Personalize Stable Diffusion with your own images
Dreambooth trained on 5 images of a dog
Dreambooth is a method of personalizing text-to-image models, such as Stable Diffusion.
Dreambooth personalizes Stable Diffusion by fine tuning on a small set of reference images (around 3-5 images) that you provide.
Current models such as Stable Diffusion produce high-quality images, but it struggles to make new versions of your data in different settings or poses.
During fine-tuning, Dreambooth learns to recognize unique features of your data.
The model associates an identifier (called sks
) to your unique features.
The sks
identifier allows the model to embed your unique features into the output domain of the model.
The sks
identifier will be used to synthesize photorealistic images of your features in different scenes or poses.
The sks
identifier was chosen randomly, because it is a rare word in the English dictionary.
Training data of five dog photos
Please download the images of the dog found here to the --dataset-dir
folder.
--class-word
describes what images in your dataset contain (in this example, the dataset contains dog photos).
--regularization-prompt
describes the type of images you want to generate.
Make a directory with mkdir logs
and pass in the directory as --log-dir
to get logs in that directory.
We set sensible defaults for the steps, batch size, and learning rate. Refer to How do I change default settings? for more information.
Output of the prompt 'sks dog on the beach'
After doing a training run on Dreambooth, run the rubbrband eval
command.
In the --input-prompt
, make sure the class-word
(e.g. dog) is in the prompt.
In the --input-prompt
, make sure the sks
identifier is in the prompt.
sks
means, refer to How Does Dreambooth Work?--log-dir
Dreambooth fine tuning is very sensitive and may require changing the default settings to get good outputs.
This blog post covers some of the settings that have been found to work well.
Personalize Stable Diffusion with your own images
Dreambooth trained on 5 images of a dog
Dreambooth is a method of personalizing text-to-image models, such as Stable Diffusion.
Dreambooth personalizes Stable Diffusion by fine tuning on a small set of reference images (around 3-5 images) that you provide.
Current models such as Stable Diffusion produce high-quality images, but it struggles to make new versions of your data in different settings or poses.
During fine-tuning, Dreambooth learns to recognize unique features of your data.
The model associates an identifier (called sks
) to your unique features.
The sks
identifier allows the model to embed your unique features into the output domain of the model.
The sks
identifier will be used to synthesize photorealistic images of your features in different scenes or poses.
The sks
identifier was chosen randomly, because it is a rare word in the English dictionary.
Training data of five dog photos
Please download the images of the dog found here to the --dataset-dir
folder.
--class-word
describes what images in your dataset contain (in this example, the dataset contains dog photos).
--regularization-prompt
describes the type of images you want to generate.
Make a directory with mkdir logs
and pass in the directory as --log-dir
to get logs in that directory.
We set sensible defaults for the steps, batch size, and learning rate. Refer to How do I change default settings? for more information.
Output of the prompt 'sks dog on the beach'
After doing a training run on Dreambooth, run the rubbrband eval
command.
In the --input-prompt
, make sure the class-word
(e.g. dog) is in the prompt.
In the --input-prompt
, make sure the sks
identifier is in the prompt.
sks
means, refer to How Does Dreambooth Work?--log-dir
Dreambooth fine tuning is very sensitive and may require changing the default settings to get good outputs.
This blog post covers some of the settings that have been found to work well.