👩‍💻Using the website

The fastest and easiest way to generate images

Go to https://dreamlook.ai/image-gen in order to start generating images.

Generate images from base models

  1. Select a model ("Stable Diffusion 1.5", "Realistic Vision", etc...)

  2. Select a prompt preset (e.g. "Woman portrait") or fill in your own prompts

  3. Click "Generate"

Generate images from your trained models (i.e. checkpoints)

  1. First train a model on https://dreamlook.ai/dreambooth

Models are only available for 48h after they are trained. Afterwards they are gone and no images can be generated anymore.

  1. The trained model then appear in the "Model" dropdown on https://dreamlook.ai/image-gen:

  1. Write a prompt containing your instance prompt (in our example this would be "photo of ukj person"). The instance prompt acts as a "trigger" to generate images of your subject/object.

If you don't use your instance prompt token (ukj) in your prompt it's unlikely you'll get any good results.

  1. Click "Generate" 🌈


I can't see my model in the drop down. Where did it go?

We delete models after 48h, so if your dreambooth run is older than 48h you won't see it in the dropdown.

Currently, we don't offer generating images on models trained with Avatar service (https://dreamlook.ai/dreambooth-image-gen), so you won't find those models in the drop down.

What is "High Res Fix"?

High Res Fix (HRF) is a method of generating images at higher resolution than 512x512 while maintaining image quality and reducing artefacts (such as multiple heads). The process includes txt2img at lower resolution, resize to target resolution, and img2img at target resolution, so it can be seen as an upscaling method. Our implementation of HRF is slightly different from the one in AUTOMATIC1111.

Note that enabling HRF has an impact on performance. If you want to optimize for speed, choose 512x512 without HRF.

Can I use prompt weighting (emphasis) like in Automatic1111?

Yes. We use the same syntax as Automatic1111, meaning that words in brackets, such as(word), increase attention/emphasis to that word by a factor of 1.1, whereas [word] decreases attention by a factor of 1.1. You can specify an arbitrary weight with a colon (e.g., woman in a (red:1.4) dress). If you want to use literal brackets, you should escape them with backlashes (\(example\)). You can find a good summary of the rules on the Automatic1111 wiki page.

We currently do not support other Automatic1111 features, such as dynamic prompt editing or alternating words.

Do you support img2img/ControlNet? What about different samplers?

We currently only offer txt2img and not img2img. We focus on keeping the platform easy to use and build highly optimized features that give workable results out of the box.

In any case, please share with us if you are missing a feature - we are happy to consider adding it.

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