manual reverse engineering – Trying to breakdown visual elements and scenes.
Let’s explore each of these techniques in detail:
Read Metadata from Image Files
If an AI image is saved as a PNG file, it may contain prompt text and other generation parameters embedded in its metadata.
Here are the steps to extract prompts from PNG images:
- Download the PNG image file to your computer.
- Use an application like AUTOMATIC1111 WebUI to view PNG metadata.
- If present, the prompt and settings will be visible – use them to recreate the image!
Alternatively, you can use online tools like PNG Meta Viewer to read PNG metadata without needing to install any software.
Use CLIP Interrogators
CLIP interrogators are AI models that can analyze an image and make an educated guess at what prompt may have been used to create it.
Popular CLIP interrogators include:
To use them:
- Upload the AI image you wish to inspect
- The model will process the image and suggest possible prompt text(s)
- Take the suggested prompt and try generating a similar image!
These tools work quite well, especially for Stable Diffusion images.
Manually Reverse Engineer the Image
If the above methods don’t work, the last resort is to manually reverse engineer the image:
- Carefully study the image and break down key elements
- Identify the subject (person, animal etc), scene, lighting, colors, textures, styles etc.
- Try to match visual styles with existing AI algorithms – photorealism, paintings, anime etc.
- Craft a detailed prompt based on your analysis
- Test and refine the prompt to get closer to the original
This process requires some trial-and-error, but often leads to the intended outcome.
Tips for Recreating AI Images
Once you have extracted a prompt, here are some tips to recreate the original AI image as closely as possible:
- Use the same model – Try generating with the same AI algorithm (DALL-E 2, Stable Diffusion etc)
- Tune parameters – Adjust settings like number of steps, guidance scale etc.
- Modify the prompt – Tweak the prompt by adding or removing details
- Try different seeds – Change the seed number to generate different variations
- Use image embeddings – For Stable Diffusion, use init images
With some experimentation, you should be able to closely recreate the original AI image from its extracted prompt.
Conclusion
Extracting prompts from AI images opens up many possibilities – we can understand how they were made, replicate and modify them, learn about how AI vision works, and more.
In this guide, we covered multiple techniques to reliably extract prompts from images created by stable diffusion, DALL-E, Midjourney and other algorithms. Methods ranged from reading metadata to using CLIP interrogators to manually reverse engineering images.
We also explored tips to fine-tune prompts and generation parameters to recreate the original AI image as faithfully as possible.
As AI art continues to rapidly progress, being able to reverse image prompts will prove an invaluable skill for artists, designers and casual users alike.